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Research Article

Twenty years of gender equality research: A scoping review based on a new semantic indicator

Contributed equally to this work with: Paola Belingheri, Filippo Chiarello, Andrea Fronzetti Colladon, Paola Rovelli

Roles Conceptualization, Formal analysis, Funding acquisition, Visualization, Writing – original draft, Writing – review & editing

Affiliation Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni, Università degli Studi di Pisa, Largo L. Lazzarino, Pisa, Italy

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Visualization, Writing – original draft, Writing – review & editing

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Engineering, University of Perugia, Perugia, Italy, Department of Management, Kozminski University, Warsaw, Poland

Roles Conceptualization, Formal analysis, Funding acquisition, Writing – original draft, Writing – review & editing

Affiliation Faculty of Economics and Management, Centre for Family Business Management, Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

• Paola Belingheri, 
• Filippo Chiarello, 
• Andrea Fronzetti Colladon, 
• Paola Rovelli

• Published: September 21, 2021
• https://doi.org/10.1371/journal.pone.0256474
• Reader Comments

9 Nov 2021: The PLOS ONE Staff (2021) Correction: Twenty years of gender equality research: A scoping review based on a new semantic indicator. PLOS ONE 16(11): e0259930. https://doi.org/10.1371/journal.pone.0259930 View correction

Gender equality is a major problem that places women at a disadvantage thereby stymieing economic growth and societal advancement. In the last two decades, extensive research has been conducted on gender related issues, studying both their antecedents and consequences. However, existing literature reviews fail to provide a comprehensive and clear picture of what has been studied so far, which could guide scholars in their future research. Our paper offers a scoping review of a large portion of the research that has been published over the last 22 years, on gender equality and related issues, with a specific focus on business and economics studies. Combining innovative methods drawn from both network analysis and text mining, we provide a synthesis of 15,465 scientific articles. We identify 27 main research topics, we measure their relevance from a semantic point of view and the relationships among them, highlighting the importance of each topic in the overall gender discourse. We find that prominent research topics mostly relate to women in the workforce–e.g., concerning compensation, role, education, decision-making and career progression. However, some of them are losing momentum, and some other research trends–for example related to female entrepreneurship, leadership and participation in the board of directors–are on the rise. Besides introducing a novel methodology to review broad literature streams, our paper offers a map of the main gender-research trends and presents the most popular and the emerging themes, as well as their intersections, outlining important avenues for future research.

Citation: Belingheri P, Chiarello F, Fronzetti Colladon A, Rovelli P (2021) Twenty years of gender equality research: A scoping review based on a new semantic indicator. PLoS ONE 16(9): e0256474. https://doi.org/10.1371/journal.pone.0256474

Editor: Elisa Ughetto, Politecnico di Torino, ITALY

Received: June 25, 2021; Accepted: August 6, 2021; Published: September 21, 2021

Copyright: © 2021 Belingheri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its supporting information files. The only exception is the text of the abstracts (over 15,000) that we have downloaded from Scopus. These abstracts can be retrieved from Scopus, but we do not have permission to redistribute them.

Funding: P.B and F.C.: Grant of the Department of Energy, Systems, Territory and Construction of the University of Pisa (DESTEC) for the project “Measuring Gender Bias with Semantic Analysis: The Development of an Assessment Tool and its Application in the European Space Industry. P.B., F.C., A.F.C., P.R.: Grant of the Italian Association of Management Engineering (AiIG), “Misure di sostegno ai soci giovani AiIG” 2020, for the project “Gender Equality Through Data Intelligence (GEDI)”. F.C.: EU project ASSETs+ Project (Alliance for Strategic Skills addressing Emerging Technologies in Defence) EAC/A03/2018 - Erasmus+ programme, Sector Skills Alliances, Lot 3: Sector Skills Alliance for implementing a new strategic approach (Blueprint) to sectoral cooperation on skills G.A. NUMBER: 612678-EPP-1-2019-1-IT-EPPKA2-SSA-B.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The persistent gender inequalities that currently exist across the developed and developing world are receiving increasing attention from economists, policymakers, and the general public [e.g., 1 – 3 ]. Economic studies have indicated that women’s education and entry into the workforce contributes to social and economic well-being [e.g., 4 , 5 ], while their exclusion from the labor market and from managerial positions has an impact on overall labor productivity and income per capita [ 6 , 7 ]. The United Nations selected gender equality, with an emphasis on female education, as part of the Millennium Development Goals [ 8 ], and gender equality at-large as one of the 17 Sustainable Development Goals (SDGs) to be achieved by 2030 [ 9 ]. These latter objectives involve not only developing nations, but rather all countries, to achieve economic, social and environmental well-being.

As is the case with many SDGs, gender equality is still far from being achieved and persists across education, access to opportunities, or presence in decision-making positions [ 7 , 10 , 11 ]. As we enter the last decade for the SDGs’ implementation, and while we are battling a global health pandemic, effective and efficient action becomes paramount to reach this ambitious goal.

Scholars have dedicated a massive effort towards understanding gender equality, its determinants, its consequences for women and society, and the appropriate actions and policies to advance women’s equality. Many topics have been covered, ranging from women’s education and human capital [ 12 , 13 ] and their role in society [e.g., 14 , 15 ], to their appointment in firms’ top ranked positions [e.g., 16 , 17 ] and performance implications [e.g., 18 , 19 ]. Despite some attempts, extant literature reviews provide a narrow view on these issues, restricted to specific topics–e.g., female students’ presence in STEM fields [ 20 ], educational gender inequality [ 5 ], the gender pay gap [ 21 ], the glass ceiling effect [ 22 ], leadership [ 23 ], entrepreneurship [ 24 ], women’s presence on the board of directors [ 25 , 26 ], diversity management [ 27 ], gender stereotypes in advertisement [ 28 ], or specific professions [ 29 ]. A comprehensive view on gender-related research, taking stock of key findings and under-studied topics is thus lacking.

Extant literature has also highlighted that gender issues, and their economic and social ramifications, are complex topics that involve a large number of possible antecedents and outcomes [ 7 ]. Indeed, gender equality actions are most effective when implemented in unison with other SDGs (e.g., with SDG 8, see [ 30 ]) in a synergetic perspective [ 10 ]. Many bodies of literature (e.g., business, economics, development studies, sociology and psychology) approach the problem of achieving gender equality from different perspectives–often addressing specific and narrow aspects. This sometimes leads to a lack of clarity about how different issues, circumstances, and solutions may be related in precipitating or mitigating gender inequality or its effects. As the number of papers grows at an increasing pace, this issue is exacerbated and there is a need to step back and survey the body of gender equality literature as a whole. There is also a need to examine synergies between different topics and approaches, as well as gaps in our understanding of how different problems and solutions work together. Considering the important topic of women’s economic and social empowerment, this paper aims to fill this gap by answering the following research question: what are the most relevant findings in the literature on gender equality and how do they relate to each other ?

To do so, we conduct a scoping review [ 31 ], providing a synthesis of 15,465 articles dealing with gender equity related issues published in the last twenty-two years, covering both the periods of the MDGs and the SDGs (i.e., 2000 to mid 2021) in all the journals indexed in the Academic Journal Guide’s 2018 ranking of business and economics journals. Given the huge amount of research conducted on the topic, we adopt an innovative methodology, which relies on social network analysis and text mining. These techniques are increasingly adopted when surveying large bodies of text. Recently, they were applied to perform analysis of online gender communication differences [ 32 ] and gender behaviors in online technology communities [ 33 ], to identify and classify sexual harassment instances in academia [ 34 ], and to evaluate the gender inclusivity of disaster management policies [ 35 ].

Applied to the title, abstracts and keywords of the articles in our sample, this methodology allows us to identify a set of 27 recurrent topics within which we automatically classify the papers. Introducing additional novelty, by means of the Semantic Brand Score (SBS) indicator [ 36 ] and the SBS BI app [ 37 ], we assess the importance of each topic in the overall gender equality discourse and its relationships with the other topics, as well as trends over time, with a more accurate description than that offered by traditional literature reviews relying solely on the number of papers presented in each topic.

This methodology, applied to gender equality research spanning the past twenty-two years, enables two key contributions. First, we extract the main message that each document is conveying and how this is connected to other themes in literature, providing a rich picture of the topics that are at the center of the discourse, as well as of the emerging topics. Second, by examining the semantic relationship between topics and how tightly their discourses are linked, we can identify the key relationships and connections between different topics. This semi-automatic methodology is also highly reproducible with minimum effort.

This literature review is organized as follows. In the next section, we present how we selected relevant papers and how we analyzed them through text mining and social network analysis. We then illustrate the importance of 27 selected research topics, measured by means of the SBS indicator. In the results section, we present an overview of the literature based on the SBS results–followed by an in-depth narrative analysis of the top 10 topics (i.e., those with the highest SBS) and their connections. Subsequently, we highlight a series of under-studied connections between the topics where there is potential for future research. Through this analysis, we build a map of the main gender-research trends in the last twenty-two years–presenting the most popular themes. We conclude by highlighting key areas on which research should focused in the future.

Our aim is to map a broad topic, gender equality research, that has been approached through a host of different angles and through different disciplines. Scoping reviews are the most appropriate as they provide the freedom to map different themes and identify literature gaps, thereby guiding the recommendation of new research agendas [ 38 ].

Several practical approaches have been proposed to identify and assess the underlying topics of a specific field using big data [ 39 – 41 ], but many of them fail without proper paper retrieval and text preprocessing. This is specifically true for a research field such as the gender-related one, which comprises the work of scholars from different backgrounds. In this section, we illustrate a novel approach for the analysis of scientific (gender-related) papers that relies on methods and tools of social network analysis and text mining. Our procedure has four main steps: (1) data collection, (2) text preprocessing, (3) keywords extraction and classification, and (4) evaluation of semantic importance and image.

Data collection

In this study, we analyze 22 years of literature on gender-related research. Following established practice for scoping reviews [ 42 ], our data collection consisted of two main steps, which we summarize here below.

Firstly, we retrieved from the Scopus database all the articles written in English that contained the term “gender” in their title, abstract or keywords and were published in a journal listed in the Academic Journal Guide 2018 ranking of the Chartered Association of Business Schools (CABS) ( https://charteredabs.org/wp-content/uploads/2018/03/AJG2018-Methodology.pdf ), considering the time period from Jan 2000 to May 2021. We used this information considering that abstracts, titles and keywords represent the most informative part of a paper, while using the full-text would increase the signal-to-noise ratio for information extraction. Indeed, these textual elements already demonstrated to be reliable sources of information for the task of domain lexicon extraction [ 43 , 44 ]. We chose Scopus as source of literature because of its popularity, its update rate, and because it offers an API to ease the querying process. Indeed, while it does not allow to retrieve the full text of scientific articles, the Scopus API offers access to titles, abstracts, citation information and metadata for all its indexed scholarly journals. Moreover, we decided to focus on the journals listed in the AJG 2018 ranking because we were interested in reviewing business and economics related gender studies only. The AJG is indeed widely used by universities and business schools as a reference point for journal and research rigor and quality. This first step, executed in June 2021, returned more than 55,000 papers.

In the second step–because a look at the papers showed very sparse results, many of which were not in line with the topic of this literature review (e.g., papers dealing with health care or medical issues, where the word gender indicates the gender of the patients)–we applied further inclusion criteria to make the sample more focused on the topic of this literature review (i.e., women’s gender equality issues). Specifically, we only retained those papers mentioning, in their title and/or abstract, both gender-related keywords (e.g., daughter, female, mother) and keywords referring to bias and equality issues (e.g., equality, bias, diversity, inclusion). After text pre-processing (see next section), keywords were first identified from a frequency-weighted list of words found in the titles, abstracts and keywords in the initial list of papers, extracted through text mining (following the same approach as [ 43 ]). They were selected by two of the co-authors independently, following respectively a bottom up and a top-down approach. The bottom-up approach consisted of examining the words found in the frequency-weighted list and classifying those related to gender and equality. The top-down approach consisted in searching in the word list for notable gender and equality-related words. Table 1 reports the sets of keywords we considered, together with some examples of words that were used to search for their presence in the dataset (a full list is provided in the S1 Text ). At end of this second step, we obtained a final sample of 15,465 relevant papers.

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https://doi.org/10.1371/journal.pone.0256474.t001

Text processing and keyword extraction

Text preprocessing aims at structuring text into a form that can be analyzed by statistical models. In the present section, we describe the preprocessing steps we applied to paper titles and abstracts, which, as explained below, partially follow a standard text preprocessing pipeline [ 45 ]. These activities have been performed using the R package udpipe [ 46 ].

The first step is n-gram extraction (i.e., a sequence of words from a given text sample) to identify which n-grams are important in the analysis, since domain-specific lexicons are often composed by bi-grams and tri-grams [ 47 ]. Multi-word extraction is usually implemented with statistics and linguistic rules, thus using the statistical properties of n-grams or machine learning approaches [ 48 ]. However, for the present paper, we used Scopus metadata in order to have a more effective and efficient n-grams collection approach [ 49 ]. We used the keywords of each paper in order to tag n-grams with their associated keywords automatically. Using this greedy approach, it was possible to collect all the keywords listed by the authors of the papers. From this list, we extracted only keywords composed by two, three and four words, we removed all the acronyms and rare keywords (i.e., appearing in less than 1% of papers), and we clustered keywords showing a high orthographic similarity–measured using a Levenshtein distance [ 50 ] lower than 2, considering these groups of keywords as representing same concepts, but expressed with different spelling. After tagging the n-grams in the abstracts, we followed a common data preparation pipeline that consists of the following steps: (i) tokenization, that splits the text into tokens (i.e., single words and previously tagged multi-words); (ii) removal of stop-words (i.e. those words that add little meaning to the text, usually being very common and short functional words–such as “and”, “or”, or “of”); (iii) parts-of-speech tagging, that is providing information concerning the morphological role of a word and its morphosyntactic context (e.g., if the token is a determiner, the next token is a noun or an adjective with very high confidence, [ 51 ]); and (iv) lemmatization, which consists in substituting each word with its dictionary form (or lemma). The output of the latter step allows grouping together the inflected forms of a word. For example, the verbs “am”, “are”, and “is” have the shared lemma “be”, or the nouns “cat” and “cats” both share the lemma “cat”. We preferred lemmatization over stemming [ 52 ] in order to obtain more interpretable results.

In addition, we identified a further set of keywords (with respect to those listed in the “keywords” field) by applying a series of automatic words unification and removal steps, as suggested in past research [ 53 , 54 ]. We removed: sparse terms (i.e., occurring in less than 0.1% of all documents), common terms (i.e., occurring in more than 10% of all documents) and retained only nouns and adjectives. It is relevant to notice that no document was lost due to these steps. We then used the TF-IDF function [ 55 ] to produce a new list of keywords. We additionally tested other approaches for the identification and clustering of keywords–such as TextRank [ 56 ] or Latent Dirichlet Allocation [ 57 ]–without obtaining more informative results.

Classification of research topics

To guide the literature analysis, two experts met regularly to examine the sample of collected papers and to identify the main topics and trends in gender research. Initially, they conducted brainstorming sessions on the topics they expected to find, due to their knowledge of the literature. This led to an initial list of topics. Subsequently, the experts worked independently, also supported by the keywords in paper titles and abstracts extracted with the procedure described above.

Considering all this information, each expert identified and clustered relevant keywords into topics. At the end of the process, the two assignments were compared and exhibited a 92% agreement. Another meeting was held to discuss discordant cases and reach a consensus. This resulted in a list of 27 topics, briefly introduced in Table 2 and subsequently detailed in the following sections.

https://doi.org/10.1371/journal.pone.0256474.t002

Evaluation of semantic importance

Working on the lemmatized corpus of the 15,465 papers included in our sample, we proceeded with the evaluation of semantic importance trends for each topic and with the analysis of their connections and prevalent textual associations. To this aim, we used the Semantic Brand Score indicator [ 36 ], calculated through the SBS BI webapp [ 37 ] that also produced a brand image report for each topic. For this study we relied on the computing resources of the ENEA/CRESCO infrastructure [ 58 ].

The Semantic Brand Score (SBS) is a measure of semantic importance that combines methods of social network analysis and text mining. It is usually applied for the analysis of (big) textual data to evaluate the importance of one or more brands, names, words, or sets of keywords [ 36 ]. Indeed, the concept of “brand” is intended in a flexible way and goes beyond products or commercial brands. In this study, we evaluate the SBS time-trends of the keywords defining the research topics discussed in the previous section. Semantic importance comprises the three dimensions of topic prevalence, diversity and connectivity. Prevalence measures how frequently a research topic is used in the discourse. The more a topic is mentioned by scientific articles, the more the research community will be aware of it, with possible increase of future studies; this construct is partly related to that of brand awareness [ 59 ]. This effect is even stronger, considering that we are analyzing the title, abstract and keywords of the papers, i.e. the parts that have the highest visibility. A very important characteristic of the SBS is that it considers the relationships among words in a text. Topic importance is not just a matter of how frequently a topic is mentioned, but also of the associations a topic has in the text. Specifically, texts are transformed into networks of co-occurring words, and relationships are studied through social network analysis [ 60 ]. This step is necessary to calculate the other two dimensions of our semantic importance indicator. Accordingly, a social network of words is generated for each time period considered in the analysis–i.e., a graph made of n nodes (words) and E edges weighted by co-occurrence frequency, with W being the set of edge weights. The keywords representing each topic were clustered into single nodes.

The construct of diversity relates to that of brand image [ 59 ], in the sense that it considers the richness and distinctiveness of textual (topic) associations. Considering the above-mentioned networks, we calculated diversity using the distinctiveness centrality metric–as in the formula presented by Fronzetti Colladon and Naldi [ 61 ].

Lastly, connectivity was measured as the weighted betweenness centrality [ 62 , 63 ] of each research topic node. We used the formula presented by Wasserman and Faust [ 60 ]. The dimension of connectivity represents the “brokerage power” of each research topic–i.e., how much it can serve as a bridge to connect other terms (and ultimately topics) in the discourse [ 36 ].

The SBS is the final composite indicator obtained by summing the standardized scores of prevalence, diversity and connectivity. Standardization was carried out considering all the words in the corpus, for each specific timeframe.

This methodology, applied to a large and heterogeneous body of text, enables to automatically identify two important sets of information that add value to the literature review. Firstly, the relevance of each topic in literature is measured through a composite indicator of semantic importance, rather than simply looking at word frequencies. This provides a much richer picture of the topics that are at the center of the discourse, as well as of the topics that are emerging in the literature. Secondly, it enables to examine the extent of the semantic relationship between topics, looking at how tightly their discourses are linked. In a field such as gender equality, where many topics are closely linked to each other and present overlaps in issues and solutions, this methodology offers a novel perspective with respect to traditional literature reviews. In addition, it ensures reproducibility over time and the possibility to semi-automatically update the analysis, as new papers become available.

Overview of main topics

In terms of descriptive textual statistics, our corpus is made of 15,465 text documents, consisting of a total of 2,685,893 lemmatized tokens (words) and 32,279 types. As a result, the type-token ratio is 1.2%. The number of hapaxes is 12,141, with a hapax-token ratio of 37.61%.

Fig 1 shows the list of 27 topics by decreasing SBS. The most researched topic is compensation , exceeding all others in prevalence, diversity, and connectivity. This means it is not only mentioned more often than other topics, but it is also connected to a greater number of other topics and is central to the discourse on gender equality. The next four topics are, in order of SBS, role , education , decision-making , and career progression . These topics, except for education , all concern women in the workforce. Between these first five topics and the following ones there is a clear drop in SBS scores. In particular, the topics that follow have a lower connectivity than the first five. They are hiring , performance , behavior , organization , and human capital . Again, except for behavior and human capital , the other three topics are purely related to women in the workforce. After another drop-off, the following topics deal prevalently with women in society. This trend highlights that research on gender in business journals has so far mainly paid attention to the conditions that women experience in business contexts, while also devoting some attention to women in society.

https://doi.org/10.1371/journal.pone.0256474.g001

Fig 2 shows the SBS time series of the top 10 topics. While there has been a general increase in the number of Scopus-indexed publications in the last decade, we notice that some SBS trends remain steady, or even decrease. In particular, we observe that the main topic of the last twenty-two years, compensation , is losing momentum. Since 2016, it has been surpassed by decision-making , education and role , which may indicate that literature is increasingly attempting to identify root causes of compensation inequalities. Moreover, in the last two years, the topics of hiring , performance , and organization are experiencing the largest importance increase.

https://doi.org/10.1371/journal.pone.0256474.g002

Fig 3 shows the SBS time trends of the remaining 17 topics (i.e., those not in the top 10). As we can see from the graph, there are some that maintain a steady trend–such as reputation , management , networks and governance , which also seem to have little importance. More relevant topics with average stationary trends (except for the last two years) are culture , family , and parenting . The feminine topic is among the most important here, and one of those that exhibit the larger variations over time (similarly to leadership ). On the other hand, the are some topics that, even if not among the most important, show increasing SBS trends; therefore, they could be considered as emerging topics and could become popular in the near future. These are entrepreneurship , leadership , board of directors , and sustainability . These emerging topics are also interesting to anticipate future trends in gender equality research that are conducive to overall equality in society.

https://doi.org/10.1371/journal.pone.0256474.g003

In addition to the SBS score of the different topics, the network of terms they are associated to enables to gauge the extent to which their images (textual associations) overlap or differ ( Fig 4 ).

https://doi.org/10.1371/journal.pone.0256474.g004

There is a central cluster of topics with high similarity, which are all connected with women in the workforce. The cluster includes topics such as organization , decision-making , performance , hiring , human capital , education and compensation . In addition, the topic of well-being is found within this cluster, suggesting that women’s equality in the workforce is associated to well-being considerations. The emerging topics of entrepreneurship and leadership are also closely connected with each other, possibly implying that leadership is a much-researched quality in female entrepreneurship. Topics that are relatively more distant include personality , politics , feminine , empowerment , management , board of directors , reputation , governance , parenting , masculine and network .

The following sections describe the top 10 topics and their main associations in literature (see Table 3 ), while providing a brief overview of the emerging topics.

https://doi.org/10.1371/journal.pone.0256474.t003

Compensation.

The topic of compensation is related to the topics of role , hiring , education and career progression , however, also sees a very high association with the words gap and inequality . Indeed, a well-known debate in degrowth economics centers around whether and how to adequately compensate women for their childbearing, childrearing, caregiver and household work [e.g., 30 ].

Even in paid work, women continue being offered lower compensations than their male counterparts who have the same job or cover the same role [ 64 – 67 ]. This severe inequality has been widely studied by scholars over the last twenty-two years. Dealing with this topic, some specific roles have been addressed. Specifically, research highlighted differences in compensation between female and male CEOs [e.g., 68 ], top executives [e.g., 69 ], and boards’ directors [e.g., 70 ]. Scholars investigated the determinants of these gaps, such as the gender composition of the board [e.g., 71 – 73 ] or women’s individual characteristics [e.g., 71 , 74 ].

Among these individual characteristics, education plays a relevant role [ 75 ]. Education is indeed presented as the solution for women, not only to achieve top executive roles, but also to reduce wage inequality [e.g., 76 , 77 ]. Past research has highlighted education influences on gender wage gaps, specifically referring to gender differences in skills [e.g., 78 ], college majors [e.g., 79 ], and college selectivity [e.g., 80 ].

Finally, the wage gap issue is strictly interrelated with hiring –e.g., looking at whether being a mother affects hiring and compensation [e.g., 65 , 81 ] or relating compensation to unemployment [e.g., 82 ]–and career progression –for instance looking at meritocracy [ 83 , 84 ] or the characteristics of the boss for whom women work [e.g., 85 ].

The roles covered by women have been deeply investigated. Scholars have focused on the role of women in their families and the society as a whole [e.g., 14 , 15 ], and, more widely, in business contexts [e.g., 18 , 81 ]. Indeed, despite still lagging behind their male counterparts [e.g., 86 , 87 ], in the last decade there has been an increase in top ranked positions achieved by women [e.g., 88 , 89 ]. Following this phenomenon, scholars have posed greater attention towards the presence of women in the board of directors [e.g., 16 , 18 , 90 , 91 ], given the increasing pressure to appoint female directors that firms, especially listed ones, have experienced. Other scholars have focused on the presence of women covering the role of CEO [e.g., 17 , 92 ] or being part of the top management team [e.g., 93 ]. Irrespectively of the level of analysis, all these studies tried to uncover the antecedents of women’s presence among top managers [e.g., 92 , 94 ] and the consequences of having a them involved in the firm’s decision-making –e.g., on performance [e.g., 19 , 95 , 96 ], risk [e.g., 97 , 98 ], and corporate social responsibility [e.g., 99 , 100 ].

Besides studying the difficulties and discriminations faced by women in getting a job [ 81 , 101 ], and, more specifically in the hiring , appointment, or career progression to these apical roles [e.g., 70 , 83 ], the majority of research of women’s roles dealt with compensation issues. Specifically, scholars highlight the pay-gap that still exists between women and men, both in general [e.g., 64 , 65 ], as well as referring to boards’ directors [e.g., 70 , 102 ], CEOs and executives [e.g., 69 , 103 , 104 ].

Finally, other scholars focused on the behavior of women when dealing with business. In this sense, particular attention has been paid to leadership and entrepreneurial behaviors. The former quite overlaps with dealing with the roles mentioned above, but also includes aspects such as leaders being stereotyped as masculine [e.g., 105 ], the need for greater exposure to female leaders to reduce biases [e.g., 106 ], or female leaders acting as queen bees [e.g., 107 ]. Regarding entrepreneurship , scholars mainly investigated women’s entrepreneurial entry [e.g., 108 , 109 ], differences between female and male entrepreneurs in the evaluations and funding received from investors [e.g., 110 , 111 ], and their performance gap [e.g., 112 , 113 ].

Education has long been recognized as key to social advancement and economic stability [ 114 ], for job progression and also a barrier to gender equality, especially in STEM-related fields. Research on education and gender equality is mostly linked with the topics of compensation , human capital , career progression , hiring , parenting and decision-making .

Education contributes to a higher human capital [ 115 ] and constitutes an investment on the part of women towards their future. In this context, literature points to the gender gap in educational attainment, and the consequences for women from a social, economic, personal and professional standpoint. Women are found to have less access to formal education and information, especially in emerging countries, which in turn may cause them to lose social and economic opportunities [e.g., 12 , 116 – 119 ]. Education in local and rural communities is also paramount to communicate the benefits of female empowerment , contributing to overall societal well-being [e.g., 120 ].

Once women access education, the image they have of the world and their place in society (i.e., habitus) affects their education performance [ 13 ] and is passed on to their children. These situations reinforce gender stereotypes, which become self-fulfilling prophecies that may negatively affect female students’ performance by lowering their confidence and heightening their anxiety [ 121 , 122 ]. Besides formal education, also the information that women are exposed to on a daily basis contributes to their human capital . Digital inequalities, for instance, stems from men spending more time online and acquiring higher digital skills than women [ 123 ].

Education is also a factor that should boost employability of candidates and thus hiring , career progression and compensation , however the relationship between these factors is not straightforward [ 115 ]. First, educational choices ( decision-making ) are influenced by variables such as self-efficacy and the presence of barriers, irrespectively of the career opportunities they offer, especially in STEM [ 124 ]. This brings additional difficulties to women’s enrollment and persistence in scientific and technical fields of study due to stereotypes and biases [ 125 , 126 ]. Moreover, access to education does not automatically translate into job opportunities for women and minority groups [ 127 , 128 ] or into female access to managerial positions [ 129 ].

Finally, parenting is reported as an antecedent of education [e.g., 130 ], with much of the literature focusing on the role of parents’ education on the opportunities afforded to children to enroll in education [ 131 – 134 ] and the role of parenting in their offspring’s perception of study fields and attitudes towards learning [ 135 – 138 ]. Parental education is also a predictor of the other related topics, namely human capital and compensation [ 139 ].

Decision-making.

This literature mainly points to the fact that women are thought to make decisions differently than men. Women have indeed different priorities, such as they care more about people’s well-being, working with people or helping others, rather than maximizing their personal (or their firm’s) gain [ 140 ]. In other words, women typically present more communal than agentic behaviors, which are instead more frequent among men [ 141 ]. These different attitude, behavior and preferences in turn affect the decisions they make [e.g., 142 ] and the decision-making of the firm in which they work [e.g., 143 ].

At the individual level, gender affects, for instance, career aspirations [e.g., 144 ] and choices [e.g., 142 , 145 ], or the decision of creating a venture [e.g., 108 , 109 , 146 ]. Moreover, in everyday life, women and men make different decisions regarding partners [e.g., 147 ], childcare [e.g., 148 ], education [e.g., 149 ], attention to the environment [e.g., 150 ] and politics [e.g., 151 ].

At the firm level, scholars highlighted, for example, how the presence of women in the board affects corporate decisions [e.g., 152 , 153 ], that female CEOs are more conservative in accounting decisions [e.g., 154 ], or that female CFOs tend to make more conservative decisions regarding the firm’s financial reporting [e.g., 155 ]. Nevertheless, firm level research also investigated decisions that, influenced by gender bias, affect women, such as those pertaining hiring [e.g., 156 , 157 ], compensation [e.g., 73 , 158 ], or the empowerment of women once appointed [ 159 ].

Career progression.

Once women have entered the workforce, the key aspect to achieve gender equality becomes career progression , including efforts toward overcoming the glass ceiling. Indeed, according to the SBS analysis, career progression is highly related to words such as work, social issues and equality. The topic with which it has the highest semantic overlap is role , followed by decision-making , hiring , education , compensation , leadership , human capital , and family .

Career progression implies an advancement in the hierarchical ladder of the firm, assigning managerial roles to women. Coherently, much of the literature has focused on identifying rationales for a greater female participation in the top management team and board of directors [e.g., 95 ] as well as the best criteria to ensure that the decision-makers promote the most valuable employees irrespectively of their individual characteristics, such as gender [e.g., 84 ]. The link between career progression , role and compensation is often provided in practice by performance appraisal exercises, frequently rooted in a culture of meritocracy that guides bonuses, salary increases and promotions. However, performance appraisals can actually mask gender-biased decisions where women are held to higher standards than their male colleagues [e.g., 83 , 84 , 95 , 160 , 161 ]. Women often have less opportunities to gain leadership experience and are less visible than their male colleagues, which constitute barriers to career advancement [e.g., 162 ]. Therefore, transparency and accountability, together with procedures that discourage discretionary choices, are paramount to achieve a fair career progression [e.g., 84 ], together with the relaxation of strict job boundaries in favor of cross-functional and self-directed tasks [e.g., 163 ].

In addition, a series of stereotypes about the type of leadership characteristics that are required for top management positions, which fit better with typical male and agentic attributes, are another key barrier to career advancement for women [e.g., 92 , 160 ].

Hiring is the entrance gateway for women into the workforce. Therefore, it is related to other workforce topics such as compensation , role , career progression , decision-making , human capital , performance , organization and education .

A first stream of literature focuses on the process leading up to candidates’ job applications, demonstrating that bias exists before positions are even opened, and it is perpetuated both by men and women through networking and gatekeeping practices [e.g., 164 , 165 ].

The hiring process itself is also subject to biases [ 166 ], for example gender-congruity bias that leads to men being preferred candidates in male-dominated sectors [e.g., 167 ], women being hired in positions with higher risk of failure [e.g., 168 ] and limited transparency and accountability afforded by written processes and procedures [e.g., 164 ] that all contribute to ascriptive inequality. In addition, providing incentives for evaluators to hire women may actually work to this end; however, this is not the case when supporting female candidates endangers higher-ranking male ones [ 169 ].

Another interesting perspective, instead, looks at top management teams’ composition and the effects on hiring practices, indicating that firms with more women in top management are less likely to lay off staff [e.g., 152 ].

Performance.

Several scholars posed their attention towards women’s performance, its consequences [e.g., 170 , 171 ] and the implications of having women in decision-making positions [e.g., 18 , 19 ].

At the individual level, research focused on differences in educational and academic performance between women and men, especially referring to the gender gap in STEM fields [e.g., 171 ]. The presence of stereotype threats–that is the expectation that the members of a social group (e.g., women) “must deal with the possibility of being judged or treated stereotypically, or of doing something that would confirm the stereotype” [ 172 ]–affects women’s interested in STEM [e.g., 173 ], as well as their cognitive ability tests, penalizing them [e.g., 174 ]. A stronger gender identification enhances this gap [e.g., 175 ], whereas mentoring and role models can be used as solutions to this problem [e.g., 121 ]. Despite the negative effect of stereotype threats on girls’ performance [ 176 ], female and male students perform equally in mathematics and related subjects [e.g., 177 ]. Moreover, while individuals’ performance at school and university generally affects their achievements and the field in which they end up working, evidence reveals that performance in math or other scientific subjects does not explain why fewer women enter STEM working fields; rather this gap depends on other aspects, such as culture, past working experiences, or self-efficacy [e.g., 170 ]. Finally, scholars have highlighted the penalization that women face for their positive performance, for instance when they succeed in traditionally male areas [e.g., 178 ]. This penalization is explained by the violation of gender-stereotypic prescriptions [e.g., 179 , 180 ], that is having women well performing in agentic areas, which are typical associated to men. Performance penalization can thus be overcome by clearly conveying communal characteristics and behaviors [ 178 ].

Evidence has been provided on how the involvement of women in boards of directors and decision-making positions affects firms’ performance. Nevertheless, results are mixed, with some studies showing positive effects on financial [ 19 , 181 , 182 ] and corporate social performance [ 99 , 182 , 183 ]. Other studies maintain a negative association [e.g., 18 ], and other again mixed [e.g., 184 ] or non-significant association [e.g., 185 ]. Also with respect to the presence of a female CEO, mixed results emerged so far, with some researches demonstrating a positive effect on firm’s performance [e.g., 96 , 186 ], while other obtaining only a limited evidence of this relationship [e.g., 103 ] or a negative one [e.g., 187 ].

Finally, some studies have investigated whether and how women’s performance affects their hiring [e.g., 101 ] and career progression [e.g., 83 , 160 ]. For instance, academic performance leads to different returns in hiring for women and men. Specifically, high-achieving men are called back significantly more often than high-achieving women, which are penalized when they have a major in mathematics; this result depends on employers’ gendered standards for applicants [e.g., 101 ]. Once appointed, performance ratings are more strongly related to promotions for women than men, and promoted women typically show higher past performance ratings than those of promoted men. This suggesting that women are subject to stricter standards for promotion [e.g., 160 ].

Behavioral aspects related to gender follow two main streams of literature. The first examines female personality and behavior in the workplace, and their alignment with cultural expectations or stereotypes [e.g., 188 ] as well as their impacts on equality. There is a common bias that depicts women as less agentic than males. Certain characteristics, such as those more congruent with male behaviors–e.g., self-promotion [e.g., 189 ], negotiation skills [e.g., 190 ] and general agentic behavior [e.g., 191 ]–, are less accepted in women. However, characteristics such as individualism in women have been found to promote greater gender equality in society [ 192 ]. In addition, behaviors such as display of emotions [e.g., 193 ], which are stereotypically female, work against women’s acceptance in the workplace, requiring women to carefully moderate their behavior to avoid exclusion. A counter-intuitive result is that women and minorities, which are more marginalized in the workplace, tend to be better problem-solvers in innovation competitions due to their different knowledge bases [ 194 ].

The other side of the coin is examined in a parallel literature stream on behavior towards women in the workplace. As a result of biases, prejudices and stereotypes, women may experience adverse behavior from their colleagues, such as incivility and harassment, which undermine their well-being [e.g., 195 , 196 ]. Biases that go beyond gender, such as for overweight people, are also more strongly applied to women [ 197 ].

Organization.

The role of women and gender bias in organizations has been studied from different perspectives, which mirror those presented in detail in the following sections. Specifically, most research highlighted the stereotypical view of leaders [e.g., 105 ] and the roles played by women within firms, for instance referring to presence in the board of directors [e.g., 18 , 90 , 91 ], appointment as CEOs [e.g., 16 ], or top executives [e.g., 93 ].

Scholars have investigated antecedents and consequences of the presence of women in these apical roles. On the one side they looked at hiring and career progression [e.g., 83 , 92 , 160 , 168 , 198 ], finding women typically disadvantaged with respect to their male counterparts. On the other side, they studied women’s leadership styles and influence on the firm’s decision-making [e.g., 152 , 154 , 155 , 199 ], with implications for performance [e.g., 18 , 19 , 96 ].

Human capital.

Human capital is a transverse topic that touches upon many different aspects of female gender equality. As such, it has the most associations with other topics, starting with education as mentioned above, with career-related topics such as role , decision-making , hiring , career progression , performance , compensation , leadership and organization . Another topic with which there is a close connection is behavior . In general, human capital is approached both from the education standpoint but also from the perspective of social capital.

The behavioral aspect in human capital comprises research related to gender differences for example in cultural and religious beliefs that influence women’s attitudes and perceptions towards STEM subjects [ 142 , 200 – 202 ], towards employment [ 203 ] or towards environmental issues [ 150 , 204 ]. These cultural differences also emerge in the context of globalization which may accelerate gender equality in the workforce [ 205 , 206 ]. Gender differences also appear in behaviors such as motivation [ 207 ], and in negotiation [ 190 ], and have repercussions on women’s decision-making related to their careers. The so-called gender equality paradox sees women in countries with lower gender equality more likely to pursue studies and careers in STEM fields, whereas the gap in STEM enrollment widens as countries achieve greater equality in society [ 171 ].

Career progression is modeled by literature as a choice-process where personal preferences, culture and decision-making affect the chosen path and the outcomes. Some literature highlights how women tend to self-select into different professions than men, often due to stereotypes rather than actual ability to perform in these professions [ 142 , 144 ]. These stereotypes also affect the perceptions of female performance or the amount of human capital required to equal male performance [ 110 , 193 , 208 ], particularly for mothers [ 81 ]. It is therefore often assumed that women are better suited to less visible and less leadership -oriented roles [ 209 ]. Women also express differing preferences towards work-family balance, which affect whether and how they pursue human capital gains [ 210 ], and ultimately their career progression and salary .

On the other hand, men are often unaware of gendered processes and behaviors that they carry forward in their interactions and decision-making [ 211 , 212 ]. Therefore, initiatives aimed at increasing managers’ human capital –by raising awareness of gender disparities in their organizations and engaging them in diversity promotion–are essential steps to counter gender bias and segregation [ 213 ].

Emerging topics: Leadership and entrepreneurship

Among the emerging topics, the most pervasive one is women reaching leadership positions in the workforce and in society. This is still a rare occurrence for two main types of factors, on the one hand, bias and discrimination make it harder for women to access leadership positions [e.g., 214 – 216 ], on the other hand, the competitive nature and high pressure associated with leadership positions, coupled with the lack of women currently represented, reduce women’s desire to achieve them [e.g., 209 , 217 ]. Women are more effective leaders when they have access to education, resources and a diverse environment with representation [e.g., 218 , 219 ].

One sector where there is potential for women to carve out a leadership role is entrepreneurship . Although at the start of the millennium the discourse on entrepreneurship was found to be “discriminatory, gender-biased, ethnocentrically determined and ideologically controlled” [ 220 ], an increasing body of literature is studying how to stimulate female entrepreneurship as an alternative pathway to wealth, leadership and empowerment [e.g., 221 ]. Many barriers exist for women to access entrepreneurship, including the institutional and legal environment, social and cultural factors, access to knowledge and resources, and individual behavior [e.g., 222 , 223 ]. Education has been found to raise women’s entrepreneurial intentions [e.g., 224 ], although this effect is smaller than for men [e.g., 109 ]. In addition, increasing self-efficacy and risk-taking behavior constitute important success factors [e.g., 225 ].

Finally, the topic of sustainability is worth mentioning, as it is the primary objective of the SDGs and is closely associated with societal well-being. As society grapples with the effects of climate change and increasing depletion of natural resources, a narrative has emerged on women and their greater link to the environment [ 226 ]. Studies in developed countries have found some support for women leaders’ attention to sustainability issues in firms [e.g., 227 – 229 ], and smaller resource consumption by women [ 230 ]. At the same time, women will likely be more affected by the consequences of climate change [e.g., 230 ] but often lack the decision-making power to influence local decision-making on resource management and environmental policies [e.g., 231 ].

Research gaps and conclusions

Research on gender equality has advanced rapidly in the past decades, with a steady increase in publications, both in mainstream topics related to women in education and the workforce, and in emerging topics. Through a novel approach combining methods of text mining and social network analysis, we examined a comprehensive body of literature comprising 15,465 papers published between 2000 and mid 2021 on topics related to gender equality. We identified a set of 27 topics addressed by the literature and examined their connections.

At the highest level of abstraction, it is worth noting that papers abound on the identification of issues related to gender inequalities and imbalances in the workforce and in society. Literature has thoroughly examined the (unconscious) biases, barriers, stereotypes, and discriminatory behaviors that women are facing as a result of their gender. Instead, there are much fewer papers that discuss or demonstrate effective solutions to overcome gender bias [e.g., 121 , 143 , 145 , 163 , 194 , 213 , 232 ]. This is partly due to the relative ease in studying the status quo, as opposed to studying changes in the status quo. However, we observed a shift in the more recent years towards solution seeking in this domain, which we strongly encourage future researchers to focus on. In the future, we may focus on collecting and mapping pro-active contributions to gender studies, using additional Natural Language Processing techniques, able to measure the sentiment of scientific papers [ 43 ].

All of the mainstream topics identified in our literature review are closely related, and there is a wealth of insights looking at the intersection between issues such as education and career progression or human capital and role . However, emerging topics are worthy of being furtherly explored. It would be interesting to see more work on the topic of female entrepreneurship , exploring aspects such as education , personality , governance , management and leadership . For instance, how can education support female entrepreneurship? How can self-efficacy and risk-taking behaviors be taught or enhanced? What are the differences in managerial and governance styles of female entrepreneurs? Which personality traits are associated with successful entrepreneurs? Which traits are preferred by venture capitalists and funding bodies?

The emerging topic of sustainability also deserves further attention, as our society struggles with climate change and its consequences. It would be interesting to see more research on the intersection between sustainability and entrepreneurship , looking at how female entrepreneurs are tackling sustainability issues, examining both their business models and their company governance . In addition, scholars are suggested to dig deeper into the relationship between family values and behaviors.

Moreover, it would be relevant to understand how women’s networks (social capital), or the composition and structure of social networks involving both women and men, enable them to increase their remuneration and reach top corporate positions, participate in key decision-making bodies, and have a voice in communities. Furthermore, the achievement of gender equality might significantly change firm networks and ecosystems, with important implications for their performance and survival.

Similarly, research at the nexus of (corporate) governance , career progression , compensation and female empowerment could yield useful insights–for example discussing how enterprises, institutions and countries are managed and the impact for women and other minorities. Are there specific governance structures that favor diversity and inclusion?

Lastly, we foresee an emerging stream of research pertaining how the spread of the COVID-19 pandemic challenged women, especially in the workforce, by making gender biases more evident.

For our analysis, we considered a set of 15,465 articles downloaded from the Scopus database (which is the largest abstract and citation database of peer-reviewed literature). As we were interested in reviewing business and economics related gender studies, we only considered those papers published in journals listed in the Academic Journal Guide (AJG) 2018 ranking of the Chartered Association of Business Schools (CABS). All the journals listed in this ranking are also indexed by Scopus. Therefore, looking at a single database (i.e., Scopus) should not be considered a limitation of our study. However, future research could consider different databases and inclusion criteria.

With our literature review, we offer researchers a comprehensive map of major gender-related research trends over the past twenty-two years. This can serve as a lens to look to the future, contributing to the achievement of SDG5. Researchers may use our study as a starting point to identify key themes addressed in the literature. In addition, our methodological approach–based on the use of the Semantic Brand Score and its webapp–could support scholars interested in reviewing other areas of research.

Supporting information

S1 text. keywords used for paper selection..

https://doi.org/10.1371/journal.pone.0256474.s001

Acknowledgments

The computing resources and the related technical support used for this work have been provided by CRESCO/ENEAGRID High Performance Computing infrastructure and its staff. CRESCO/ENEAGRID High Performance Computing infrastructure is funded by ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development and by Italian and European research programmes (see http://www.cresco.enea.it/english for information).

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Research Roundup: How Women Experience the Workplace Today

• Dagny Dukach

New studies on what happens when women reach the top, the barriers they still face, and the (sometimes hidden) stresses they deal with.

What will it take to make gender equity in the workplace a reality? It’s a complicated question, with no easy answers — but research from a wide array of academic disciplines aims to expand our understanding of the unique challenges and opportunities women face today. In this research roundup, we share highlights from several new and forthcoming studies that explore the many facets of gender at work.

In 2021, the gender gap in U.S. workforce participation hit an all-time low . But of course, substantial gender disparities persist in pay, leadership representation, access to resources, and many other key metrics. How can we make sense of all these different dimensions of gender equity in the workplace?

• Dagny Dukach is a former associate editor at Harvard Business Review.

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Frequently asked questions about gender equality

Resource date: 2005

Author: UNFPA

What is meant by gender?

The term gender refers to the economic, social and cultural attributes and opportunities associated with being male or female. In most societies, being a man or a woman is not simply a matter of different biological and physical characteristics. Men and women face different expectations about how they should dress, behave or work. Relations between men and women, whether in the family, the workplace or the public sphere, also reflect understandings of the talents, characteristics and behaviour appropriate to women and to men. Gender thus differs from sex in that it is social and cultural in nature rather than biological. Gender attributes and characteristics, encompassing, inter alia, the roles that men and women play and the expectations placed upon them, vary widely among societies and change over time. But the fact that gender attributes are socially constructed means that they are also amenable to change in ways that can make a society more just and equitable.

What is the difference between gender equity, gender equality and women’s empowerment?

Gender equity is the process of being fair to women and men. To ensure fairness, strategies and measures must often be available to compensate for women’s historical and social disadvantages that prevent women and men from otherwise operating on a level playing field. Equity leads to equality. Gender equality requires equal enjoyment by women and men of socially-valued goods, opportunities, resources and rewards. Where gender inequality exists, it is generally women who are excluded or disadvantaged in relation to decision-making and access to economic and social resources. Therefore a critical aspect of promoting gender equality is the empowerment of women, with a focus on identifying and redressing power imbalances and giving women more autonomy to manage their own lives. Gender equality does not mean that men and women become the same; only that access to opportunities and life changes is neither dependent on, nor constrained by, their sex. Achieving gender equality requires women’s empowerment to ensure that decision-making at private and public levels, and access to resources are no longer weighted in men’s favour, so that both women and men can fully participate as equal partners in productive and reproductive life.

Why is it important to take gender concerns into account in programme design and implementation?

Taking gender concerns into account when designing and implementing population and development programmes therefore is important for two reasons. First, there are differences between the roles of men and women, differences that demand different approaches. Second, there is systemic inequality between men and women. Universally, there are clear patterns of women’s inferior access to resources and opportunities. Moreover, women are systematically under-represented in decision-making processes that shape their societies and their own lives. This pattern of inequality is a constraint to the progress of any society because it limits the opportunities of one-half of its population. When women are constrained from reaching their full potential, that potential is lost to society as a whole. Programme design and implementation should endeavour to address either or both of these factors.

What is gender mainstreaming?

Gender mainstreaming is a strategy for integrating gender concerns in the analysis, formulation and monitoring of policies, programmes and projects. It is therefore a means to an end, not an end in itself; a process, not a goal. The purpose of gender mainstreaming is to promote gender equality and the empowerment of women in population and development activities. This requires addressing both the condition, as well as the position, of women and men in society. Gender mainstreaming therefore aims to strengthen the legitimacy of gender equality values by addressing known gender disparities and gaps in such areas as the division of labour between men and women; access to and control over resources; access to services, information and opportunities; and distribution of power and decision-making. UNFPA has adopted the mainstreaming of gender concerns into all population and development activities as the primary means of achieving the commitments on gender equality, equity and empowerment of women stemming from the International Conference on Population and Development.

Gender mainstreaming, as a strategy, does not preclude interventions that focus only on women or only on men. In some instances, the gender analysis that precedes programme design and development reveals severe inequalities that call for an initial strategy of sex-specific interventions. However, such sex-specific interventions should still aim to reduce identified gender disparities by focusing on equality or inequity as the objective rather than on men or women as a target group. In such a context, sex-specific interventions are still important aspects of a gender mainstreaming strategy. When implemented correctly, they should not contribute to a marginalization of men in such a critical area as access to reproductive and sexual health services. Nor should they contribute to the evaporation of gains or advances already secured by women. Rather, they should consolidate such gains that are central building blocks towards gender equality.

Why is gender equality important?

Gender equality is intrinsically linked to sustainable development and is vital to the realization of human rights for all. The overall objective of gender equality is a society in which women and men enjoy the same opportunities, rights and obligations in all spheres of life. Equality between men and women exists when both sexes are able to share equally in the distribution of power and influence; have equal opportunities for financial independence through work or through setting up businesses; enjoy equal access to education and the opportunity to develop personal ambitions, interests and talents; share responsibility for the home and children and are completely free from coercion, intimidation and gender-based violence both at work and at home.

Within the context of population and development programmes, gender equality is critical because it will enable women and men to make decisions that impact more positively on their own sexual and reproductive health as well as that of their spouses and families. Decision-making with regard to such issues as age at marriage, timing of births, use of contraception, and recourse to harmful practices (such as female genital cutting) stands to be improved with the achievement of gender equality.

However it is important to acknowledge that where gender inequality exists, it is generally women who are excluded or disadvantaged in relation to decision-making and access to economic and social resources. Therefore a critical aspect of promoting gender equality is the empowerment of women, with a focus on identifying and redressing power imbalances and giving women more autonomy to manage their own lives. This would enable them to make decisions and take actions to achieve and maintain their own reproductive and sexual health. Gender equality and women’s empowerment do not mean that men and women become the same; only that access to opportunities and life changes is neither dependent on, nor constrained by, their sex.

Is gender equality a concern for men?

The achievement of gender equality implies changes for both men and women. More equitable relationships will need to be based on a redefinition of the rights and responsibilities of women and men in all spheres of life, including the family, the workplace and the society at large. It is therefore crucial not to overlook gender as an aspect of men’s social identity. This fact is, indeed, often overlooked, because the tendency is to consider male characteristics and attributes as the norm, and those of women as a variation of the norm.

But the lives of men are just as strongly influenced by gender as those of women. Societal norms and conceptions of masculinity and expectations of men as leaders, husbands or sons create demands on men and shape their behaviour. Men are too often expected to concentrate on the material needs of their families, rather than on the nurturing and caring roles assigned to women. Socialization in the family and later in schools promotes risk-taking behaviour among young men, and this is often reinforced through peer pressure and media stereotypes. So the lifestyles that men’s roles demand often result in their being more exposed to greater risks of morbidity and mortality than women. These risks include ones relating to accidents, violence and alcohol consumption.

Men also have the right to assume a more nurturing role, and opportunities for them to do so should be promoted. Equally, however, men have responsibilities in regard to child health and to their own and their partners’ sexual and reproductive health. Addressing these rights and responsibilities entails recognizing men’s specific health problems, as well as their needs and the conditions that shape them. The adoption of a gender perspective is an important first step; it reveals that there are disadvantages and costs to men accruing from patterns of gender difference. It also underscores that gender equality is concerned not only with the roles, responsibilities and needs of women and men, but also with the interrelationships between them.

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Economic Inequality by Gender

How big are the inequalities in pay, jobs, and wealth between men and women? What causes these differences?

By Esteban Ortiz-Ospina, Joe Hasell and Max Roser

This page was first published in March 2018 and last revised in March 2024.

On this page, you can find writing, visualizations, and data on how big the inequalities in pay, jobs, and wealth are between men and women, how they have changed over time, and what may be causing them

Although economic gender inequalities remain common and large, they are today smaller than they used to be some decades ago.

Related topics

Women's Employment

How does women’s labor force participation differ across countries? How has it changed over time? What is behind these differences and changes?

Women’s Rights

How has the protection of women’s rights changed over time? How does it differ across countries? Explore global data and research on women’s rights.

Maternal Mortality

What could be more tragic than a mother losing her life in the moment that she is giving birth to her newborn? Why are mothers dying and what can be done to prevent these deaths?

See all interactive charts on economic inequality by gender ↓

How does the gender pay gap look like across countries and over time?

The 'gender pay gap' comes up often in political debates , policy reports , and everyday news . But what is it? What does it tell us? Is it different from country to country? How does it change over time?

Here we try to answer these questions, providing an empirical overview of the gender pay gap across countries and over time.

The gender pay gap measures inequality but not necessarily discrimination

The gender pay gap (or the gender wage gap) is a metric that tells us the difference in pay (or wages, or income) between women and men. It's a measure of inequality and captures a concept that is broader than the concept of equal pay for equal work.

Differences in pay between men and women capture differences along many possible dimensions, including worker education, experience, and occupation. When the gender pay gap is calculated by comparing all male workers to all female workers – irrespective of differences along these additional dimensions – the result is the 'raw' or 'unadjusted' pay gap. On the contrary, when the gap is calculated after accounting for underlying differences in education, experience, etc., then the result is the 'adjusted' pay gap.

Discrimination in hiring practices can exist in the absence of pay gaps – for example, if women know they will be treated unfairly and hence choose not to participate in the labor market. Similarly, it is possible to observe large pay gaps in the absence of discrimination in hiring practices – for example, if women get fair treatment but apply for lower-paid jobs.

The implication is that observing differences in pay between men and women is neither necessary nor sufficient to prove discrimination in the workplace. Both discrimination and inequality are important. But they are not the same.

In most countries, there is a substantial gender pay gap

Cross-country data on the gender pay gap is patchy, but the most complete source in terms of coverage is the United Nation's International Labour Organization (ILO). The visualization here presents this data. You can add observations by clicking on the option 'add country' at the bottom of the chart.

The estimates shown here correspond to differences between the average hourly earnings of men and women (expressed as a percentage of average hourly earnings of men), and cover all workers irrespective of whether they work full-time or part-time. 1

As we can see: (i) in most countries the gap is positive – women earn less than men, and (ii) there are large differences in the size of this gap across countries. 2

In most countries, the gender pay gap has decreased in the last couple of decades

How is the gender pay gap changing over time? To answer this question, let's consider this chart showing available estimates from the OECD. These estimates include OECD member states, as well as some other non-member countries, and they are the longest available series of cross-country data on the gender pay gap that we are aware of.

Here we see that the gap is large in most OECD countries, but it has been going down in the last couple of decades. In some cases the reduction is remarkable. In the United States, for example, the gap declined by more than half.

These estimates are not directly comparable to those from the ILO, because the pay gap is measured slightly differently here: The OECD estimates refer to percent differences in median earnings (i.e. the gap here captures differences between men and women in the middle of the earnings distribution), and they cover only full-time employees and self-employed workers (i.e. the gap here excludes disparities that arise from differences in hourly wages for part-time and full-time workers).

However, the ILO data shows similar trends.

The conclusion is that in most countries with available data, the gender pay gap has decreased in the last couple of decades.

The gender pay gap is larger for older workers

The United States Census Bureau defines the pay gap as the ratio between median wages – that is, they measure the gap by calculating the wages of men and women at the middle of the earnings distribution, and dividing them.

By this measure, the gender wage gap is expressed as a percent (median earnings of women as a share of median earnings of men) and it is always positive. Here, values below 100% mean that women earn less than men, while values above 100% mean that women earn more. Values closer to 100% reflect a lower gap.

The next chart shows available estimates of this metric for full-time workers in the US, by age group.

First, we see that the series trends upwards, meaning the gap has been shrinking in the last couple of decades. Secondly, we see that there are important differences by age.

The second point is crucial to understanding the gender pay gap: the gap is a statistic that changes during the life of a worker. In most rich countries, it’s small when formal education ends and employment begins, and it increases with age. As we discuss in our analysis of the determinants below, the gender pay gap tends to increase when women marry and when/if they have children.

The gender pay gap is smaller in middle-income countries – which tend to be countries with low labor force participation of women

The chart here plots available ILO estimates on the gender pay gap against GDP per capita. As we can see there is a weak positive correlation between GDP per capita and the gender pay gap. However, the chart shows that the relationship is not really linear. Actually, middle-income countries tend to have the smallest pay gap.

The fact that middle-income countries have low gender wage gaps is, to a large extent, the result of selection of women into employment . Olivetti and Petrongolo (2008) explain it as follows: “[I]f women who are employed tend to have relatively high‐wage characteristics, low female employment rates may become consistent with low gender wage gaps simply because low‐wage women would not feature in the observed wage distribution.” 3

Olivetti and Petrongolo (2008) show that this pattern holds in the data: unadjusted gender wage gaps across countries tend to be negatively correlated with gender employment gaps. That is, the gender pay gaps tend to be smaller where relatively fewer women participate in the labor force .

So, rather than reflect greater equality, the lower wage gaps observed in some countries could indicate that only women with certain characteristics – for instance, with no husband or children – are entering the workforce.

Why is there a gender pay gap?

In almost all countries, if you compare the wages of men and women you find that women tend to earn less than men.  These inequalities have been narrowing across the world. In particular, most high-income countries have seen sizeable reductions in the gender pay gap over the last couple of decades.

How did these reductions come about and why do substantial gaps remain?

Before we get into the details, here is a preview of the main points.

• An important part of the reduction in the gender pay gap in rich countries over the last decades is due to a historical narrowing, and often even reversal of the education gap between men and women.
• Today, education is relatively unimportant in explaining the remaining gender pay gap in rich countries. In contrast, the characteristics of the jobs that women tend to do, remain important contributing factors.
• The gender pay gap is not a direct metric of discrimination. However, evidence from different contexts suggests discrimination is indeed important to understand the gender pay gap. Similarly, social norms affecting the gender distribution of labor are important determinants of wage inequality.
• On the other hand, the available evidence suggests differences in psychological attributes and non-cognitive skills are at best modest factors contributing to the gender pay gap.

Differences in human capital

The adjusted pay gap.

Differences in earnings between men and women capture differences across many possible dimensions, including education, experience, and occupation.

For example, if we consider that more educated people tend to have higher earnings, it is natural to expect that the narrowing of the pay gap across the world can be partly explained by the fact that women have been catching up with men in terms of educational attainment, in particular years of schooling.

Indeed, since differences in education partly contribute to explaining differences in wages, it is common to distinguish between 'unadjusted' and 'adjusted' pay differences.

When the gender pay gap is calculated by comparing all male and female workers, irrespective of differences in worker characteristics, the result is the raw or unadjusted pay gap. In contrast to this, when the gap is calculated after accounting for underlying differences in education, experience, and other factors that matter for the pay gap, then the result is the adjusted pay gap.

The idea of the adjusted pay gap is to make comparisons within groups of workers with roughly similar jobs, tenure, and education. This allows us to tease out the extent to which different factors contribute to observed inequalities.

The chart here, from Blau and Kahn (2017) shows the evolution of the adjusted and unadjusted gender pay gap in the US. 4

More precisely, the chart shows the evolution of female-to-male wage ratios in three different scenarios: (i) Unadjusted; (ii) Adjusted, controlling for gender differences in human capital, i.e. education and experience; and (iii) Adjusted, controlling for a full range of covariates, including education, experience, job industry, and occupation, among others. The difference between 100% and the full specification (the green bars) is the “unexplained” residual. 5

Several points stand out here.

• First, the unadjusted gender pay gap in the US shrunk over this period. This is evident from the fact that the blue bars are closer to 100% in 2010 than in 1980.
• Second, if we focus on groups of workers with roughly similar jobs, tenure, and education, we also see a narrowing. The adjusted gender pay gap has shrunk.
• Third, we can see that education and experience used to help explain a very large part of the pay gap in 1980, but this changed substantially in the decades that followed. This third point follows from the fact that the difference between the blue and red bars was much larger in 1980 than in 2010.
• And fourth, the green bars grew substantially in the 1980s, but stayed fairly constant thereafter. In other words: Most of the convergence in earnings occurred during the 1980s, a decade in which the "unexplained" gap shrunk substantially.

Education and experience have become much less important in explaining gender differences in wages in the US

The next chart shows a breakdown of the adjusted gender pay gaps in the US, factor by factor, in 1980 and 2010.

When comparing the contributing factors in 1980 and 2010, we see that education and work experience have become much less important in explaining gender differences in wages over time, while occupation and industry have become more important. 6

In this chart we can also see that the 'unexplained' residual has gone down. This means the observable characteristics of workers and their jobs explain wage differences better today than a couple of decades ago. At first sight, this seems like good news – it suggests that today there is less discrimination, in the sense that differences in earnings are today much more readily explained by differences in 'productivity' factors. But is this really the case?

The unexplained residual may include aspects of unmeasured productivity (i.e. unobservable worker characteristics that could not be accounted for in the study), while the "explained" factors may themselves be vehicles of discrimination.

For example, suppose that women are indeed discriminated against, and they find it hard to get hired for certain jobs simply because of their sex. This would mean that in the adjusted specification, we would see that occupation and industry are important contributing factors – but that is precisely because discrimination is embedded in occupational differences!

Hence, while the unexplained residual gives us a first-order approximation of what is going on, we need much more detailed data and analysis in order to say something definitive about the role of discrimination in observed pay differences.

Gender pay differences around the world are better explained by occupation than by education

The set of three maps here, taken from the World Development Report (2012) , shows that today gender pay differences are much better explained by occupation than by education. This is consistent with the point already made above using data for the US: as education expanded radically over the last few decades, human capital has become much less important in explaining gender differences in wages.

Justin Sandefur at the Center for Global Development shows that education also fails to explain wage gaps if we include workers with zero income (i.e. if we decompose the wage gap after including people who are not employed).

Looking beyond worker characteristics

Job flexibility.

All over the world women tend to do more unpaid care work at home than men – and women tend to be overrepresented in low-paying jobs where they have the flexibility required to attend to these additional responsibilities.

The most important evidence regarding this link between the gender pay gap and job flexibility is presented and discussed by Claudia Goldin in the article ' A Grand Gender Convergence: Its Last Chapter ', where she digs deep into the data from the US. 8 There are some key lessons that apply both to rich and non-rich countries.

Goldin shows that when one looks at the data on occupational choice in some detail, it becomes clear that women disproportionately seek jobs, including full-time jobs, that tend to be compatible with childrearing and other family responsibilities. In other words, women, more than men, are expected to have temporal flexibility in their jobs. Things like shifting hours of work and rearranging shifts to accommodate emergencies at home. And these are jobs with lower earnings per hour, even when the total number of hours worked is the same.

The importance of job flexibility in this context is very clearly illustrated by the fact that, over the last couple of decades, women in the US increased their participation and remuneration in only some fields. In a recent paper, Goldin and Katz (2016) show that pharmacy became a highly remunerated female-majority profession with a small gender earnings gap in the US, at the same time as pharmacies went through substantial technological changes that made flexible jobs in the field more productive (e.g. computer systems that increased the substitutability among pharmacists). 9

The chart here shows how quickly female wages increased in pharmacy, relative to other professions, over the last few decades in the US.

The motherhood penalty

Closely related to job flexibility and occupational choice is the issue of work interruptions due to motherhood. On this front, there is again a great deal of evidence in support of the so-called 'motherhood penalty'.

Lundborg, Plug, and Rasmussen (2017) provide evidence from Denmark – more specifically, Danish women who sought medical help in achieving pregnancy. 10

By tracking women’s fertility and employment status through detailed periodic surveys, these researchers were able to establish that women who had a successful in vitro fertilization treatment, ended up having lower earnings down the line than similar women who, by chance, were unsuccessfully treated.

Lundborg, Plug, and Rasmussen summarise their findings as follows: "Our main finding is that women who are successfully treated by [in vitro fertilization] earn persistently less because of having children. We explain the decline in annual earnings by women working less when children are young and getting paid less when children are older. We explain the decline in hourly earnings, which is often referred to as the motherhood penalty, by women moving to lower-paid jobs that are closer to home."

The fact that the motherhood penalty is indeed about ‘motherhood’ and not ‘parenthood’, is supported by further evidence.

A recent study , also from Denmark, tracked men and women over the period 1980-2013 and found that after the first child, women’s earnings sharply dropped and never fully recovered. But this was not the case for men with children, nor the case for women without children.

These patterns are shown in the chart here. The first panel shows the trend in earnings for Danish women with and without children. The second panel shows the same comparison for Danish men.

Note that these two examples are from Denmark – a country that ranks high on gender equality measures and where there are legal guarantees requiring that a woman can return to the same job after taking time to give birth.

This shows that, although family-friendly policies contribute to improving female labor force participation and reducing the gender pay gap , they are only part of the solution. Even when there is generous paid leave and subsidized childcare, as long as mothers disproportionately take additional work at home after having children, inequities in pay are likely to remain.

Ability, personality, and social norms

The discussion so far has emphasized the importance of job characteristics and occupational choice in explaining the gender pay gap. This leads to obvious questions: What determines the systematic gender differences in occupational choice? What makes women seek job flexibility and take a disproportionate amount of unpaid care work?

One argument usually put forward is that, to the extent that biological differences in preferences and abilities underpin gender roles, they are the main factors explaining the gender pay gap. In their review of the evidence, Francine Blau and Lawrence Kahn (2017) show that there is limited empirical support for this argument. 11

To be clear, yes, there is evidence supporting the fact that men and women differ in some key attributes that may affect labor market outcomes. For example, standardized tests show that there are statistical gender gaps in maths scores in some countries ; and experiments show that women avoid more salary negotiations , and they often show particular predisposition to accept and receive requests for tasks with low promotion potential . However, these observed differences are far from being biologically fixed – 'gendering' begins early in life and the evidence shows that preferences and skills are highly malleable. You can influence tastes, and you can certainly teach people to tolerate risk, to do maths, or to negotiate salaries.

What's more, independently of where they come from, Blau and Kahn show that these empirically observed differences can typically only account for a modest portion of the gender pay gap.

In contrast, the evidence does suggest that social norms and culture, which in turn affect preferences, behavior, and incentives to foster specific skills, are key factors in understanding gender differences in labor force participation and wages. You can read more about this farther below.

Discrimination and bias

Independently of the exact origin of the unequal distribution of gender roles, it is clear that our recent and even current practices show that these roles persist with the help of institutional enforcement. Goldin (1988), for instance, examines past prohibitions against the training and employment of married women in the US. She touches on some well-known restrictions, such as those against the training and employment of women as doctors and lawyers, before focusing on the lesser known but even more impactful 'marriage bars' that arose in the late 1800s and early 1900s. These work prohibitions are important because they applied to teaching and clerical jobs – occupations that would become the most commonly held among married women after 1950. Around the time the US entered World War II, it is estimated that 87% of all school boards would not hire a married woman and 70% would not retain an unmarried woman who married. 12

The map here highlights that to this day, explicit barriers limit the extent to which women are allowed to do the same jobs as men in some countries. 13

However, even after explicit barriers are lifted and legal protections put in place, discrimination and bias can persist in less overt ways. Goldin and Rouse (2000), for example, look at the adoption of "blind" auditions by orchestras and show that by using a screen to conceal the identity of a candidate, impartial hiring practices increased the number of women in orchestras by 25% between 1970 and 1996. 14

Many other studies have found similar evidence of bias in different labor market contexts. Biases also operate in other spheres of life with strong knock-on effects on labor market outcomes. For example, at the end of World War II only 18% of people in the US thought that a wife should work if her husband was able to support her . This obviously circles back to our earlier point about social norms. 15

Strategies for reducing the gender pay gap

In many countries wage inequality between men and women can be reduced by improving the education of women. However, in many countries, gender gaps in education have been closed and we still have large gender inequalities in the workforce. What else can be done?

An obvious alternative is fighting discrimination. But the evidence presented above shows that this is not enough. Public policy and management changes on the firm level matter too: Family-friendly labor-market policies may help. For example, maternity leave coverage can contribute by raising women’s retention over the period of childbirth, which in turn raises women’s wages through the maintenance of work experience and job tenure. 16

Similarly, early education and childcare can increase the labor force participation of women — and reduce gender pay gaps — by alleviating the unpaid care work undertaken by mothers. 17

Additionally, the experience of women's historical advance in specific professions (e.g. pharmacists in the US), suggests that the gender pay gap could also be considerably reduced if firms did not have the incentive to disproportionately reward workers who work long hours, and fixed, non-flexible schedules. 18

Changing these incentives is of course difficult because it requires reorganizing the workplace. But it is likely to have a large impact on gender inequality, particularly in countries where other measures are already in place. 19

Implementing these strategies can have a positive self-reinforcing effect. For example, family-friendly labor-market policies that lead to higher labor-force attachment and salaries for women will raise the returns on women's investment in education – so women in future generations will be more likely to invest in education, which will also help narrow gender gaps in labor market outcomes down the line. 20

Nevertheless, powerful as these strategies may be, they are only part of the solution. Social norms and culture remain at the heart of family choices and the gender distribution of labor. Achieving equality in opportunities requires ensuring that we change the norms and stereotypes that limit the set of choices available both to men and women. It is difficult, but as the next section shows, social norms can be changed, too.

How well do biological differences explain the gender pay gap?

Across the world, women tend to take on more family responsibilities than men. As a result, women tend to be overrepresented in low-paying jobs where they are more likely to have the flexibility required to attend to these additional responsibilities.

These two facts – documented above – are often used to claim that, since men and women tend to be endowed with different tastes and talents, it follows that most of the observed gender differences in wages stem from biological sex differences. But what’s the broader evidence for these claims?

In a nutshell, here's what the research and data shows:

• There is evidence supporting the fact that statistically speaking, men and women tend to differ in some key aspects, including psychological attributes that may affect labor-market outcomes.
• There is no consensus on the exact weight that nurture and nature have in determining these differences, but whatever the exact weight, the evidence does show that these attributes are strongly malleable.
• Regardless of the origin, these differences can only explain a modest part of the gender pay gap.

Some context regarding the gender distribution of labor

Before we get into the discussion of whether biological attributes explain wage differences via gender roles, let's get some perspective on the gender distribution of work.

The following chart shows, by country, the female-to-male ratio of time devoted to unpaid care work, including tasks like taking care of children at home, housework, or doing community work. As can be seen, all over the world there is a radical unbalance in the gender distribution of labor – everywhere women take a disproportionate amount of unpaid work.

This is of course closely related to the fact that in most countries there are gender gaps in labor force participation and wages .

“Boys are better at maths”

Differences in biological attributes that determine our ability to develop 'hard skills', such as maths, are often argued to be at the heart of the gender pay gap. 21 Do large gender differences in maths skills really exist? If so, is this because of differences in the attributes we are born with?

Let's look at the data.

Are boys better in the mathematics section of the PISA standardized test ? One could argue that looking at top scores is more relevant here since top scores are more likely to determine gaps in future professional trajectories – for example, gaps in access to 'STEM degrees' at the university level.

The chart shows the share of male and female test-takers scoring at the highest level on the PISA test (that's level 6). As we can see, most countries lie above the diagonal line marking gender parity; so yes, achieving high scores in maths tends to be more common among boys than girls. However, there is huge cross-country variation – the differences between countries are much larger than the differences between the sexes. And in many countries, the gap is effectively inexistent. 22

Similarly, researchers have found that within countries there is also large geographic variation in gender gaps in test scores. So clearly these gaps in mathematical ability do not seem to be fully determined by biological endowments. 23

Indeed, research looking at the PISA cross-country results suggests that improved social conditions for women are related to improved math performance by girls. 24

Not only do statistical gaps in test scores vary substantially across societies – they also vary substantially across time. This suggests that social factors play a large role in explaining differences between the sexes.

In the US, for example, the gender gap in mathematics has narrowed in recent decades. 25 And this narrowing took place as high school curricula of boys and girls became more similar. The following chart shows this: In the US boys in 1957 took far more math and science courses than did girls; but by 1992 there was virtual parity in almost all science and math courses.

More importantly for the question at hand, gender gaps in 'hard skills' are not large enough to explain the gender gaps in earnings. In their review of the evidence, Blau and Kahn (2017) concludes that gaps in test scores in the US are too small to explain much of the gender pay at any point in time. 26

So, taken together, the evidence suggests that statistical gaps in maths test scores are both relatively small and heavily influenced by social and environmental factors.

“It’s about personality”

Biological differences in tastes (e.g. preferences for 'people' over 'things'), psychological attributes (e.g. 'risk aversion'), and soft skills (e.g. the ability to get along with others) are also often argued to be at the heart of the gender pay gap.

There are hundreds of studies trying to establish whether there are gender differences in preferences, personality traits, and 'soft skills'. The quality and general relevance (i.e. the internal and external validity) of these studies is the subject of much discussion, as illustrated in the recent debate that ensued from the Google Memo affair .

A recent article from the 'Heterodox Academy ', which was produced specifically in the context of the Google Memo, provides a fantastic overview of the evidence on this topic and the key points of contention among scholars.

For the purpose of this blog post, let's focus on the review of the evidence presented in Blau and Kahn (2017) – their review is particularly helpful because they focus on gender differences in the context of labor markets.

Blau and Kahn point out that, yes, researchers have found statistical differences between men and women that are important in the context of labor-market outcomes. For example, studies have found statistical gender differences in 'people skills' (i.e. ability to listen, communicate, and relate to others). Similarly, experimental studies have found that women more often avoid salary negotiations , and they often show a particular predisposition to accept and receive requests for tasks with low promotability. But are the origins of these differences mainly biological or are they social? And are they strong enough to explain pay gaps?

The available evidence here suggests these factors can only explain a relatively small fraction of the observed differences in wages. 27 And they are anyway far from being purely biological – preferences and skills are highly malleable and 'gendering' begins early in life. 28

Here is a concrete example: Leibbrandt and List (2015) did an experiment in which they assessed how men and women reacted to job advertisements. 29 They found that although men were more likely to negotiate than women when there was no explicit statement that wages were negotiable, the gender difference disappeared and even reversed when it was explicitly stated that wages were negotiable. This suggests that it is not as much about 'talent', as it is about norms and rules.

“A man should earn more than his wife”

The experiment in which researchers found that gender differences in negotiation attitudes disappeared when it was explicitly stated that wages were negotiable, emphasizes the important role that social norms and culture play in labor-market outcomes.

These concepts may seem abstract: What do social norms and culture actually look like in the context of the gender pay gap?

The reproduction of stereotypes through everyday positive enforcement can be seen in a range of aspects: A study analyzing 124 prime-time television programs in the US found that female characters continue to inhabit interpersonal roles with romance, family, and friends, while male characters enact work-related roles. 30 In the realm of children’s books, a study of 5,618 books found that compared to females, males are represented nearly twice as often in titles and 1.6 times as often as central characters. 31 Qualitative research shows that even in the home, parents are often enforcers of gender norms – especially when it comes to fathers endorsing masculinity in male children. 32

Of particular relevance in the context of labor markets, social norms also often take the form of specific behavioral prescriptions such as "a man should earn more than his wife".

The following chart depicts the distribution of the share of the household income earned by the wife, across married couples in the US.

Consistent with the idea that "a man should earn more than his wife", the data shows a sharp drop at 0.5, the point where the wife starts to earn more than the husband.

Distribution of income share earned by the wife across married couples in the US – Bertrand, Kamenica, and Pan (2015) 33

This is the result of two factors. First, it is about the matching of men and women before they marry – 'matches' in which the woman has higher earning potential are less common. Second, it is a result of choices after marriage – the researchers show that married women with higher earning potential than their husbands often stay out of the labor force, or take 'below-potential' jobs. 34

The authors of the study from which this chart is taken explored the data in more detail and found that in couples where the wife earns more than the husband, the wife spends more time on household chores, so the gender gap in unpaid care work is even larger; and these couples are also less satisfied with their marriage and are more likely to divorce than couples where the wife earns less than the husband.

The empirical exploration in this study highlights the remarkable power that gender norms and identity have on labor-market outcomes.

Why do gender norms and identity matter?

Does it actually matter if social norms and culture are important determinants of gender roles and labor-market outcomes? Are social norms in our contemporary societies really less fixed than biological traits?

The available research suggests that the answers to these questions are yes and yes. There is evidence that social norms can be actively and rapidly changed.

Here is a concrete example: Jensen and Oster (2009) find that the introduction of cable television in India led to a significant decrease in the reported acceptability of domestic violence towards women and son preference, as well as increases in women’s autonomy and decreases in fertility. 35

Of course, TV is a small aspect of all the big things that matter for social norms. But this study is important for the discussion because it is hard to study how social norms can be changed. TV introduction is a rare opportunity to see how a group that is exposed to a driver of social change actually changes.

As Jensen and Oster point out, most popular cable TV shows in India feature urban settings where lifestyles differ radically from those in rural areas. For example, many female characters on popular soap operas have more education, marry later, and have smaller families than most women in rural areas. And, similarly, many female characters in these tv shows are featured working outside the home as professionals, running businesses, or are shown in other positions of authority.

The bar chart below shows how cable access changed attitudes toward the self-reported preference for their child to be a son. As the authors note, "reported desire for the next child to be a son is relatively unchanged in areas with no change in cable status, but it decreases sharply between 2001 and 2002 for villages that get cable in 2002, and between 2002 and 2003 (but notably not between 2001 and 2002) for those that get cable in 2003. For both measures of attitudes, the changes are large and striking, and correspond closely to the timing of introduction of cable."

To conclude: The evidence suggests that biological differences are not a key driver of gender inequality in labor-market outcomes; while social norms and culture – which in turn affect preferences, behavior, and incentives to foster specific skills – are very important.

This matters for policy because social norms are not fixed – they can be influenced in a number of ways, including through intergenerational learning processes, exposure to alternative norms, and activism such as that which propelled the women's movement. 36

How are women represented across jobs?

Representation of women at the top of the income distribution.

Despite having fallen in recent decades, there remains a substantial pay gap between the average wages of men and women .

But what does gender inequality look like if we focus on the very top of the income distribution? Do we find any evidence of the so-called 'glass ceiling' preventing women from reaching the top? How did this change over time?

Answers to these questions are found in the work of Atkinson, Casarico and Voitchovsky (2018). Using tax records, they investigated the incomes of women and men separately across nine high-income countries. As such, they were restricted to those countries in which taxes are collected on an individual basis, rather than as couples. 37

In addition to wages they also take into account income from investments and self-employment.

Whilst investment income tends to make up a larger share of the total income of rich individuals in general, the authors found this to be particularly marked in the case of women in top-income groups.

The two charts present the key figures from the study.

One chart shows the proportion of women out of all individuals falling into the top 10%, 1%, and 0.1% of the income distribution. The open circle represents the share of women in the top income brackets back in 2000; the closed circle shows the latest data, which is from 2013.

The other chart shows the data over time for individual countries. You can explore data for other countries using the 'Change country' button on the chart.

The two charts allow us to answer the initial questions:

• Women are greatly under-represented in top income groups – they make up much less than 50% across each of the nine countries. Within the top 1% women account for around 20% and there is surprisingly little variation across countries.
• The proportion of women is lower the higher you look up the income distribution. In the top 10% up to every third income-earner is a woman; in the top 0.1% only every fifth or tenth person is a woman.
• The trend is the same in all countries of this study: Women are now better represented in all top-income groups than they were in 2000.
• But improvements have generally been more limited at the very top. With the exception of Australia, we see a much smaller increase in the share of women amongst the top 0.1% than amongst the top 10%.

Overall, despite recent inroads, we continue to see remarkably few women making it to the top of the income distribution today.

Representation of women in management positions

The chart here plots the proportion of women in senior and middle management positions around the world. It shows that women all over the world are underrepresented in high-profile jobs, which tend to be better paid.

The next chart provides an alternative perspective on the same issue. Here we show the share of firms that have a woman as manager. We highlight world regions by default, but you can remove them and add specific countries.

As we can see, all over the world firms tend to be managed by men. And, globally, only about 18% of firms have a female manager.

Firms with female managers tend to be different to firms with male managers. For example, firms with female managers tend to also be firms with more female workers .

Representation of women in low-paying jobs

Above we show that women all over the world are underrepresented in high-profile jobs, which tend to be better paid. As it turns out, in many countries women are at the same time overrepresented in low-paying jobs.

This is shown in the chart here, where 'low-pay' refers to workers earning less than two-thirds of the median (i.e. the middle) of the earnings distribution.

A share above 50% implies that women are 'overrepresented', in the sense that among those with low wages, there are more women than men.

The fact that women in rich countries are overrepresented in the bottom of the income distribution goes together with the fact that working women in these countries are overrepresented in low-paying occupations. The chart shows this for the US.

How much control do women have over household resources?

Women often have no control over their personal earned income.

The next chart plots cross-country estimates of the share of women who are not involved in decisions about their own income. The line shows national averages, while the dots show averages for rich and poor households (i.e. averages for women in households within the top and bottom quintiles of the corresponding national income distribution).

As we can see, in many countries, particularly in Sub-Saharan Africa and Asia, a large fraction of women are not involved in household decisions about spending their personal earned income. And this pattern is stronger among low-income households within low-income countries.

Percentage of women not involved in decisions about their own income – World Development Report (2012) 39

In many countries, women have limited influence over important household decisions

Above we focus on whether women get to choose how their own personal income is spent. Now we look at women's influence over total household income.

In this chart, we plot the share of currently married women who report having a say in major household purchase decisions, against national GDP per capita.

We see that in many countries, notably in Sub-Saharan Africa and Asia, an important number of women have limited influence over major spending decisions.

The chart above shows that women’s control over household spending tends to be greater in richer countries. In the next chart, we show that this correlation also holds within countries: Women’s control is greater in wealthier households. Household wealth is shown by the quintile in the wealth distribution on the x-axis – the poorest households are in the lowest quintiles (Q1) on the left.

There are many factors at play here, and it's important to bear in mind that this correlation partly captures the fact that richer households enjoy greater discretionary income beyond levels required to cover basic expenditure, while at the same time, in richer households women often have greater agency via access to broader networks as well as higher personal assets and incomes.

Land ownership is more often in the hands of men

Economic inequalities between men and women manifest themselves not only in terms of wages earned but also in terms of assets owned. For example, as the chart shows, in nearly all low and middle-income countries with data, men are more likely to own land than women.

Women's lack of control over important household assets, such as land, can be a critical problem in case of divorce or the husband’s death.

Closely related to the issue of land ownership is the fact that in several countries women do not have the same rights to property as men. These countries are highlighted in the map. 40

Gender-equal inheritance systems have been adopted in most, but not all countries

Inheritance is one of the main mechanisms for the accumulation of assets. In the map, we provide an overview of the countries that do and do not have gender-equal inheritance systems.

If you move the slider to 1920, you will see that while gender-equal inheritance systems were very rare in the early 20th century, today they are much more common. And still, despite the progress achieved, in many countries, notably in North Africa and the Middle East, women and girls still have fewer inheritance rights than men and boys.

Gender differences in access to productive inputs are often large

Above we show that there are large gender gaps in land ownership across low-income countries. Here we show that there are also large gaps in terms of access to borrowed capital.

The chart shows the percentage of men and women who report borrowing any money in the past 12 months to start, operate, or expand a farm or business.

As we can see, almost everywhere, including in many rich countries, women are less likely to obtain borrowed capital for productive purposes.

This can have large knock-on effects: in agriculture and entrepreneurship, gender differences in access to productive inputs, including land and credit, can lead to gaps in earnings via lower productivity.

Indeed, studies have found that, when statistical gender differences in agricultural productivity exist, they often disappear when access to and use of productive inputs are taken into account. 41

Interactive Charts on Economic Inequality by Gender

Acknowledgements.

We thank Sandra Tzvetkova and Diana Beltekian for their great research assistance.

There are some exceptions to this definition. In particular, sometimes self-employed workers, or part-time workers are excluded.

This measure can also be negative. This means that, on an hourly basis, men earn on average less than women. It is the case for some countries, such as Malaysia.

Olivetti, C., & Petrongolo, B. (2008). Unequal pay or unequal employment? A cross-country analysis of gender gaps. Journal of Labor Economics, 26(4), 621-654.

Blau, Francine D., and Lawrence M. Kahn. 2017. " The Gender Wage Gap: Extent, Trends, and Explanations. " Journal of Economic Literature, 55(3): 789-865.

For each specification, Blau and Kahn (2017) perform regression analyses on data from the PSID (the Michigan Panel Study of Income Dynamics), which includes information on labor-market experience and considers men and women ages 25-64 who were full-time, non-farm, wage and salary workers.

In 2010, unionization and education show negative values; this reflects the fact that women have surpassed men in educational attainment, and unionization in the US has been in general decline with a greater effect on men.

The full source is: World Development Report (2012) Gender Equality and Development , World Bank.

Goldin, C. (2014). A grand gender convergence: Its last chapter. The American Economic Review, 104(4), 1091-1119.

Goldin, C., & Katz, L. F. (2016). A most egalitarian profession: pharmacy and the evolution of a family-friendly occupation. Journal of Labor Economics, 34(3), 705-746.

Lundborg, P., Plug, E., & Rasmussen, A. W. (2017). Can Women Have Children and a Career? IV Evidence from IVF Treatments. American Economic Review, 107(6), 1611-1637.

Blau, Francine D., and Lawrence M. Kahn. 2017. " The Gender Wage Gap: Extent, Trends, and Explanations. " Journal of Economic Literature, 55(3): 789-865

Goldin, C. (1988). Marriage bars: Discrimination against married women workers, 1920's to 1950's .

The data in this map, which comes from the World Bank's World Development Indicators, provides a measure of whether there are any specific jobs that women are not allowed to perform. So, for example, a country might be coded as "No" if women are only allowed to work in certain jobs within the mining industry, such as health care professionals within mines, but not as miners.

Goldin, C., & Rouse, C. (2000). Orchestrating impartiality: The impact of" blind" auditions on female musicians. American Economic Review , 90(4), 715-741.

Blau and Kahn (2017) provide a whole list of experimental studies that have found labor-market discrimination. Another early example is from Neumark et al. (1996), who look at discrimination in restaurants. In this case, male and female pseudo-job-seekers were given similar CVs to apply for jobs waiting on tables at the same set of restaurants in Philadelphia. The results showed discrimination against women in high-priced restaurants.

The full reference of this study is Neumark, D., Bank, R. J., & Van Nort, K. D. (1996). Sex discrimination in restaurant hiring: An audit study. The Quarterly Journal of Economics, 111(3), 915-941.

Waldfogel, J. (1998). Understanding the "family gap" in pay for women with children. The Journal of Economic Perspectives, 12(1), 137-156.

Olivetti, C., & Petrongolo, B. (2017). The economic consequences of family policies: lessons from a century of legislation in high-income countries. The Journal of Economic Perspectives, 31(1), 205-230.

As we show above, in several nations, such as Sweden and Denmark, a “motherhood penalty” in earnings exists, even though these nations have generous family policies, including paid family leave and subsidized child care.

For a discussion of this mechanism, see page 814, Blau, Francine D., and Lawrence M. Kahn. 2017. The Gender Wage Gap: Extent, Trends, and Explanations. Journal of Economic Literature, 55(3): 789-865.

Hard skills are abilities that can be defined and measured, such as writing, reading, or doing maths. By contrast, soft skills are less tangible and harder to measure and quantify.

Also importantly: If we focus on gender differences for average , rather than top students, we find that there is not even a clear tendency in favor of boys. ( This interactive chart compares PISA average math scores for boys and girls ).

For more on this see Pope, D. G., & Sydnor, J. R. (2010). Geographic variation in the gender differences in test scores. Journal of Economic Perspectives, 24(2), 95-108.

Guiso, L., Monte, F., Sapienza, P., & Zingales, L. (2008). Culture, gender, and math. SCIENCE-NEW YORK THEN WASHINGTON-, 320(5880), 1164.

A number of papers have documented the narrowing of gender gaps in test scores. See, for example, Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., & Williams, C. C. (2008). Gender similarities characterize math performance . Science, 321(5888), 494-495.

Blau, Francine D., and Lawrence M. Kahn. 2017. The Gender Wage Gap: Extent, Trends, and Explanations. Journal of Economic Literature, 55(3): 789-865.

Blau and Kahn write: "While findings such as those in table 7 ['Selected Studies Assessing the Role of Psychological Traits in Accounting for the Gender Pay Gap'] are informative in elucidating some of the possible omitted factors that lie behind gender differences in wages as well as the unexplained gap in traditional wage regressions, in general, the results suggest that these factors do not account for a large portion of either the raw or unexplained gender gap."

For a discussion of 'gendering' see West, C., & Zimmerman, D. H. (1987). Doing gender. Gender & Society, 1(2), 125-151.

Leibbrandt, A., & List, J. A. (2014). Do women avoid salary negotiations? Evidence from a large-scale natural field experiment. Management Science, 61(9), 2016-2024.

Lauzen, M. M., Dozier, D. M., & Horan, N. (2008). Constructing gender stereotypes through social roles in prime-time television. Journal of Broadcasting & Electronic Media, 52(2), 200-214.

McCabe, J., Fairchild, E., Grauerholz, L., Pescosolido, B. A., & Tope, D. (2011). Gender in twentieth-century children’s books: Patterns of disparity in titles and central characters. Gender & Society, 25(2), 197-226.

Kane, E. W. (2006). “No way my boys are going to be like that!” Parents’ responses to children’s gender nonconformity. Gender & Society, 20(2), 149-176.

Bertrand, M., Kamenica, E., & Pan, J. (2015). Gender identity and relative income within households. The Quarterly Journal of Economics, 130(2), 571-614.

More precisely, the authors find that in couples where the wife’s potential income is likely to exceed her husband’s (based on the income that would be predicted for her observed characteristics), the wife is less likely to be in the labor force, and if she does work, her income is lower than predicted.

Jensen, R., & Oster, E. (2009). The power of TV: Cable television and women's status in India . In  The Quarterly Journal of Economics , 124(3), 1057-1094.

Regarding intergenerational transmission of gender roles, see Fernández, R. (2013). Cultural change as learning: The evolution of female labor force participation over a century. The American Economic Review, 103(1), 472-500.

For a discussion regarding social activism and its link to the determinants of female labor supply, see for example this study by Heer and Grossbard-Shechtman (1981).

Atkinson, A.B., Casarico, A. & Voitchovsky, S. Top incomes and the gender divide . J Econ Inequal (2018) 16: 225.

The authors produced results for 8 countries, and included earlier results for Sweden from Boschini, A., Gunnarsson, K., Roine, J.: Women in Top Incomes: Evidence from Sweden 1974-2013, IZA Discussion paper 10979, August (2017).

World Bank. (2011). World development report 2012: gender equality and development . World Bank Publications.

The map from The World Development Report (2012) provides a more fine-grained overview of different property regimes operating in different countries.

For more discussion of the evidence see page 20 in World Bank (2011) World Development Report 2012: Gender Equality and Development. World Bank Publications.

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• 09 May 2024

How ignorance and gender inequality thwart treatment of a widespread illness

• Claire Ainsworth 0

Claire Ainsworth is a freelance science journalist in Hampshire, UK.

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On a visit to a woman at home in rural Zambia, community-health worker Janet Chisaila unpacks a bag that contains swabs, sample pots and a 3D-printed model of a vagina and cervix. Using the model, Chisaila explains how to use the swabs to take genital samples. The woman then goes to a private area to do her sampling. Later, she visits the local health clinic, where Chisaila’s colleague Alice Mwale, a nurse, takes digital photographs of the woman’s cervix, which are then uploaded to a secure platform. Thousands of miles away, at the London School of Hygiene & Tropical Medicine, clinician and principal investigator Amaya Bustinduy logs in to the platform to review the images and offer advice.

Part of Nature Outlook: Neglected tropical diseases

The woman is one of around 2,500 taking part in a study 1 called Zipime Weka Schista! (Do self-testing, sister!), which aims to transform the diagnosis of a little-known neglected tropical disease (NTD) called female genital schistosomiasis (FGS). By combining FGS screening with testing for HIV, human papillomavirus (HPV) and a sexually transmitted disease called trichomoniasis in a single visit, the tests are striking a blow for gender equality and women’s sexual- and reproductive-health rights. “This approach has empowered the women to know about these diseases,” says Chisaila. “They have been given the confidence to talk about some of these health issues and have access to treatment and care.”

FGS is a debilitating gynaecological condition caused by chronic infection with a parasitic disease known as schistosomiasis. Painful and stigmatizing, the disease is associated with reduced fertility and miscarriage. Infection increases the risk of contracting HIV, and probably HPV and cervical cancer as well. Although it was first recorded 2 125 years ago, few people — even health-care workers in regions where the condition is thought to be most common — are aware that it exists. “FGS is neglected, under-researched and overlooked in endemic countries,” says Kwame Shanaube, clinical epidemiologist and site coordinator of the Zipime Weka Schista! study at Zambart, a Zambian non-governmental public-health research organization in Lusaka that specializes in public health and grew out of a collaboration between the University of Zambia’s School of Medicine and the London School of Hygiene & Tropical Medicine.

Women and girls are vulnerable to FGS both because of their sex and because of socially determined roles and expectations that increase their exposure to infection and make it difficult for them to access treatment or talk about their symptoms. The social roles of women expose them more often to infection, and make it harder to access prevention and treatment, or even to talk about their symptoms than do those of men. “It’s very hard for women to talk about painful sex and sub-fertility in contexts where it’s hard to access a health-care provider,” says Sally Theobald at the Liverpool School of Tropical Medicine, UK, who studies gender inequity and health systems. “So it is this chronic pain and rights issues that have been going on for decades and decades.”

FGS is a disease of compounded neglect: ignored because it is an illness found mainly in low-income countries; overlooked because of a lack of awareness; stigmatized because it pertains to sexual health; and further neglected because it affects women, especially low-income and marginalized women, whose health is chronically underfunded and under-researched. Tackling it is therefore not merely a biomedical problem, but also one that involves addressing gender inequality and the sexual and reproductive health rights of women and girls.

An insidious disease

Schistosomiasis, also called bilharzia, is caused by parasitic worms known as schistosomes. The species that causes FGS, Schistosoma haematobium , infests freshwater lakes and rivers. The larvae burrow through a person’s skin, making their way to a collection of veins around the bladder and pelvic organs. There, the larvae mature into adults, each the size of a grain of rice, and mate. Each female worm lays hundreds of eggs. These work their way through the bladder wall with the aid of sharp spines and destructive enzymes. Once in the bladder, the eggs are released through urination into the environment to start the cycle anew.

In some societies, girls are expected to fetch the family's water. Credit: Simon Townsley/Panos Pictures

Left untreated, the infection becomes chronic. “These worms can live in your bloodstream for 30 or 40 years,” says Evan Secor, a parasitologist at the US Centers for Disease Control and Prevention in Atlanta, Georgia. Between 30% and 75% of women infected with S. haematobium go on to develop FGS, which occurs when schistosome eggs end up trapped in the tissues of the reproductive system, including the cervix, vagina and fallopian tubes. These trapped eggs cause pain and become surrounded by immune cells, forming inflamed nodules called granulomas, which in turn can lead to scarring. Men can also get genital schistosomiasis, particularly those whose occupations put them at increased risk, such as freshwater fishermen.

Only about 15,000 women and girls in endemic areas have been included in study surveys for FGS, so there are no precise figures for the prevalence of the condition, says Bustinduy. Estimates suggest that between 30 million and 56 million women globally have FGS, most of them in sub-Saharan Africa.

Part of the problem lies in the difficulty of diagnosing the disease. Conventional approaches involve inspecting the cervix with an instrument known as a colposcope, or taking a biopsy and sending it to a lab to look for schistosome eggs under a microscope. But these tools are rarely available in endemic areas — colposcopes are expensive and require specialized gynaecological training to use.

Looking for schistosome eggs in urine samples is cheap, but misses most FGS cases because the correlation between eggs in urine and FGS is only about 20–30% . Molecular testing to detect schistosome DNA in samples such as urine is much more reliable but requires specialist facilities and expensive reagents. Facilities such as these are also usually found only in hospitals, which can be hard for people with low incomes to travel to. And gynaecological examination of girls and young women before they are sexually active is unacceptable in some cultures.

Diagnostic delays mean that, even after standard treatment with a drug called praziquantel that kills the adult worms, women can have permanent tissue damage. Delphine Pedeboy-Knoetze, who grew up in France but who now lives and works in South Africa, had FGS that went undiagnosed for several months. She still experiences chronic pain six years later. “It’s extremely demoralizing, because nobody can establish what’s wrong,” she says. Consultations with multiple specialists in various countries have yielded no answers. This adds to the mental-health burden of FGS. “It’s the loneliness of it,” she says. “That’s the scariest feeling, because you think, ‘Oh wow, I really am on my own’.”

An array of neglect

The astonishing lack of awareness of FGS among health workers starts with education. FGS is not mentioned in many medical textbooks and rarely forms part of medical training. The classic symptom of urogenital schistosomiasis is blood in the urine, which can be confused with menstruation or ‘spotting’. This means that the disease is assumed to affect men only. “Health professionals do not have FGS in their radar of diagnosis,” says Motto Nganda, a clinician at the Liverpool School of Tropical Medicine who has studied how to integrate FGS management into primary health-care settings in Liberia.

Schistosoma larvae can burrow through a person's skin. Credit: LENNART NILSSON, TT/SCIENCE PHOTO LIBRARY

This means that genital symptoms can be wrongly attributed to sexually-transmitted infections, with the result that women are not only given ineffective treatment, but also stigmatized. Teenage girls report being scolded by clinic nurses who assume that the girls have had premarital sex, while older women (or their partners) have been accused of infidelity. Pedeboy-Knoetze, for example, was told that she had herpes and to be suspicious of her partner.

Larger political decisions have also shaped the neglect of FGS, says Laura Dean, who studies person-centred health-system responses to NTDs at the Liverpool School of Tropical Medicine. Mass drug-administration is the main effort to control NTDs that can be tackled in this way, including schistosomiasis, she says. The approach is designed to prevent and treat these diseases in endemic areas. This is an essential strategy and one that should be continued, Dean says. However, it isn’t a magic bullet that, in isolation, can prevent continuous cycles of reinfection — particularly for a disease such as schistosomiasis that is closely linked to the broader environment and access to clean water, sanitation and hygiene. People who cannot access these programmes, or for whom the drugs don’t work, can develop chronic morbidities. This risk is especially high for diseases such as schistosomiasis in which there is a high risk of reinfection 3 .

Compounding all of these factors is gender: the social expectations and roles that societies attribute to men and women (and people of other genders). Gender is increasingly being recognized as a key factor that affects an individual’s vulnerability to NTDs, and FGS is a classic example. “Gender norms in many contexts mean that much of the work done by women in households and communities involves a lot of interaction with water,” says Theobald. This includes doing the family’s laundry and fetching water from local rivers and ponds. “So there’s ongoing exposure to schistosomiasis in multiple ways.”

Gender also affects access to treatment and health care. For schistosomiasis, this involves the mass administration of praziquantel in vulnerable populations 4 . This is often delivered to children in schools, but girls are less likely to attend school than are boys, says Secor. Gender inequality also affects how women experience the disease once they have it. “It brings subfertility, it brings painful sex, it brings discharge, and it’s in a context where there’s so much pressure to conceive,” says Theobald. For example, in some parts of Liberia and Nigeria, a woman’s social status is linked to fertility and her ability to have children. As a result of poor sexual and reproductive health, including pregnancy complications or infertility, women with FGS can be ostracized, accused of witchcraft, and faced with the loss of their homes and partners 5 .

“The fact that there’s a parasite that’s easily treatable with a dose of praziquantel that costs very little and that can change the outcome of a woman’s life, and we’re not doing that, is absolutely shocking,” says Pedeboy-Knoetze. “Shame on the global-health community and shame on the medical community for this.”

Attack on all fronts

All of this means that programmes to tackle FGS need to build in social, political and cultural factors, as well as biomedical ones. They also need to work with the clinical resources that are available in endemic areas. In the past few years, a number of projects have piloted ways to do this. The Zipime Weka Schista! study, for example, uses culturally appropriate ways to raise awareness of FGS. Drama groups perform songs and dances in areas such as community marketplaces to draw in members of the public and communicate messages about FGS. Community workers then go door to door to offer more information and to recruit study participants.

A health worker at a medical centre in Zimbabwe tests for schistosome parasites. Credit: Xinhua/Shutterstock

Reactions from the communities have been positive, says Rhoda Ndubani, a social scientist and study manager of Zipime Weka Schista! at Zambart. The project is reducing stigma around these diseases and giving women the confidence to talk about them and seek treatment, she adds. It’s also empowering the nurses and community midwives. “It’s really helping us because, before, I did not know that women can actually get schistosomiasis,” says Mwale. Training and handheld colposcopes are already allowing nurses to make FGS diagnoses independently and to administer praziquantel immediately.

Similar messages came out of a study in Liberia. Nganda, Dean and their colleagues piloted a clinical-care package in primary-care settings, which included an FGS symptoms checklist, training in simple gynaecological examinations and treatment guides. Importantly, the package included training traditional midwives, who are trusted in local communities. The study diagnosed and treated 245 women and girls over a period of 6 months, during routine primary health care 6 . A related study 5 in Nigeria returned similar findings. “It’s showing what is possible to do within different under-resourced health systems,” says Theobald.

Making diagnoses in primary-care settings that are accessible to women is key. “We’re trying to steer away from using hospitals as much as possible, because that is really when the bottleneck comes in,” says Bustinduy. The goal, she says, is to instead promote the use of rural clinics staffed with midwives and nurses. It’s also about making the FGS diagnosis less reliant on clinical examinations, which can result in varying diagnoses depending on the physicians, adds Secor, who chairs a World Health Organization diagnostic advisory panel for FGS diagnostics. “We’re really trying to move to something that’s a little bit more objective,” he says.

Taking inspiration from other self-sampling programmes, such as those in place for HPV and HIV, Bustinduy and her colleagues conducted a study of around 600 women to explore the use of self-sampled genital swabs and DNA testing 7 . The BILHIV (bilharzia and HIV) study showed that participants readily accepted self-sampling, that it was as good as clinical sampling at detecting FGS, and, therefore, that home-based self-sampling could present a scalable way of diagnosing FGS in endemic regions. In further experiments, the BILHIV study investigated a lower cost alternative to the DNA-amplifying technique PCR called recombinase polymerase amplification (RPA). Unlike PCR, RPA works at room temperature, and is rapid and highly portable. The findings suggested that RPA was a viable alternative to PCR, and could form part of a portable laboratory to be used at point of care 8 .

FGS is associated with other genital infections, such as HIV, HPV (the main cause of cervical cancer) and trichomoniasis. The Zipime Weka Schista! study therefore aims to see whether testing for all four could be integrated into a single home visit. Like the BILHIV study, the approach is getting a positive reaction from women — especially the self-sampling aspect. “For many, it is the first time they have been screened in this way,” says Chisaila.

There are signs that the condition is slowly starting to shed its neglected status: its association with HIV has brought the sexual and reproductive health communities together, and advocacy by FGS researchers is moving the issue up national and international health agendas. In January, for example, a government committee report recommended that FGS be integrated into the UK government’s sexual and reproductive rights aid programmes. Witnesses testifying to the committee advocated moving away from a focus on individual diseases to a patient-centred one — FGS often falls into a gap between NTD and sexual-health programmes. The Joint United Nations Programme on HIV/AIDS has also recognized the need for FGS integration.

Science has its part to play, too. One aspect is in finding ways to help women like Pedeboy-Knoetze who have tissue damage. “We don’t really have a good way to treat that chronic, longer, more severe pathology,” says Secor. Another is finding ways to prevent the disease, such as vaccination. Adding these to mass drug-administration programmes could reduce the risk of reinfection and help to cut the cycle of transmission. Three vaccines are currently undergoing development. Although each targets the Schistosoma mansoni parasite, which causes intestinal schistosomiasis, one of them also protects against S. haematobium . This vaccine, called Sm-p80 (SchistoShield), is in phase I trials.

More diagnostics are also in the works. DNA swabs are thought not to work well in advanced FGS, because the eggs are walled inside scar tissue, so researchers are exploring two other approaches. One is a test for schistosome antigens in the blood that is scheduled to go into field trials in the next few months, says Secor. Another approach, one Secor's team is taking, is testing for anti-schistosome antibodies. Although these don’t necessarily reveal whether a person has an active infection (antibodies persist for a long time), such tests could be easy to incorporate into routine clinical screening, such as prenatal visits. Tests under development include lateral-flow tests similar to pregnancy tests or those used to rapidly detect COVID-19 (ref. 9 ). These tests can detect antibodies or schistosome antigens and are easy for users to interpret, and would ideally cost less than US$1 per test, says Secor. “I’m optimistic,” he says, “but we’re not there yet.”

Complicating matters is that any new approaches to diagnosing and treating FGS must be adapted to the realities of living in some of the poorest, most marginalized communities in the world. “If we can do that, it’s a win–win for gender equity, rights and social justice,” says Theobald. “It’s a win–win for responsive, effective, person-centred health systems.”

doi: https://doi.org/10.1038/d41586-024-01386-w

This article is part of Nature Outlook: Neglected tropical diseases , a supplement funded by a grant from Merck Sharp & Dohme and with financial support from Moderna . Nature maintains full independence in all editorial decisions related to the content. About this content .

Shanaube, K. et al. Preprint at medRxiv https://doi.org/10.1101/2023.10.02.23296341 (2023)

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Gender equality is a major problem that places women at a disadvantage thereby stymieing economic growth and societal advancement. In the last two decades, extensive research has been conducted on gender related issues, studying both their antecedents and consequences. However, existing literature reviews fail to provide a comprehensive and clear picture of what has been studied so far, which could guide scholars in their future research. Our paper offers a scoping review of a large portion of the research that has been published over the last 22 years, on gender equality and related issues, with a specific focus on business and economics studies. Combining innovative methods drawn from both network analysis and text mining, we provide a synthesis of 15,465 scientific articles. We identify 27 main research topics, we measure their relevance from a semantic point of view and the relationships among them, highlighting the importance of each topic in the overall gender discourse. We find that prominent research topics mostly relate to women in the workforce–e.g., concerning compensation, role, education, decision-making and career progression. However, some of them are losing momentum, and some other research trends–for example related to female entrepreneurship, leadership and participation in the board of directors–are on the rise. Besides introducing a novel methodology to review broad literature streams, our paper offers a map of the main gender-research trends and presents the most popular and the emerging themes, as well as their intersections, outlining important avenues for future research.

Introduction

The persistent gender inequalities that currently exist across the developed and developing world are receiving increasing attention from economists, policymakers, and the general public [e.g., 1 – 3 ]. Economic studies have indicated that women’s education and entry into the workforce contributes to social and economic well-being [e.g., 4 , 5 ], while their exclusion from the labor market and from managerial positions has an impact on overall labor productivity and income per capita [ 6 , 7 ]. The United Nations selected gender equality, with an emphasis on female education, as part of the Millennium Development Goals [ 8 ], and gender equality at-large as one of the 17 Sustainable Development Goals (SDGs) to be achieved by 2030 [ 9 ]. These latter objectives involve not only developing nations, but rather all countries, to achieve economic, social and environmental well-being.

As is the case with many SDGs, gender equality is still far from being achieved and persists across education, access to opportunities, or presence in decision-making positions [ 7 , 10 , 11 ]. As we enter the last decade for the SDGs’ implementation, and while we are battling a global health pandemic, effective and efficient action becomes paramount to reach this ambitious goal.

Scholars have dedicated a massive effort towards understanding gender equality, its determinants, its consequences for women and society, and the appropriate actions and policies to advance women’s equality. Many topics have been covered, ranging from women’s education and human capital [ 12 , 13 ] and their role in society [e.g., 14 , 15 ], to their appointment in firms’ top ranked positions [e.g., 16 , 17 ] and performance implications [e.g., 18 , 19 ]. Despite some attempts, extant literature reviews provide a narrow view on these issues, restricted to specific topics–e.g., female students’ presence in STEM fields [ 20 ], educational gender inequality [ 5 ], the gender pay gap [ 21 ], the glass ceiling effect [ 22 ], leadership [ 23 ], entrepreneurship [ 24 ], women’s presence on the board of directors [ 25 , 26 ], diversity management [ 27 ], gender stereotypes in advertisement [ 28 ], or specific professions [ 29 ]. A comprehensive view on gender-related research, taking stock of key findings and under-studied topics is thus lacking.

Extant literature has also highlighted that gender issues, and their economic and social ramifications, are complex topics that involve a large number of possible antecedents and outcomes [ 7 ]. Indeed, gender equality actions are most effective when implemented in unison with other SDGs (e.g., with SDG 8, see [ 30 ]) in a synergetic perspective [ 10 ]. Many bodies of literature (e.g., business, economics, development studies, sociology and psychology) approach the problem of achieving gender equality from different perspectives–often addressing specific and narrow aspects. This sometimes leads to a lack of clarity about how different issues, circumstances, and solutions may be related in precipitating or mitigating gender inequality or its effects. As the number of papers grows at an increasing pace, this issue is exacerbated and there is a need to step back and survey the body of gender equality literature as a whole. There is also a need to examine synergies between different topics and approaches, as well as gaps in our understanding of how different problems and solutions work together. Considering the important topic of women’s economic and social empowerment, this paper aims to fill this gap by answering the following research question: what are the most relevant findings in the literature on gender equality and how do they relate to each other ?

To do so, we conduct a scoping review [ 31 ], providing a synthesis of 15,465 articles dealing with gender equity related issues published in the last twenty-two years, covering both the periods of the MDGs and the SDGs (i.e., 2000 to mid 2021) in all the journals indexed in the Academic Journal Guide’s 2018 ranking of business and economics journals. Given the huge amount of research conducted on the topic, we adopt an innovative methodology, which relies on social network analysis and text mining. These techniques are increasingly adopted when surveying large bodies of text. Recently, they were applied to perform analysis of online gender communication differences [ 32 ] and gender behaviors in online technology communities [ 33 ], to identify and classify sexual harassment instances in academia [ 34 ], and to evaluate the gender inclusivity of disaster management policies [ 35 ].

Applied to the title, abstracts and keywords of the articles in our sample, this methodology allows us to identify a set of 27 recurrent topics within which we automatically classify the papers. Introducing additional novelty, by means of the Semantic Brand Score (SBS) indicator [ 36 ] and the SBS BI app [ 37 ], we assess the importance of each topic in the overall gender equality discourse and its relationships with the other topics, as well as trends over time, with a more accurate description than that offered by traditional literature reviews relying solely on the number of papers presented in each topic.

This methodology, applied to gender equality research spanning the past twenty-two years, enables two key contributions. First, we extract the main message that each document is conveying and how this is connected to other themes in literature, providing a rich picture of the topics that are at the center of the discourse, as well as of the emerging topics. Second, by examining the semantic relationship between topics and how tightly their discourses are linked, we can identify the key relationships and connections between different topics. This semi-automatic methodology is also highly reproducible with minimum effort.

This literature review is organized as follows. In the next section, we present how we selected relevant papers and how we analyzed them through text mining and social network analysis. We then illustrate the importance of 27 selected research topics, measured by means of the SBS indicator. In the results section, we present an overview of the literature based on the SBS results–followed by an in-depth narrative analysis of the top 10 topics (i.e., those with the highest SBS) and their connections. Subsequently, we highlight a series of under-studied connections between the topics where there is potential for future research. Through this analysis, we build a map of the main gender-research trends in the last twenty-two years–presenting the most popular themes. We conclude by highlighting key areas on which research should focused in the future.

Our aim is to map a broad topic, gender equality research, that has been approached through a host of different angles and through different disciplines. Scoping reviews are the most appropriate as they provide the freedom to map different themes and identify literature gaps, thereby guiding the recommendation of new research agendas [ 38 ].

Several practical approaches have been proposed to identify and assess the underlying topics of a specific field using big data [ 39 – 41 ], but many of them fail without proper paper retrieval and text preprocessing. This is specifically true for a research field such as the gender-related one, which comprises the work of scholars from different backgrounds. In this section, we illustrate a novel approach for the analysis of scientific (gender-related) papers that relies on methods and tools of social network analysis and text mining. Our procedure has four main steps: (1) data collection, (2) text preprocessing, (3) keywords extraction and classification, and (4) evaluation of semantic importance and image.

Data collection

In this study, we analyze 22 years of literature on gender-related research. Following established practice for scoping reviews [ 42 ], our data collection consisted of two main steps, which we summarize here below.

Firstly, we retrieved from the Scopus database all the articles written in English that contained the term “gender” in their title, abstract or keywords and were published in a journal listed in the Academic Journal Guide 2018 ranking of the Chartered Association of Business Schools (CABS) ( https://charteredabs.org/wp-content/uploads/2018/03/AJG2018-Methodology.pdf ), considering the time period from Jan 2000 to May 2021. We used this information considering that abstracts, titles and keywords represent the most informative part of a paper, while using the full-text would increase the signal-to-noise ratio for information extraction. Indeed, these textual elements already demonstrated to be reliable sources of information for the task of domain lexicon extraction [ 43 , 44 ]. We chose Scopus as source of literature because of its popularity, its update rate, and because it offers an API to ease the querying process. Indeed, while it does not allow to retrieve the full text of scientific articles, the Scopus API offers access to titles, abstracts, citation information and metadata for all its indexed scholarly journals. Moreover, we decided to focus on the journals listed in the AJG 2018 ranking because we were interested in reviewing business and economics related gender studies only. The AJG is indeed widely used by universities and business schools as a reference point for journal and research rigor and quality. This first step, executed in June 2021, returned more than 55,000 papers.

In the second step–because a look at the papers showed very sparse results, many of which were not in line with the topic of this literature review (e.g., papers dealing with health care or medical issues, where the word gender indicates the gender of the patients)–we applied further inclusion criteria to make the sample more focused on the topic of this literature review (i.e., women’s gender equality issues). Specifically, we only retained those papers mentioning, in their title and/or abstract, both gender-related keywords (e.g., daughter, female, mother) and keywords referring to bias and equality issues (e.g., equality, bias, diversity, inclusion). After text pre-processing (see next section), keywords were first identified from a frequency-weighted list of words found in the titles, abstracts and keywords in the initial list of papers, extracted through text mining (following the same approach as [ 43 ]). They were selected by two of the co-authors independently, following respectively a bottom up and a top-down approach. The bottom-up approach consisted of examining the words found in the frequency-weighted list and classifying those related to gender and equality. The top-down approach consisted in searching in the word list for notable gender and equality-related words. Table 1 reports the sets of keywords we considered, together with some examples of words that were used to search for their presence in the dataset (a full list is provided in the S1 Text ). At end of this second step, we obtained a final sample of 15,465 relevant papers.

Text processing and keyword extraction

Text preprocessing aims at structuring text into a form that can be analyzed by statistical models. In the present section, we describe the preprocessing steps we applied to paper titles and abstracts, which, as explained below, partially follow a standard text preprocessing pipeline [ 45 ]. These activities have been performed using the R package udpipe [ 46 ].

The first step is n-gram extraction (i.e., a sequence of words from a given text sample) to identify which n-grams are important in the analysis, since domain-specific lexicons are often composed by bi-grams and tri-grams [ 47 ]. Multi-word extraction is usually implemented with statistics and linguistic rules, thus using the statistical properties of n-grams or machine learning approaches [ 48 ]. However, for the present paper, we used Scopus metadata in order to have a more effective and efficient n-grams collection approach [ 49 ]. We used the keywords of each paper in order to tag n-grams with their associated keywords automatically. Using this greedy approach, it was possible to collect all the keywords listed by the authors of the papers. From this list, we extracted only keywords composed by two, three and four words, we removed all the acronyms and rare keywords (i.e., appearing in less than 1% of papers), and we clustered keywords showing a high orthographic similarity–measured using a Levenshtein distance [ 50 ] lower than 2, considering these groups of keywords as representing same concepts, but expressed with different spelling. After tagging the n-grams in the abstracts, we followed a common data preparation pipeline that consists of the following steps: (i) tokenization, that splits the text into tokens (i.e., single words and previously tagged multi-words); (ii) removal of stop-words (i.e. those words that add little meaning to the text, usually being very common and short functional words–such as “and”, “or”, or “of”); (iii) parts-of-speech tagging, that is providing information concerning the morphological role of a word and its morphosyntactic context (e.g., if the token is a determiner, the next token is a noun or an adjective with very high confidence, [ 51 ]); and (iv) lemmatization, which consists in substituting each word with its dictionary form (or lemma). The output of the latter step allows grouping together the inflected forms of a word. For example, the verbs “am”, “are”, and “is” have the shared lemma “be”, or the nouns “cat” and “cats” both share the lemma “cat”. We preferred lemmatization over stemming [ 52 ] in order to obtain more interpretable results.

In addition, we identified a further set of keywords (with respect to those listed in the “keywords” field) by applying a series of automatic words unification and removal steps, as suggested in past research [ 53 , 54 ]. We removed: sparse terms (i.e., occurring in less than 0.1% of all documents), common terms (i.e., occurring in more than 10% of all documents) and retained only nouns and adjectives. It is relevant to notice that no document was lost due to these steps. We then used the TF-IDF function [ 55 ] to produce a new list of keywords. We additionally tested other approaches for the identification and clustering of keywords–such as TextRank [ 56 ] or Latent Dirichlet Allocation [ 57 ]–without obtaining more informative results.

Classification of research topics

To guide the literature analysis, two experts met regularly to examine the sample of collected papers and to identify the main topics and trends in gender research. Initially, they conducted brainstorming sessions on the topics they expected to find, due to their knowledge of the literature. This led to an initial list of topics. Subsequently, the experts worked independently, also supported by the keywords in paper titles and abstracts extracted with the procedure described above.

Considering all this information, each expert identified and clustered relevant keywords into topics. At the end of the process, the two assignments were compared and exhibited a 92% agreement. Another meeting was held to discuss discordant cases and reach a consensus. This resulted in a list of 27 topics, briefly introduced in Table 2 and subsequently detailed in the following sections.

Evaluation of semantic importance

Working on the lemmatized corpus of the 15,465 papers included in our sample, we proceeded with the evaluation of semantic importance trends for each topic and with the analysis of their connections and prevalent textual associations. To this aim, we used the Semantic Brand Score indicator [ 36 ], calculated through the SBS BI webapp [ 37 ] that also produced a brand image report for each topic. For this study we relied on the computing resources of the ENEA/CRESCO infrastructure [ 58 ].

The Semantic Brand Score (SBS) is a measure of semantic importance that combines methods of social network analysis and text mining. It is usually applied for the analysis of (big) textual data to evaluate the importance of one or more brands, names, words, or sets of keywords [ 36 ]. Indeed, the concept of “brand” is intended in a flexible way and goes beyond products or commercial brands. In this study, we evaluate the SBS time-trends of the keywords defining the research topics discussed in the previous section. Semantic importance comprises the three dimensions of topic prevalence, diversity and connectivity. Prevalence measures how frequently a research topic is used in the discourse. The more a topic is mentioned by scientific articles, the more the research community will be aware of it, with possible increase of future studies; this construct is partly related to that of brand awareness [ 59 ]. This effect is even stronger, considering that we are analyzing the title, abstract and keywords of the papers, i.e. the parts that have the highest visibility. A very important characteristic of the SBS is that it considers the relationships among words in a text. Topic importance is not just a matter of how frequently a topic is mentioned, but also of the associations a topic has in the text. Specifically, texts are transformed into networks of co-occurring words, and relationships are studied through social network analysis [ 60 ]. This step is necessary to calculate the other two dimensions of our semantic importance indicator. Accordingly, a social network of words is generated for each time period considered in the analysis–i.e., a graph made of n nodes (words) and E edges weighted by co-occurrence frequency, with W being the set of edge weights. The keywords representing each topic were clustered into single nodes.

The construct of diversity relates to that of brand image [ 59 ], in the sense that it considers the richness and distinctiveness of textual (topic) associations. Considering the above-mentioned networks, we calculated diversity using the distinctiveness centrality metric–as in the formula presented by Fronzetti Colladon and Naldi [ 61 ].

Lastly, connectivity was measured as the weighted betweenness centrality [ 62 , 63 ] of each research topic node. We used the formula presented by Wasserman and Faust [ 60 ]. The dimension of connectivity represents the “brokerage power” of each research topic–i.e., how much it can serve as a bridge to connect other terms (and ultimately topics) in the discourse [ 36 ].

The SBS is the final composite indicator obtained by summing the standardized scores of prevalence, diversity and connectivity. Standardization was carried out considering all the words in the corpus, for each specific timeframe.

This methodology, applied to a large and heterogeneous body of text, enables to automatically identify two important sets of information that add value to the literature review. Firstly, the relevance of each topic in literature is measured through a composite indicator of semantic importance, rather than simply looking at word frequencies. This provides a much richer picture of the topics that are at the center of the discourse, as well as of the topics that are emerging in the literature. Secondly, it enables to examine the extent of the semantic relationship between topics, looking at how tightly their discourses are linked. In a field such as gender equality, where many topics are closely linked to each other and present overlaps in issues and solutions, this methodology offers a novel perspective with respect to traditional literature reviews. In addition, it ensures reproducibility over time and the possibility to semi-automatically update the analysis, as new papers become available.

Overview of main topics

In terms of descriptive textual statistics, our corpus is made of 15,465 text documents, consisting of a total of 2,685,893 lemmatized tokens (words) and 32,279 types. As a result, the type-token ratio is 1.2%. The number of hapaxes is 12,141, with a hapax-token ratio of 37.61%.

Fig 1 shows the list of 27 topics by decreasing SBS. The most researched topic is compensation , exceeding all others in prevalence, diversity, and connectivity. This means it is not only mentioned more often than other topics, but it is also connected to a greater number of other topics and is central to the discourse on gender equality. The next four topics are, in order of SBS, role , education , decision-making , and career progression . These topics, except for education , all concern women in the workforce. Between these first five topics and the following ones there is a clear drop in SBS scores. In particular, the topics that follow have a lower connectivity than the first five. They are hiring , performance , behavior , organization , and human capital . Again, except for behavior and human capital , the other three topics are purely related to women in the workforce. After another drop-off, the following topics deal prevalently with women in society. This trend highlights that research on gender in business journals has so far mainly paid attention to the conditions that women experience in business contexts, while also devoting some attention to women in society.

Fig 2 shows the SBS time series of the top 10 topics. While there has been a general increase in the number of Scopus-indexed publications in the last decade, we notice that some SBS trends remain steady, or even decrease. In particular, we observe that the main topic of the last twenty-two years, compensation , is losing momentum. Since 2016, it has been surpassed by decision-making , education and role , which may indicate that literature is increasingly attempting to identify root causes of compensation inequalities. Moreover, in the last two years, the topics of hiring , performance , and organization are experiencing the largest importance increase.

Fig 3 shows the SBS time trends of the remaining 17 topics (i.e., those not in the top 10). As we can see from the graph, there are some that maintain a steady trend–such as reputation , management , networks and governance , which also seem to have little importance. More relevant topics with average stationary trends (except for the last two years) are culture , family , and parenting . The feminine topic is among the most important here, and one of those that exhibit the larger variations over time (similarly to leadership ). On the other hand, the are some topics that, even if not among the most important, show increasing SBS trends; therefore, they could be considered as emerging topics and could become popular in the near future. These are entrepreneurship , leadership , board of directors , and sustainability . These emerging topics are also interesting to anticipate future trends in gender equality research that are conducive to overall equality in society.

In addition to the SBS score of the different topics, the network of terms they are associated to enables to gauge the extent to which their images (textual associations) overlap or differ ( Fig 4 ).

There is a central cluster of topics with high similarity, which are all connected with women in the workforce. The cluster includes topics such as organization , decision-making , performance , hiring , human capital , education and compensation . In addition, the topic of well-being is found within this cluster, suggesting that women’s equality in the workforce is associated to well-being considerations. The emerging topics of entrepreneurship and leadership are also closely connected with each other, possibly implying that leadership is a much-researched quality in female entrepreneurship. Topics that are relatively more distant include personality , politics , feminine , empowerment , management , board of directors , reputation , governance , parenting , masculine and network .

The following sections describe the top 10 topics and their main associations in literature (see Table 3 ), while providing a brief overview of the emerging topics.

Compensation

The topic of compensation is related to the topics of role , hiring , education and career progression , however, also sees a very high association with the words gap and inequality . Indeed, a well-known debate in degrowth economics centers around whether and how to adequately compensate women for their childbearing, childrearing, caregiver and household work [e.g., 30 ].

Even in paid work, women continue being offered lower compensations than their male counterparts who have the same job or cover the same role [ 64 – 67 ]. This severe inequality has been widely studied by scholars over the last twenty-two years. Dealing with this topic, some specific roles have been addressed. Specifically, research highlighted differences in compensation between female and male CEOs [e.g., 68 ], top executives [e.g., 69 ], and boards’ directors [e.g., 70 ]. Scholars investigated the determinants of these gaps, such as the gender composition of the board [e.g., 71 – 73 ] or women’s individual characteristics [e.g., 71 , 74 ].

Among these individual characteristics, education plays a relevant role [ 75 ]. Education is indeed presented as the solution for women, not only to achieve top executive roles, but also to reduce wage inequality [e.g., 76 , 77 ]. Past research has highlighted education influences on gender wage gaps, specifically referring to gender differences in skills [e.g., 78 ], college majors [e.g., 79 ], and college selectivity [e.g., 80 ].

Finally, the wage gap issue is strictly interrelated with hiring –e.g., looking at whether being a mother affects hiring and compensation [e.g., 65 , 81 ] or relating compensation to unemployment [e.g., 82 ]–and career progression –for instance looking at meritocracy [ 83 , 84 ] or the characteristics of the boss for whom women work [e.g., 85 ].

The roles covered by women have been deeply investigated. Scholars have focused on the role of women in their families and the society as a whole [e.g., 14 , 15 ], and, more widely, in business contexts [e.g., 18 , 81 ]. Indeed, despite still lagging behind their male counterparts [e.g., 86 , 87 ], in the last decade there has been an increase in top ranked positions achieved by women [e.g., 88 , 89 ]. Following this phenomenon, scholars have posed greater attention towards the presence of women in the board of directors [e.g., 16 , 18 , 90 , 91 ], given the increasing pressure to appoint female directors that firms, especially listed ones, have experienced. Other scholars have focused on the presence of women covering the role of CEO [e.g., 17 , 92 ] or being part of the top management team [e.g., 93 ]. Irrespectively of the level of analysis, all these studies tried to uncover the antecedents of women’s presence among top managers [e.g., 92 , 94 ] and the consequences of having a them involved in the firm’s decision-making –e.g., on performance [e.g., 19 , 95 , 96 ], risk [e.g., 97 , 98 ], and corporate social responsibility [e.g., 99 , 100 ].

Besides studying the difficulties and discriminations faced by women in getting a job [ 81 , 101 ], and, more specifically in the hiring , appointment, or career progression to these apical roles [e.g., 70 , 83 ], the majority of research of women’s roles dealt with compensation issues. Specifically, scholars highlight the pay-gap that still exists between women and men, both in general [e.g., 64 , 65 ], as well as referring to boards’ directors [e.g., 70 , 102 ], CEOs and executives [e.g., 69 , 103 , 104 ].

Finally, other scholars focused on the behavior of women when dealing with business. In this sense, particular attention has been paid to leadership and entrepreneurial behaviors. The former quite overlaps with dealing with the roles mentioned above, but also includes aspects such as leaders being stereotyped as masculine [e.g., 105 ], the need for greater exposure to female leaders to reduce biases [e.g., 106 ], or female leaders acting as queen bees [e.g., 107 ]. Regarding entrepreneurship , scholars mainly investigated women’s entrepreneurial entry [e.g., 108 , 109 ], differences between female and male entrepreneurs in the evaluations and funding received from investors [e.g., 110 , 111 ], and their performance gap [e.g., 112 , 113 ].

Education has long been recognized as key to social advancement and economic stability [ 114 ], for job progression and also a barrier to gender equality, especially in STEM-related fields. Research on education and gender equality is mostly linked with the topics of compensation , human capital , career progression , hiring , parenting and decision-making .

Education contributes to a higher human capital [ 115 ] and constitutes an investment on the part of women towards their future. In this context, literature points to the gender gap in educational attainment, and the consequences for women from a social, economic, personal and professional standpoint. Women are found to have less access to formal education and information, especially in emerging countries, which in turn may cause them to lose social and economic opportunities [e.g., 12 , 116 – 119 ]. Education in local and rural communities is also paramount to communicate the benefits of female empowerment , contributing to overall societal well-being [e.g., 120 ].

Once women access education, the image they have of the world and their place in society (i.e., habitus) affects their education performance [ 13 ] and is passed on to their children. These situations reinforce gender stereotypes, which become self-fulfilling prophecies that may negatively affect female students’ performance by lowering their confidence and heightening their anxiety [ 121 , 122 ]. Besides formal education, also the information that women are exposed to on a daily basis contributes to their human capital . Digital inequalities, for instance, stems from men spending more time online and acquiring higher digital skills than women [ 123 ].

Education is also a factor that should boost employability of candidates and thus hiring , career progression and compensation , however the relationship between these factors is not straightforward [ 115 ]. First, educational choices ( decision-making ) are influenced by variables such as self-efficacy and the presence of barriers, irrespectively of the career opportunities they offer, especially in STEM [ 124 ]. This brings additional difficulties to women’s enrollment and persistence in scientific and technical fields of study due to stereotypes and biases [ 125 , 126 ]. Moreover, access to education does not automatically translate into job opportunities for women and minority groups [ 127 , 128 ] or into female access to managerial positions [ 129 ].

Finally, parenting is reported as an antecedent of education [e.g., 130 ], with much of the literature focusing on the role of parents’ education on the opportunities afforded to children to enroll in education [ 131 – 134 ] and the role of parenting in their offspring’s perception of study fields and attitudes towards learning [ 135 – 138 ]. Parental education is also a predictor of the other related topics, namely human capital and compensation [ 139 ].

Decision-making

This literature mainly points to the fact that women are thought to make decisions differently than men. Women have indeed different priorities, such as they care more about people’s well-being, working with people or helping others, rather than maximizing their personal (or their firm’s) gain [ 140 ]. In other words, women typically present more communal than agentic behaviors, which are instead more frequent among men [ 141 ]. These different attitude, behavior and preferences in turn affect the decisions they make [e.g., 142 ] and the decision-making of the firm in which they work [e.g., 143 ].

At the individual level, gender affects, for instance, career aspirations [e.g., 144 ] and choices [e.g., 142 , 145 ], or the decision of creating a venture [e.g., 108 , 109 , 146 ]. Moreover, in everyday life, women and men make different decisions regarding partners [e.g., 147 ], childcare [e.g., 148 ], education [e.g., 149 ], attention to the environment [e.g., 150 ] and politics [e.g., 151 ].

At the firm level, scholars highlighted, for example, how the presence of women in the board affects corporate decisions [e.g., 152 , 153 ], that female CEOs are more conservative in accounting decisions [e.g., 154 ], or that female CFOs tend to make more conservative decisions regarding the firm’s financial reporting [e.g., 155 ]. Nevertheless, firm level research also investigated decisions that, influenced by gender bias, affect women, such as those pertaining hiring [e.g., 156 , 157 ], compensation [e.g., 73 , 158 ], or the empowerment of women once appointed [ 159 ].

Career progression

Once women have entered the workforce, the key aspect to achieve gender equality becomes career progression , including efforts toward overcoming the glass ceiling. Indeed, according to the SBS analysis, career progression is highly related to words such as work, social issues and equality. The topic with which it has the highest semantic overlap is role , followed by decision-making , hiring , education , compensation , leadership , human capital , and family .

Career progression implies an advancement in the hierarchical ladder of the firm, assigning managerial roles to women. Coherently, much of the literature has focused on identifying rationales for a greater female participation in the top management team and board of directors [e.g., 95 ] as well as the best criteria to ensure that the decision-makers promote the most valuable employees irrespectively of their individual characteristics, such as gender [e.g., 84 ]. The link between career progression , role and compensation is often provided in practice by performance appraisal exercises, frequently rooted in a culture of meritocracy that guides bonuses, salary increases and promotions. However, performance appraisals can actually mask gender-biased decisions where women are held to higher standards than their male colleagues [e.g., 83 , 84 , 95 , 160 , 161 ]. Women often have less opportunities to gain leadership experience and are less visible than their male colleagues, which constitute barriers to career advancement [e.g., 162 ]. Therefore, transparency and accountability, together with procedures that discourage discretionary choices, are paramount to achieve a fair career progression [e.g., 84 ], together with the relaxation of strict job boundaries in favor of cross-functional and self-directed tasks [e.g., 163 ].

In addition, a series of stereotypes about the type of leadership characteristics that are required for top management positions, which fit better with typical male and agentic attributes, are another key barrier to career advancement for women [e.g., 92 , 160 ].

Hiring is the entrance gateway for women into the workforce. Therefore, it is related to other workforce topics such as compensation , role , career progression , decision-making , human capital , performance , organization and education .

A first stream of literature focuses on the process leading up to candidates’ job applications, demonstrating that bias exists before positions are even opened, and it is perpetuated both by men and women through networking and gatekeeping practices [e.g., 164 , 165 ].

The hiring process itself is also subject to biases [ 166 ], for example gender-congruity bias that leads to men being preferred candidates in male-dominated sectors [e.g., 167 ], women being hired in positions with higher risk of failure [e.g., 168 ] and limited transparency and accountability afforded by written processes and procedures [e.g., 164 ] that all contribute to ascriptive inequality. In addition, providing incentives for evaluators to hire women may actually work to this end; however, this is not the case when supporting female candidates endangers higher-ranking male ones [ 169 ].

Another interesting perspective, instead, looks at top management teams’ composition and the effects on hiring practices, indicating that firms with more women in top management are less likely to lay off staff [e.g., 152 ].

Performance

Several scholars posed their attention towards women’s performance, its consequences [e.g., 170 , 171 ] and the implications of having women in decision-making positions [e.g., 18 , 19 ].

At the individual level, research focused on differences in educational and academic performance between women and men, especially referring to the gender gap in STEM fields [e.g., 171 ]. The presence of stereotype threats–that is the expectation that the members of a social group (e.g., women) “must deal with the possibility of being judged or treated stereotypically, or of doing something that would confirm the stereotype” [ 172 ]–affects women’s interested in STEM [e.g., 173 ], as well as their cognitive ability tests, penalizing them [e.g., 174 ]. A stronger gender identification enhances this gap [e.g., 175 ], whereas mentoring and role models can be used as solutions to this problem [e.g., 121 ]. Despite the negative effect of stereotype threats on girls’ performance [ 176 ], female and male students perform equally in mathematics and related subjects [e.g., 177 ]. Moreover, while individuals’ performance at school and university generally affects their achievements and the field in which they end up working, evidence reveals that performance in math or other scientific subjects does not explain why fewer women enter STEM working fields; rather this gap depends on other aspects, such as culture, past working experiences, or self-efficacy [e.g., 170 ]. Finally, scholars have highlighted the penalization that women face for their positive performance, for instance when they succeed in traditionally male areas [e.g., 178 ]. This penalization is explained by the violation of gender-stereotypic prescriptions [e.g., 179 , 180 ], that is having women well performing in agentic areas, which are typical associated to men. Performance penalization can thus be overcome by clearly conveying communal characteristics and behaviors [ 178 ].

Evidence has been provided on how the involvement of women in boards of directors and decision-making positions affects firms’ performance. Nevertheless, results are mixed, with some studies showing positive effects on financial [ 19 , 181 , 182 ] and corporate social performance [ 99 , 182 , 183 ]. Other studies maintain a negative association [e.g., 18 ], and other again mixed [e.g., 184 ] or non-significant association [e.g., 185 ]. Also with respect to the presence of a female CEO, mixed results emerged so far, with some researches demonstrating a positive effect on firm’s performance [e.g., 96 , 186 ], while other obtaining only a limited evidence of this relationship [e.g., 103 ] or a negative one [e.g., 187 ].

Finally, some studies have investigated whether and how women’s performance affects their hiring [e.g., 101 ] and career progression [e.g., 83 , 160 ]. For instance, academic performance leads to different returns in hiring for women and men. Specifically, high-achieving men are called back significantly more often than high-achieving women, which are penalized when they have a major in mathematics; this result depends on employers’ gendered standards for applicants [e.g., 101 ]. Once appointed, performance ratings are more strongly related to promotions for women than men, and promoted women typically show higher past performance ratings than those of promoted men. This suggesting that women are subject to stricter standards for promotion [e.g., 160 ].

Behavioral aspects related to gender follow two main streams of literature. The first examines female personality and behavior in the workplace, and their alignment with cultural expectations or stereotypes [e.g., 188 ] as well as their impacts on equality. There is a common bias that depicts women as less agentic than males. Certain characteristics, such as those more congruent with male behaviors–e.g., self-promotion [e.g., 189 ], negotiation skills [e.g., 190 ] and general agentic behavior [e.g., 191 ]–, are less accepted in women. However, characteristics such as individualism in women have been found to promote greater gender equality in society [ 192 ]. In addition, behaviors such as display of emotions [e.g., 193 ], which are stereotypically female, work against women’s acceptance in the workplace, requiring women to carefully moderate their behavior to avoid exclusion. A counter-intuitive result is that women and minorities, which are more marginalized in the workplace, tend to be better problem-solvers in innovation competitions due to their different knowledge bases [ 194 ].

The other side of the coin is examined in a parallel literature stream on behavior towards women in the workplace. As a result of biases, prejudices and stereotypes, women may experience adverse behavior from their colleagues, such as incivility and harassment, which undermine their well-being [e.g., 195 , 196 ]. Biases that go beyond gender, such as for overweight people, are also more strongly applied to women [ 197 ].

Organization

The role of women and gender bias in organizations has been studied from different perspectives, which mirror those presented in detail in the following sections. Specifically, most research highlighted the stereotypical view of leaders [e.g., 105 ] and the roles played by women within firms, for instance referring to presence in the board of directors [e.g., 18 , 90 , 91 ], appointment as CEOs [e.g., 16 ], or top executives [e.g., 93 ].

Scholars have investigated antecedents and consequences of the presence of women in these apical roles. On the one side they looked at hiring and career progression [e.g., 83 , 92 , 160 , 168 , 198 ], finding women typically disadvantaged with respect to their male counterparts. On the other side, they studied women’s leadership styles and influence on the firm’s decision-making [e.g., 152 , 154 , 155 , 199 ], with implications for performance [e.g., 18 , 19 , 96 ].

Human capital

Human capital is a transverse topic that touches upon many different aspects of female gender equality. As such, it has the most associations with other topics, starting with education as mentioned above, with career-related topics such as role , decision-making , hiring , career progression , performance , compensation , leadership and organization . Another topic with which there is a close connection is behavior . In general, human capital is approached both from the education standpoint but also from the perspective of social capital.

The behavioral aspect in human capital comprises research related to gender differences for example in cultural and religious beliefs that influence women’s attitudes and perceptions towards STEM subjects [ 142 , 200 – 202 ], towards employment [ 203 ] or towards environmental issues [ 150 , 204 ]. These cultural differences also emerge in the context of globalization which may accelerate gender equality in the workforce [ 205 , 206 ]. Gender differences also appear in behaviors such as motivation [ 207 ], and in negotiation [ 190 ], and have repercussions on women’s decision-making related to their careers. The so-called gender equality paradox sees women in countries with lower gender equality more likely to pursue studies and careers in STEM fields, whereas the gap in STEM enrollment widens as countries achieve greater equality in society [ 171 ].

Career progression is modeled by literature as a choice-process where personal preferences, culture and decision-making affect the chosen path and the outcomes. Some literature highlights how women tend to self-select into different professions than men, often due to stereotypes rather than actual ability to perform in these professions [ 142 , 144 ]. These stereotypes also affect the perceptions of female performance or the amount of human capital required to equal male performance [ 110 , 193 , 208 ], particularly for mothers [ 81 ]. It is therefore often assumed that women are better suited to less visible and less leadership -oriented roles [ 209 ]. Women also express differing preferences towards work-family balance, which affect whether and how they pursue human capital gains [ 210 ], and ultimately their career progression and salary .

On the other hand, men are often unaware of gendered processes and behaviors that they carry forward in their interactions and decision-making [ 211 , 212 ]. Therefore, initiatives aimed at increasing managers’ human capital –by raising awareness of gender disparities in their organizations and engaging them in diversity promotion–are essential steps to counter gender bias and segregation [ 213 ].

Emerging topics: Leadership and entrepreneurship

Among the emerging topics, the most pervasive one is women reaching leadership positions in the workforce and in society. This is still a rare occurrence for two main types of factors, on the one hand, bias and discrimination make it harder for women to access leadership positions [e.g., 214 – 216 ], on the other hand, the competitive nature and high pressure associated with leadership positions, coupled with the lack of women currently represented, reduce women’s desire to achieve them [e.g., 209 , 217 ]. Women are more effective leaders when they have access to education, resources and a diverse environment with representation [e.g., 218 , 219 ].

One sector where there is potential for women to carve out a leadership role is entrepreneurship . Although at the start of the millennium the discourse on entrepreneurship was found to be “discriminatory, gender-biased, ethnocentrically determined and ideologically controlled” [ 220 ], an increasing body of literature is studying how to stimulate female entrepreneurship as an alternative pathway to wealth, leadership and empowerment [e.g., 221 ]. Many barriers exist for women to access entrepreneurship, including the institutional and legal environment, social and cultural factors, access to knowledge and resources, and individual behavior [e.g., 222 , 223 ]. Education has been found to raise women’s entrepreneurial intentions [e.g., 224 ], although this effect is smaller than for men [e.g., 109 ]. In addition, increasing self-efficacy and risk-taking behavior constitute important success factors [e.g., 225 ].

Finally, the topic of sustainability is worth mentioning, as it is the primary objective of the SDGs and is closely associated with societal well-being. As society grapples with the effects of climate change and increasing depletion of natural resources, a narrative has emerged on women and their greater link to the environment [ 226 ]. Studies in developed countries have found some support for women leaders’ attention to sustainability issues in firms [e.g., 227 – 229 ], and smaller resource consumption by women [ 230 ]. At the same time, women will likely be more affected by the consequences of climate change [e.g., 230 ] but often lack the decision-making power to influence local decision-making on resource management and environmental policies [e.g., 231 ].

Research gaps and conclusions

Research on gender equality has advanced rapidly in the past decades, with a steady increase in publications, both in mainstream topics related to women in education and the workforce, and in emerging topics. Through a novel approach combining methods of text mining and social network analysis, we examined a comprehensive body of literature comprising 15,465 papers published between 2000 and mid 2021 on topics related to gender equality. We identified a set of 27 topics addressed by the literature and examined their connections.

At the highest level of abstraction, it is worth noting that papers abound on the identification of issues related to gender inequalities and imbalances in the workforce and in society. Literature has thoroughly examined the (unconscious) biases, barriers, stereotypes, and discriminatory behaviors that women are facing as a result of their gender. Instead, there are much fewer papers that discuss or demonstrate effective solutions to overcome gender bias [e.g., 121 , 143 , 145 , 163 , 194 , 213 , 232 ]. This is partly due to the relative ease in studying the status quo, as opposed to studying changes in the status quo. However, we observed a shift in the more recent years towards solution seeking in this domain, which we strongly encourage future researchers to focus on. In the future, we may focus on collecting and mapping pro-active contributions to gender studies, using additional Natural Language Processing techniques, able to measure the sentiment of scientific papers [ 43 ].

All of the mainstream topics identified in our literature review are closely related, and there is a wealth of insights looking at the intersection between issues such as education and career progression or human capital and role . However, emerging topics are worthy of being furtherly explored. It would be interesting to see more work on the topic of female entrepreneurship , exploring aspects such as education , personality , governance , management and leadership . For instance, how can education support female entrepreneurship? How can self-efficacy and risk-taking behaviors be taught or enhanced? What are the differences in managerial and governance styles of female entrepreneurs? Which personality traits are associated with successful entrepreneurs? Which traits are preferred by venture capitalists and funding bodies?

The emerging topic of sustainability also deserves further attention, as our society struggles with climate change and its consequences. It would be interesting to see more research on the intersection between sustainability and entrepreneurship , looking at how female entrepreneurs are tackling sustainability issues, examining both their business models and their company governance . In addition, scholars are suggested to dig deeper into the relationship between family values and behaviors.

Moreover, it would be relevant to understand how women’s networks (social capital), or the composition and structure of social networks involving both women and men, enable them to increase their remuneration and reach top corporate positions, participate in key decision-making bodies, and have a voice in communities. Furthermore, the achievement of gender equality might significantly change firm networks and ecosystems, with important implications for their performance and survival.

Similarly, research at the nexus of (corporate) governance , career progression , compensation and female empowerment could yield useful insights–for example discussing how enterprises, institutions and countries are managed and the impact for women and other minorities. Are there specific governance structures that favor diversity and inclusion?

Lastly, we foresee an emerging stream of research pertaining how the spread of the COVID-19 pandemic challenged women, especially in the workforce, by making gender biases more evident.

For our analysis, we considered a set of 15,465 articles downloaded from the Scopus database (which is the largest abstract and citation database of peer-reviewed literature). As we were interested in reviewing business and economics related gender studies, we only considered those papers published in journals listed in the Academic Journal Guide (AJG) 2018 ranking of the Chartered Association of Business Schools (CABS). All the journals listed in this ranking are also indexed by Scopus. Therefore, looking at a single database (i.e., Scopus) should not be considered a limitation of our study. However, future research could consider different databases and inclusion criteria.

With our literature review, we offer researchers a comprehensive map of major gender-related research trends over the past twenty-two years. This can serve as a lens to look to the future, contributing to the achievement of SDG5. Researchers may use our study as a starting point to identify key themes addressed in the literature. In addition, our methodological approach–based on the use of the Semantic Brand Score and its webapp–could support scholars interested in reviewing other areas of research.

Supporting information

Acknowledgments.

The computing resources and the related technical support used for this work have been provided by CRESCO/ENEAGRID High Performance Computing infrastructure and its staff. CRESCO/ENEAGRID High Performance Computing infrastructure is funded by ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development and by Italian and European research programmes (see http://www.cresco.enea.it/english for information).

Funding Statement

P.B and F.C.: Grant of the Department of Energy, Systems, Territory and Construction of the University of Pisa (DESTEC) for the project “Measuring Gender Bias with Semantic Analysis: The Development of an Assessment Tool and its Application in the European Space Industry. P.B., F.C., A.F.C., P.R.: Grant of the Italian Association of Management Engineering (AiIG), “Misure di sostegno ai soci giovani AiIG” 2020, for the project “Gender Equality Through Data Intelligence (GEDI)”. F.C.: EU project ASSETs+ Project (Alliance for Strategic Skills addressing Emerging Technologies in Defence) EAC/A03/2018 - Erasmus+ programme, Sector Skills Alliances, Lot 3: Sector Skills Alliance for implementing a new strategic approach (Blueprint) to sectoral cooperation on skills G.A. NUMBER: 612678-EPP-1-2019-1-IT-EPPKA2-SSA-B.

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Risk–return preferences, gender inequalities and the moderating role of a counselling intervention on choice of major: evidence from a field and survey experiment

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• Published: 14 May 2024

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• Lukas Fervers   ORCID: orcid.org/0000-0002-7850-700X 1 , 2 ,
• Marita Jacob 2 ,
• Janina Beckmann 3 &
• Joachim G. Piepenburg 1 , 4  

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In this study, we examine gender inequalities in educational decision-making. Specifically, we consider high school students selecting a higher education study programme and examine gender-specific risk and return preferences regarding monetary returns and the risk of failure in the programme. Moreover, we assess whether a counselling intervention can mitigate these gender inequalities. We employ a research design that combines a factorial survey and a field experiment to test our hypotheses. Consistent with our theoretical expectations, the results of the factorial survey confirm that girls are disproportionally deterred by the higher failure rates of possible study programmes, whereas boys are attracted more strongly by higher expected returns after graduation. Overall, the counselling intervention reduces the dissuasive effect of higher failure rates. Contrary to our expectations, the moderating effect is not stronger for girls but (if at all) is stronger for boys.

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Introduction

Gender differences in the choice of major occur in almost all industrialized countries (Barone, 2011 ). One frequently observed pattern is the overrepresentation of women in fields such as humanities and pedagogics, whereas men are overrepresented in science, technology, engineering and mathematics, with the proportion of one gender reaching more than 90% in some study programmes (Destatis, 2019 ; Liu & Zuo, 2019 ). These gender inequalities in the choice of major have consequences that transcend the educational system itself, as educational choices are important determinants of future employment and earnings (Gerber & Cheung, 2008 ; Horowitz, 2018 ; Jacob & Klein, 2019 ; Smyth, 2005 ). Consequently, a large body of literature on higher education has investigated the link between gender and field of study intention and choice (Bieri et al., 2016 ; Jonsson, 1999 ; Mann & Diprete, 2013 ; Morgan et al., 2013 ; Ochsenfeld, 2016 ; Reimer & Steinmetz, 2009 ; Silander et al., 2022 ; Xie et al., 2015 ), as well as the degree to which interventions can mitigate these gender differences (Barone et al., 2019 ; Finger et al., 2020 ; Scheeren et al., 2018 ).

This paper adds to this discussion in two ways. First, we build on psychological research that consistently documents gendered differences in risk aversion and return preferences (Niederle & Vesterlund, 2007 ; Niederle & Vesterlund, 2011 ; Paola & Gioia, 2012 ; Sutter et al., 2016 ; Sutter & Glätzle-Rützler, 2014 ) and argue that these differences may partly explain gendered differences in higher education choices. This argument is motivated by descriptive evidence showing a strong correlation between the risk–return profile of a certain study programme and the proportion of men to women in the programme. Study programmes with a high share of male students, such as engineering or computer science, offer the most favourable employment prospects after graduation but are also characterized by very high failure rates, while study programmes with a high share of female students often show the exact opposite pattern (for data on Germany, see Neugebauer et al., 2019 ).

Second, we assess whether the role of risk and return preferences permits policy interventions to mitigate gender differences. If a high (perceived) risk of failure deters female students from pursuing study programmes that yield higher employment prospects, counselling that strengthens self-confidence and fosters problem-solving skills for study-related difficulties could increase enrolment in these types of study programmes, thus reducing gender disparities in the choice of major. As girls tend to underestimate their skills, particularly regarding ambitious educational paths, counselling could indirectly mitigate gender differences by correcting these gender-biased ability beliefs, which have been documented by several studies (Marshman et al., 2018 ; mathematics, Perez-Felkner et al., 2017 ).

Methodologically, neither question is trivial to answer. First, study programmes differ in many respects beyond their risk–return profiles. Therefore, the observed correlation between risk–return profile and the share of male and female students may be spurious. Second, drawing causal inferences on the moderating effects of counselling may be complicated by endogenous self-selection into counselling programmes, which undermines the comparability between participants and non-participants (Imbens & Rubin, 2015 ). Therefore, we conducted a survey experiment (factorial survey) embedded in a field experiment. In the first step, we recruited high school students and divided them into treatment and control group. The treatment group was invited to participate in a counselling workshop, while the control group was compensated through participation in a prize draw. In the second step, we conducted a factorial survey a few months after the workshop and prize draw. We asked participants to rate the attractiveness of study programmes, experimentally varying the failure rates and expected income after graduation while holding all other parameters constant. This research design enabled us to assess whether risk–return profiles exert different influences on boys versus girls and identify the possible mitigating role of the counselling workshop.

Theory and related work

Risk, return and the role of counselling.

Rational choice theory suggests that individuals will select the educational pathways promising the highest utility. Two major determinants of utility are the (perceived) benefits of a certain choice ( return ) and the probability of success ( risk ) .  Individuals will, therefore, opt for an educational pathway that maximizes utility by offering the most favourable risk–benefit ratio (Breen et al., 2014 ; Breen & Goldthorpe, 1997 ; Gabay-Egozi et al., 2010 ; Tutić, 2017 ). Building on and extending this framework, we argue that individual utility depends not only on objectively measured risk and returns but also on individual risk and return preferences. For example, risk-averse individuals are more likely to refrain from pursuing challenging educational paths (such as those with high failure rates), even with accurate information. As laboratory experiments in economics and psychology indicate substantially higher risk aversion among women (e.g. Niederle & Vesterlund, 2007 ), women may be more strongly deterred by fields of study that present a higher risk of failure. Similarly, men could be disproportionately attracted by higher returns as they tend to emphasize income and career (Busch-Heizmann, 2015 ; Jurczyk et al., 2019 ; Wolter et al., 2019 ).

This raises the role of counselling. We suggest that interventions could (indirectly) mitigate perceived risks by fostering students’ confidence in their abilities and discussing problem-solving strategies to address study-related difficulties. This could lower the perceived risk of failure in a certain study programme, thereby mitigating the deterring effect of higher failure rates and encouraging riskier and, possibly, more rewarding choices (we provide a detailed description of the content of the intervention in the “ The intervention ” section). While interventions to lower perceived risk could be expected to increase the probability of making risky choices for both boys and girls, there are reasons to expect that the effect will be larger for girls. First, as girls display lower average levels of risk affinity than boys, they may profit more from counselling due to ceiling effects at the top of the risk-affinity distribution. Second, girls might be more responsive to feedback regarding their risk evaluations, irrespective of their starting level, because they generally underestimate their competencies in various ambitious study programmes, such as those in STEM fields, compared to boys (see, e.g. physics, Marshman et al., 2018 ; mathematics, Perez-Felkner et al., 2017 ), leaving more room to correct their downward-biased risk perceptions. Therefore, boys and girls are expected to become more similar in their subjective evaluations of a given choice, which would contribute to less gendered choices of major. In this study, we focus on risk, as our counselling approach targets risk preferences and perceptions rather than return preferences. In sum, we hypothesize that:

(H1) Girls are more strongly guided by risk attributes while boys emphasize return characteristics when making educational choices.

(H2) Participation in counselling interventions mitigates the negative impact of higher risk on individual utility.

(H3) The effect of a counselling intervention on taking riskier choices will be stronger for girls.

Related work

At a general level, this paper contributes to several fields, including gender inequalities in higher education (Buchmann et al., 2008 ; Cech et al., 2011 ; Herd et al., 2019 ; Mann & Diprete, 2013 ; Morgan et al., 2013 ; Schwerter & Ilg, 2021 ), as well as the role of risk and return preferences or personality traits for study and career choices (Breen et al., 2014 ; Buser et al., 2014 ; Chen & Simpson, 2015 ; Daniel & Watermann, 2018 ; Finger, 2016 ; Sanabria & Penner, 2017 ; Sax et al., 2017 ). More specifically, we add to the policy-oriented literature that assesses the effects of interventions on gendered differences in higher education choices. Previous research in this field has mostly provided short info-treatments on actual risks and returns, seeking to correct social or gender-specific misperceptions about the risks and returns of certain educational pathways (Barone et al., 2016 , 2019 ; Bleemer & Zafar, 2018 ; Callender & Melis, 2022 ; Ehlert et al., 2017 ; Evans & Boatman, 2018 ; Finger et al., 2020 ; French & Oreopoulos, 2017 ; Herbaut & Geven, 2020 ; Ruder & van Noy, 2017 ). While these interventions appear to reduce social inequalities with respect to socioeconomic background (for a review, see French & Oreopoulos, 2017 ), there is no evidence that they reduce gender inequalities. If at all, the effect appears to be stronger for boys. One reason for this finding could be that perceptions of actual risk and returns do not differ between genders, even without counselling workshops (as Barone et al., 2019 , reported). Consequently, the approach of correcting gender-specific concepts may be of limited utility. At the same time, our theoretical reasoning suggests that men and women may differ more strongly in their risk and return preferences rather than their knowledge of actual risks and returns. Therefore, we extend the previous research by analysing the impact of an intervention that (indirectly) targets the perceived risk of failure.

Research design

Essentially, our research design combines a survey and field experiment. The field experiment consists of a counselling workshop, with participants randomly assigned into treatment and control group (randomized controlled trial, RCT), while the survey experiment consists of a factorial survey conducted after the counselling workshops. For the RCT, we recruit high school students from the area surrounding two large German cities who are between 6 and 18 months from graduating high school (i.e. attaining the German higher education entrance diploma, Abitur ). During recruitment, we point out that participation would consist of multiple online surveys with monetary compensation (10 euros each). Moreover, we indicate that a randomly allocated subset of study participants would be invited to participate in a university guidance and counselling workshop offered by the Department for Student Services. Those who were not offered the workshop would take part in a raffle where five prizes of 100 euros could be won in addition to the monetary compensation for the surveys. The recruiting strategy for our study was similar to the approach typically employed for such workshops, e.g. providing flyers to high school students or contacting schools to relay information on guidance workshops to their students. Therefore, the resulting sample closely mirrors the target group that would usually participate in such interventions.

After registering for the study, participants complete an online questionnaire (first wave of the survey) that mostly consists of pre-treatment covariates. At the end of the first survey, participants are randomly assigned to either the treatment or control group, and only members of the treatment group were offered places in a 1-day workshop. Between 3 and 6 months after the end of the first survey, participants are invited to complete a second online survey, which contains a survey experiment assessing the importance of risk and return characteristics for study programme choice (see Fig.  1 ). This setup enables us to analyse whether the importance of risk and return varies between genders, whether participation in the workshops has a moderating effect on the importance of risk, and whether this moderating effect is stronger for girls. We summarize the research design in Fig.  1 and outline its components in more detail in the following sections.

Visualization of research design

The intervention

The intervention consists of a 1-day counselling workshop and takes place between the two survey waves. The workshop was conducted by professional counsellors from two universities and consists of two modules offering general information as well as psychological counselling. First, students complete three exercises designed to increase their awareness of their cognitive abilities, occupational interests and personal values. For example, they receive individual feedback on a self-assessment of their cognitive abilities that they completed before the workshop. These exercises constituted the basis of the discussion about suitable majors for the students. Second, students receive general information about study opportunities, such as the differences between universities and universities of applied sciences or access to reliable sources of information. More importantly in our context, the third part of the workshop consists of psychological counselling dedicated to strategies and resources for handling problems in possible study programmes; this stage includes an already enrolled student. The student provided examples of their experiences along with the difficulties they encountered during the study programme and described strategies to handle those issues. Additional individual exercises and group work encouraged participants to think about how to handle difficulties by discussing their past experiences and future applications. The general notion conveyed by the intervention is that while studying may present several challenges and demands, students should not be deterred from pursuing their preferred study programmes, as resources and problem-solving strategies are available to help overcome difficulties. The workshop did not target a specific study programme but emphasized that participants should choose based on their preferences.

Consequently, workshop participation can alleviate the deterrent effect of a higher average failure rate because participants become aware of the resources and strategies available to them in case of difficulties. In addition, they will have encountered an experienced student who has overcome difficulties encountered during their studies, increasing the credibility of the information they receive.

The factorial survey

The factorial survey was conducted in the second survey wave, after the intervention. It was designed to vary the risk–return pattern of potential study programmes while keeping all other factors fixed. This allows us to disentangle the impact of risk and return characteristics on the attractiveness of a certain choice from possible confounders. To increase the robustness of our findings, we ask two types of questions to observe participants’ risk and return preferences. We use a factorial survey offering different vignettes of risk and return profiles and asking participants to rate the different programmes, as well as a choice question that asks participants to decide between specific study programmes. We adopt these two approaches to confirm whether our results could be sensitive to different survey designs.

In the vignette study, we present participants with the following scenario and ask the following question:

"Imagine that you already know which major you wish to study. The major is offered at three universities nearby. The study programs differ with respect to dropout rates and expected income after graduation. Assume you can study your preferred study program at University (A/ B/ C). The average income after graduation is (32,000 / 43,000 / 54,000€), the failure rate is (22 / 31 / 40%). On a scale from 0 to 10, how likely will you apply for this study program?"

By stating that the participants can study their preferred major at some university not further specified, we reassure that systematic variations in programme attractiveness reflect only the differences in risk and return outlined in the description of the study programme. This, therefore, fulfils our goal of creating exogenous variation in the risk–return pattern of a certain study programme that is not confounded by other characteristics, such as gender-specific vocational interests. Importantly, the experiment is also not confounded by the participants’ actual study intentions because the experimental design rules out factors such as students with more ambitious study intentions or different return preferences receiving higher values in their vignettes. While the effects may vary between students depending on their study intentions, the estimation of the average effect across the sample remains unaffected. At the same time, the intervention may affect study intentions; therefore, participants from the treatment group might have a slightly different set of study programmes in mind. However, the analysis relies on within-respondent variation (the fixed-effects analyses exclusively assess within-respondent variation), implying that survey participants have the same major in mind when responding to the vignettes.

Every participant responded to three vignettes. As Table  1 shows, we use three levels for the two dimensions, “risk” and “return”, generating a vignette universe of nine. We follow an algorithm suggested by Nguyen ( 2001 ) to assign the vignettes to three blocks. The exact blocking used in this study is presented in Table A.5 . Each participant is randomly assigned to one block. As we are particularly interested in the interaction between the vignette dimensions and individual-level variables (treatment status and gender), we could limit the vignette dimensions to two options with three levels each.

As a second measure of participants’ risk and return preferences, we asked participants a simple choice question:

“Assume you can study your preferred study program at University A and University B. At University A, the failure rate is 27%, the average income after completion is 34,000€. At University B, the failure rate is 39%, the average income after completion 47,000€.”

Which option do you prefer?

The choice question also fulfils our main purpose of creating exogenous variation in the risk–return profile. Varying risk and return simultaneously prevents the disentangling of the dimensions and tests them jointly. As this question focuses on both dimensions simultaneously, it is less relevant to the analysis of the treatment, which was not intended to affect return preferences. Nevertheless, the choice question is a reasonable method to assess the role of gender in choosing high-risk high-return vs. low-risk low-return programmes.

Data and variables

Our approaches produce different data structures. The vignette study produces a clustered dataset with vignettes clustered by person, with each observation including the corresponding rating and vignette variables (risk/return). The choice question results in a cross-section dataset including a variable of choosing University A or B (covariates are measured before the start of the treatment, and the survey experiment was conducted afterwards. As most of the covariates measured before the treatment are time-invariant, we are de facto dealing with a cross-section dataset including a variable of choosing University A or B). Both datasets contain an exogenous treatment indicator, an indicator for actual treatment status (not identical due to non-compliance) and the covariates measured in survey wave one, i.e. before participation in the counselling workshop. These include participants’ age in months, gender, school grade in maths and German and parents’ educational background (a dummy variable indicating whether both parents hold university degrees). Moreover, we coded two dummy variables for household composition (living with both parents and having siblings) and the share of schoolmates who planned to enter university. Finally, we included an indicator for the self-reported start of gathering information on study opportunities. As this is an experiment, controlling for confounders is less relevant for the treatment effect estimations, but it may be helpful to assess how sensitive the gender effect is to the inclusion of covariates.

In total, 725 high school students registered for our study and completed the initial survey before being assigned to experimental groups. Of those, 608 students participated in the second wave, which is a response rate of more than 80%. Panel attrition was strongly reduced by inviting participants via e-mail, text message and up to 20 telephone calls. The remaining panel attrition was mostly limited to participants with invalid phone numbers or who never answered the phone. Data cleaning (e.g. due to missing information on important covariates) reduced the sample to 580 cases. Due to randomization, no selection bias towards treatment (i.e. covariate imbalance) is apparent. A summary of the participants’ descriptive statistics is provided in Table A.1 . The two most remarkable findings are a strong overrepresentation of girls (about 75%) and, on average, a certain preference for high-risk high-return choices (also about 75%). The overrepresentation of girls is consistent with experiences from similar workshops, reinforcing that we are utilizing a sample that is similar to the real-world conditions of such workshops but not representative of all students. Moreover, we must account for two-sided non-compliance in the estimations (see the “ Estimation, inference and robustness checks ” section), although the compliance rates are rather high (almost 80% in the treatment group and more than 95% in the control group).

Estimation, inference and robustness checks

We made our estimates in two steps. First, we relied on the experimental vignette study and the choice question to describe gendered differences in risk and return preferences. In the second step, we jointly considered the results from the survey and the field experiment to assess the counselling workshop’s potential to reduce the impact of risk preferences on students’ study programme choices. This allows our estimation strategy to account for the peculiarities of the two experiments’ respective data structures.

Gender and risk/return

To analyse gendered differences in risk–return preferences, we start by analysing the data from the vignette study. To do so, we run random effects multilevel regressions to account for the nested data structure of ratings on vignette variables (risk/return) and covariates. To assess the differences in the importance of risk/return between genders, we additionally insert cross-level interaction terms between gender and risk/return.

As stated in the previous section, we confirmed the robustness of our approach with the choice question. Due to the cross-sectional data structure, we simply regressed the dummy variable indicating the high-risk high-return option on gender using linear probability models (LPM) with robust standard errors. To assess the sensitivity of the effect of gender, we run additional regressions with different sets of control variables.

The moderating role of the counselling workshop

In the second part of the analysis, we focus on the moderating role that treatment participation plays in students’ risk preferences. To do so, we focus on the factorial survey, as the workshop is expected to affect risk preferences but not return preferences. Therefore, we do not expect an impact on the binary choice question, although we briefly report the results of that analysis as well. Generally speaking, the approach for analysing the moderating role is very similar to the first part, except we exchange the risk/return × gender interaction for the risk × treatment interaction (see Eq.  2 ).

Here, we have to address an endogeneity issue caused by two-sided non-compliance; that is, a certain proportion of the invited participants did not attend the workshop (about 20% of those who were assigned to the treatment group), while ten participants who were assigned to the control group achieved placement in the workshops by registering for the study multiple times (non-compliance rate 3%). Excluding these participants completely would have biased the results, as (apparently) particularly motivated participants from the control group would have been excluded, generating a correlation between treatment assignment and unobserved confounders (per protocol analysis; Imbens & Rubin, 2015 ). However, actual treatment status is not randomized anymore and therefore possibly endogenous. Therefore, we use treatment assignment and the treatment assignment × risk interaction as instruments for actual treatment status and the treatment status × risk interaction, and estimate Eq.  2 by generalized least squares instrumental variable (GLS-IV) estimation (Imbens & Rubin, 2015 ). We estimated this equation for the whole sample as well as for both genders separately to analyse gendered differences in the moderating role of the treatment.

Robustness checks

To further substantiate the robustness of our results, we conduct two additional robustness checks. First, we conduct an intent-to-treat (ITT) analysis instead of our IV approach. This involves estimating the moderating effect of treatment assignment rather than actual treatment status to circumvent the problem of non-compliance. Second, we replace the GLS-IV regressions with FE-IV regressions to re-confirm the reliability of our research design.

Most importantly, we check whether endogenous panel attrition induces a correlation between treatment assignment and confounders among participants who participated in the second survey wave. To this end, we first run a selection regression (among all participants from wave 1) of participation in wave 2 on treatment assignment on all covariates. To further confirm whether attrition leads to covariate imbalance, we conduct a multivariate balancing test among second-wave participants by regressing treatment assignment on all covariates. Finally, we include a full set of treatment × covariate interactions in the selection regression to explicitly test for different selection patterns between groups.

Results and discussion

Risk, return and gender.

We start by presenting the first part of our analysis, the description of gendered differences in risk and return preferences. First, we look at descriptive statistics on the relationship between the vignette dimensions and the outcome. As Fig.  2 shows, the relationship follows the expected pattern. The left panel shows a decreasing average rating for higher failure rates. Similarly, the average rating strongly increases for higher expected income.

Descriptive results for the relation of vignette variables and the outcome

We proceed with the results of the regression analyses. Table  2 summarizes the results of the factorial survey. Models 1 and 2 present regressions on the rating of the vignette variables with (Model 2) and without (Model 1) covariates, while Model 3 includes the interaction terms. In all models, the vignette variables enter as dummy variables with the lowest category as the reference category.

Models 1 and 2 confirm that the effect of the vignette variables is significant at the 1% level. Theoretically speaking, the most interesting results are those from the interaction terms model. To facilitate interpretation, we present the coefficients in Fig.  3 .

Visualization of gender × vignette interactions. The corresponding regression is displayed in Table  2 , model 3

The displayed coefficients show the estimated effect of moving from the lowest to the medium or highest category separately for both genders. For both dimensions, the observed gender differences are consistent with our theoretical expectations but differ in magnitude as well as statistical significance. As the left panel shows, boys and girls assign (ceteris paribus) lower ratings to study programmes with higher failure rates, but not to the same degree. While there is no difference in the medium category, the difference in the highest category confirms that girls react more strongly than boys to higher failure rates. The point estimates (see Table  2 ) imply a negative effect for boys of − 1.3, whereas the effect for girls is − 1.7. This amounts to a relative difference of about 30%, meaning the negative effect is 30% stronger for girls than boys. The interaction effect barely misses statistical significance ( t -value, − 1.49). The opposite picture is revealed for returns, as shown in the right panel. Once again, both genders assign higher ratings to study programmes with higher expected income, with larger gender differences in the highest category. The positive effect of going from the lowest to the highest category is 4.4 for boys, but only 3.4 for girls, which means that the effect is, again, about 30% greater for boys. While the gender difference revealed here is comparable to that for risk, the estimated difference is significant at the 1% level. Altogether, these results confirm the hypotheses that girls are deterred more strongly by higher failure rates, whereas boys are disproportionately attracted by higher income potential in their selection of specific study programmes.

To reaffirm the robustness of our results, we proceed with the results from the LPMs that regress the choice of the high-risk high-return option on gender plus different sets of covariates. The results are shown in Table  3 . The coefficient of female expresses the difference in the probability of choosing the high-risk high-return option, compared to boys, in percentage points. In all models, the effect is significant at the 1% level and the effect size ranges between 12 and 15% points. Notably, the effect does not consistently diminish when covariates are included, suggesting that gender differences are not driven by omitted (unobservable) variables. As expected, treatment status does not affect the chosen programme as it constitutes a combined risk and return measure and there is no theoretical reason to believe that the treatment affects return preferences. Taken together, both parts of our experiment confirm our first hypothesis, that risk and return preferences vary along gender lines and may play an important role in students’ choice of major.

The moderating effect of the treatment

We now examine whether the counselling intervention can mitigate the dissuasive effect of higher failure rates among high school students in general and girls in particular. We proceed by presenting the results from the risk-treatment interactions as outlined in Eq. ( 2 ). Table  4 displays the results for the entire sample (Model 1) as well as boys alone (Model 2) and girls alone (Model 3). We display the coefficients of the interaction term for Model 1, including both genders, in Fig.  4 .

Mitigating role of counselling for the effect of risk aversion on rating (whole sample). Corresponding regression is given in Table  4 (model 1)

Participation in the counselling workshop appears to considerably mitigate the negative effect of higher failure rates, especially in the medium category. The negative risk effect of − 0.83 shrinks to − 0.29 with treatment participation, implying that the deterrent effect decreases to almost one-third of its original size (significant at the 10% level). This confirms our second hypothesis that the counselling workshop made participants less sensitive to higher failure rates for medium- vs. low-risk options. When interpreting the moderator, it should be noted that its maximum positive effect is limited by design, as higher failure rates can (ceteris paribus) rarely be regarded as positive. This demonstrates the volume of the estimated decrease.

We further display the coefficients from the regressions for both genders separately in Fig.  5 . As the left (girls) and right (boys) panels indicate, the intervention alleviated the negative effect of higher failure rates for both genders, once again especially in the medium category. However, the difference between the two groups belies our theoretical expectations. Contrary to our hypothesis, the difference in point estimates between the treatment and control groups is larger for boys for both risk categories. For example, for girls without treatment, the rating of a study programme decreases by 1.796 scale points when the risk increases from the lowest to the highest category. This deterrent effect slightly decreases to − 1.660 with treatment. In contrast, for boys, the deterrent effect decreases from 1.637 in the control group to 0.824 in the treatment group. This corresponds to a decrease of 0.28 standard deviations (SD = 2.91) for boys compared to a decrease of 0.05 standard deviations for girls (SD = 2.74). While this difference is non-negligible, it does not reach statistical significance due to the small number of cases in each subgroup and the overall small number of male students in our sample. It remains subject to future research whether significant differences can be found in larger samples.

Moderating effect of treatment, separately by gender. Corresponding regressions are displayed in Table  4 (model 2 and 3)

Our robustness checks (ITT analysis and FE estimations, summarized in Tables A.2 and A.3) show that methodological choices play a minor role in our results. While the FE estimates rarely diverge from the results presented in this section, the ITT analyses vary in the expected way as the coefficients are smaller, although the significance levels are more or less unchanged. Moreover, panel attrition does not seem to induce confounding. While response rates are slightly higher in the treatment group (though not significant at the 5% level; Table A.4 , Model 1), a multivariate check on covariate imbalance among individuals who participated in the second survey wave shows that none of the covariates is related to treatment assignment (Model 2; the p -value of joint significance is 0.87). This is substantiated by selection regressions including interaction terms (Models 3 and 4), which show that the treatment and control groups follow very similar selection patterns. In sum, this implies that while we observed panel attrition, it did not induce confounding and does not, therefore, indicate biased treatment effect estimates. Unobserved confounding cannot be ruled out completely, but this seems unlikely in light of the results concerning the observed covariates.

Discussion and conclusion

This paper been inspired by consistent gendered differences in the choice of major in higher education, as well as previous research into interventions to mitigate these differences. We focused on seeking a theoretical explanation for gendered differences that would highlight the role of risk/return preferences. Subsequently, we have assessed the moderating impact of an intervention that does not focus on providing objective information about risks and returns but instead aims to strengthen students’ self-confidence in their abilities to mitigate the deterrent effect of higher failure rates. To answer these research questions, we employed a survey experiment combined with a field experiment.

Our results partly confirm and partly subvert our theoretical expectations. On one hand, female participants are indeed disproportionately deterred by higher failure rates, whereas male participants are disproportionately attracted by higher returns. Moreover, participation in the counselling workshop mitigate the deterrent effect of higher failure rates. On the other hand, and contrary to our expectations, the mitigating effect of the workshop is not stronger for girls, but, if at all, stronger for boys (but these differences are not statistically significant).

These results inform higher education research and indicate new directions for future research in three ways. First, and at the most abstract level, our results confirm the general notion outlined in rational choice approaches that utility considerations matter for educational choices. Moreover, the apparent gendered differences reveal that the evaluation of options depends heavily on the subjective evaluation of their risk–return patterns, implying that individual risk–return preferences matter even in cases of perfect information.

Second, our results add to the understanding of gender inequalities in educational decision-making in general, and particularly in higher education. As outlined in the introduction, the correlation between risk–return patterns and the proportion of male to female students in college majors is quite apparent at the aggregate level. However, causal claims about this relationship are hampered because the relevant study programmes differ in numerous other ways that may confound the relationship between risk–return patterns and student gender proportions. Our survey experiment, therefore, substantiates the argument that risk/return preferences might drive this relationship.

Finally, our results show that the importance of perceived risk and returns could be exploited by interventions designed to support students’ decisions. However, the results from the gender-specific analyses counter our theoretical expectations, as the counselling intervention exerted a stronger effect on boys than girls. There are multiple explanations for this unexpected result. On one hand, this may have resulted from a classical Matthew effect, in which people at the higher rather than the lower end of the risk-affinity distribution are pushed further upwards even heavier. On the other hand, these results also raise the question of whether we still lack a sufficient understanding of the mechanisms behind gender differences, as well as the heterogeneous effects of educational interventions on both genders. This argument is reinforced by the fact that we are not the first to observe effect heterogeneity that favours boys when stronger effects on girls were expected. For example, see other researchers’ results on the provision of objective information about risk and returns (Barone et al., 2019 ; Finger et al., 2020 ; Peters et al. 2023 ), curricular demands (Görlitz & Gravert, 2018 ; Jacob et al., 2020 ) or gendered responses to failure in “weed out courses” (Sanabria & Penner, 2017 ). In this regard, pursuing a deeper understanding of the gender-specific mechanisms of study choice, as well as the effect of educational interventions, should remain an important part of the higher education research agenda.

Despite its contributions to the field, our research design is not without limitations. First, offering the counselling workshop under real conditions is both an advantage and a disadvantage, as the findings concerning the importance of risk–return preferences do not necessarily generalize to the population of all students but rather to those who participate in similar interventions. (For further considerations of participation rates, see Pietrzyk & Erdmann, 2020 .) This reaffirms the external validity of the policy conclusions drawn concerning the moderating effect of the intervention. Moreover, our results align with existing research into gendered differences in risk and return preferences that relied on representative samples (Sanabria & Penner, 2017 ), suggesting that the observed differences in risk–return preferences are not merely due to sample selection. Second, we investigated intended rather than actual study choice. While the results presented by Buser et al. ( 2014 ) imply that intended choice may translate into actual study choice, future research must determine whether similar interventions actually lead to different study choices. Third, and relatedly, as we wanted students to evaluate different study programmes for their preferred major, it remains to be seen whether students would change their preferred major if their risk and return preferences changed. While we asked students to compare the same majors at different universities, it seems reasonable to assume that the effect would translate to comparisons of different majors. Finally, the notion of encouraging students to engage in more challenging and rewarding educational paths is often regarded positively in education research (Lent et al., 2018 ) as it may guide pupils to pursue study choices based on interest rather than anxiety. However, this does not guarantee their mastery of the resulting challenges. Therefore, future research should investigate whether the possible effect on study choice correlates with higher success and satisfaction during tertiary education.

In sum, our results reinforce the importance of both actual risk–return patterns and subjective perceptions, while also highlighting potential avenues for future research regarding long-term consequences and possible policy options.

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Open Access funding enabled and organized by Projekt DEAL. This research received funding from the BMBF (Bundesministerium für Bildung und Forschung) Funding Priority—“Academic success and dropout phenomena” (funding code (FKZ): 01PX16004).

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Fervers, L., Jacob, M., Beckmann, J. et al. Risk–return preferences, gender inequalities and the moderating role of a counselling intervention on choice of major: evidence from a field and survey experiment. High Educ (2024). https://doi.org/10.1007/s10734-024-01237-7

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Published : 14 May 2024

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TOP 100 Gender Equality Essay Topics

Table of Contents

Need ideas for argumentative essay on gender inequality? We’ve got a bunch!

… But let’s start off with a brief intro.

What is gender equality?

Equality between the sexes is a huge part of basic human rights. It means that men and women have the same opportunities to fulfil their potential in all spheres of life.

Today, we still face inequality issues as there is a persistent gap in access to opportunities for men and women.

Women have less access to decision-making and higher education. They constantly face obstacles at the workplace and have greater safety risks. Maintaining equal rights for both sexes is critical for meeting a wide range of goals in global development.

Inequality between the sexes is an interesting area to study so high school, college, and university students are often assigned to write essays on gender topics.

In this article, we are going to discuss the key peculiarities of gender equality essay. Besides, we have created a list of the best essay topic ideas.

What is the specifics of gender equality essay?

Equality and inequality between the sexes are important historical and current social issues which impact the way students and their families live. They are common topics for college papers in psychology, sociology, gender studies.

When writing an essay on equality between the sexes, you need to argue for a strong point of view and support your argument with relevant evidence gathered from multiple sources.

But first, you’d need to choose a good topic which is neither too broad nor too narrow to research.

Research is crucial for the success of your essay because you should develop a strong argument based on an in-depth study of various scholarly sources.

Equality between sexes is a complex problem. You have to consider different aspects and controversial points of view on specific issues, show your ability to think critically, develop a strong thesis statement, and build a logical argument, which can make a great impression on your audience.

If you are looking for interesting gender equality essay topics, here you will find a great list of 100 topic ideas for writing essays and research papers on gender issues in contemporary society.

Should you find that some topics are too broad, feel free to narrow them down.

Powerful gender equality essay topics

Here are the top 25 hottest topics for your argumentative opinion paper on gender issues.

Whether you are searching for original creative ideas for gender equality in sports essay or need inspiration for gender equality in education essay, we’ve got you covered.

Use imagination and creativity to demonstrate your approach.

• Analyze gender-based violence in different countries
• Compare wage gap between the sexes in different countries
• Explain the purpose of gender mainstreaming
• Implications of sex differences in the human brain
• How can we teach boys and girls that they have equal rights?
• Discuss gender-neutral management practices
• Promotion of equal opportunities for men and women in sports
• What does it mean to be transgender?
• Discuss the empowerment of women
• Why is gender-blindness a problem for women?
• Why are girls at greater risk of sexual violence and exploitation?
• Women as victims of human trafficking
• Analyze the glass ceiling in management
• Impact of ideology in determining relations between sexes
• Obstacles that prevent girls from getting quality education in African countries
• Why are so few women in STEM?
• Major challenges women face at the workplace
• How do women in sport fight for equality?
• Women, sports, and media institutions
• Contribution of women in the development of the world economy
• Role of gender diversity in innovation and scientific discovery
• What can be done to make cities safer for women and girls?
• International trends in women’s empowerment
• Role of schools in teaching children behaviours considered appropriate for their sex
• Feminism on social relations uniting women and men as groups

Gender roles essay topics

We can measure the equality of men and women by looking at how both sexes are represented in a range of different roles. You don’t have to do extensive and tiresome research to come up with gender roles essay topics, as we have already done it for you.

Have a look at this short list of top-notch topic ideas .

• Are paternity and maternity leaves equally important for babies?
• Imagine women-dominated society and describe it
• Sex roles in contemporary western societies
• Compare theories of gender development
• Adoption of sex-role stereotyped behaviours
• What steps should be taken to achieve gender-parity in parenting?
• What is gender identity?
• Emotional differences between men and women
• Issues modern feminism faces
• Sexual orientation and gender identity
• Benefits of investing in girls’ education
• Patriarchal attitudes and stereotypes in family relationships
• Toys and games of girls and boys
• Roles of men and women in politics
• Compare career opportunities for both sexes in the military
• Women in the US military
• Academic careers and sex equity
• Should men play larger roles in childcare?
• Impact of an ageing population on women’s economic welfare
• Historical determinants of contemporary differences in sex roles
• Gender-related issues in gaming
• Culture and sex-role stereotypes in advertisements
• What are feminine traits?
• Sex role theory in sociology
• Causes of sex differences and similarities in behaviour

Gender inequality research paper topics

Examples of inequality can be found in the everyday life of different women in many countries across the globe. Our gender inequality research paper topics are devoted to different issues that display discrimination of women throughout the world.

Choose any topic you like, research it, brainstorm ideas, and create a detailed gender inequality essay outline before you start working on your first draft.

Start off with making a debatable thesis, then write an engaging introduction, convincing main body, and strong conclusion for gender inequality essay .

• Aspects of sex discrimination
• Main indications of inequality between the sexes
• Causes of sex discrimination
• Inferior role of women in the relationships
• Sex differences in education
• Can education solve issues of inequality between the sexes?
• Impact of discrimination on early childhood development
• Why do women have limited professional opportunities in sports?
• Gender discrimination in sports
• Lack of women having leadership roles
• Inequality between the sexes in work-family balance
• Top factors that impact inequality at a workplace
• What can governments do to close the gender gap at work?
• Sex discrimination in human resource processes and practices
• Gender inequality in work organizations
• Factors causing inequality between men and women in developing countries
• Work-home conflict as a symptom of inequality between men and women
• Why are mothers less wealthy than women without children?
• Forms of sex discrimination in a contemporary society
• Sex discrimination in the classroom
• Justification of inequality in American history
• Origins of sex discrimination
• Motherhood and segregation in labour markets
• Sex discrimination in marriage
• Can technology reduce sex discrimination?

Most controversial gender topics

Need a good controversial topic for gender stereotypes essay? Here are some popular debatable topics concerning various gender problems people face nowadays.

They are discussed in scientific studies, newspaper articles, and social media posts. If you choose any of them, you will need to perform in-depth research to prepare an impressive piece of writing.

• How do gender misconceptions impact behaviour?
• Most common outdated sex-role stereotypes
• How does gay marriage influence straight marriage?
• Explain the role of sexuality in sex-role stereotyping
• Role of media in breaking sex-role stereotypes
• Discuss the dual approach to equality between men and women
• Are women better than men or are they equal?
• Sex-role stereotypes at a workplace
• Racial variations in gender-related attitudes
• Role of feminism in creating the alternative culture for women
• Feminism and transgender theory
• Gender stereotypes in science and education
• Are sex roles important for society?
• Future of gender norms
• How can we make a better world for women?
• Are men the weaker sex?
• Beauty pageants and women’s empowerment
• Are women better communicators?
• What are the origins of sexual orientation?
• Should prostitution be legal?
• Pros and cons of being a feminist
• Advantages and disadvantages of being a woman
• Can movies defy gender stereotypes?
• Sexuality and politics

Feel free to use these powerful topic ideas for writing a good college-level gender equality essay or as a starting point for your study.

No time to do decent research and write your top-notch paper? No big deal! Choose any topic from our list and let a pro write the essay for you!

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143 Unique Gender Inequality Essay Titles & Examples

Here, you will find 85 thought-provoking topics relating to gender, equality, and discrimination. Browse through our list to find inspiration for your paper – and don’t forget to read the gender inequality essay samples written by other students.

👩 Top 10 Gender Equality Title Ideas

🏆 best gender bias essay topics, 💡 interesting topics to write about gender inequality, 📌 simple & easy gender inequality essay titles, 👍 good gender equality research title ideas, ❓ gender inequality research questions.

• Globalization, gender, and development.
• The Pink Tax.
• Women and unpaid labor.
• Gender stereotypes in media.
• Emma Watson’s speech on gender equality.
• A critique of HeForShe campaign.
• Education for girls in Ghana.
• The suffrage movement.
• Crimes against girls and women.
• Female empowerment in STEM fields.
• Gender Inequality in the Field of Working Wright and Yaeger state that it is the deep intersection of the life and work fields in the current working paradigm that creates daily and long-term problems, limits the available time for male and female […]
• Gender Inequality in the Story of Ama Aidoo “In the Cutting of a Drink” The story of Ama Aidoo In the Cutting of a Drink tells about gender inequality, which is expressed in the clash between the typical values of rural residents and the values of people living in […]
• Gender Inequality: The Role of Media The media plays a major role in gender socialization because of the ways it chooses to portray women. Shows such as Beauty and the Beast, Cinderella, and Snow White are famous because they usher children […]
• Gender Inequality as a Global Issue This essay will examine some of the causes that affect the gap in the treatment of men and women, and its ramifications, particularly regarding developing countries.
• Sociological perspectives of Gender Inequality The events taking place in the modern world and the occurrence of the feminist movements during the past few decades can be used to offer a deeper understanding on the subject of gender inequality and […]
• Women’s Rights and Gender Inequality in Saudi Arabia Indeed, it is crucial to understand the importance of women’s rights, see the connections between the past, the present, the local, and the global, and realize how political and media discourse represents the social issue […]
• Gender Inequality in Social Media Research shows that teenagers from the age of thirteen use social media to discuss the physical appearances of girls and exchange images with sexual content.
• Gender Inequality and Female Leaders in the Hospitality Industry The current literature regarding the challenges and issues facing women in leadership positions in the hospitality industry in France is inadequate.
• Femicide in Mexico and the Problem of Gender Inequality Femicide remains one of the most devastating issues in Mexico, and it is vital to address the gender oppression and inequality that women face.
• Gender Inequality: On the Influence of Culture and Religion Therefore, to understand more about the topic, it is essential to study the issues from various perspectives and find the connection of the discourse to other gender-related problems and theories.
• Gender Inequality, Violence Against Women, and Fear in The Sopranos Thus, the major research question will be “Does The Sopranos endorse or criticize VaW through the frequent depiction of the scenes of cruelty?” The hypothesis of the research paper will be “The portrayal of VaW […]
• How Gender Inequality Persists in the Modern World? According Ridgeway, it may not be correct per se to say that its only women who are aggrieved by the gender imbalance but majority of the cases that depict gender inequalities involve women on the […]
• Gender inequality in Canada According to, although it is certain that men and women have actual differences particularly physically, most of the social indifference perception are not because of the biological connotation but because of the over time cultural […]
• Social, Cultural and Gender Inequality From a Global Perspective It is the duty of the tutor to craft a lecture-room environment that serves to enhance meaningful discussions concerning gender. This is due to the fact that students learn best in various ways.
• Gender Inequality in the Video Games Industry The portrayal of males and females in video games is a subject of study in gender studies and is discussed in the context of sexism in the industry.
• Combating Gender Inequality It is thanks to this approach that humanity will be able to successfully cope with the problem of gender inequality, sexism, and discrimination.
• Gender Inequality as a Global Societal Problem For eliminating the gender wage gap, nationwide legislation shows to increase the hiring and promotion of women in the workplace. Unfortunately, there is a gap in scholarly research in regards to reflecting the success of […]
• Gender Inequality in Workplace Gender is the main reason for inequalities in the workplace; this is because nowadays there is a steady increase in the number of women in workplaces in the world.
• The Issue of Gender Inequality Reflection Unfortunately, in the opinion of many, inequality in their treatment is even more pronounced, forming a third group from such persons in addition to binary people and positioning them at the end of the list.
• Gender Inequality in Mass Media However, as a part of society, media organizations are influenced by the same social aspects and biased conclusions as the rest of the community. As a result, the owners and managers of media are mainly […]
• Gender Inequality in American Stories and Plays There are disputes about the sexual desire of men and women and how it is applied, and the use of physical strength of men on women.
• Gender Inequality and Female Empowerment Promotion Therefore, it is crucial to continue celebrating women’s accomplishments and encourage a positive change within the current perception of women as a social and biological class.
• Gender Inequality in Interdisciplinary Lenses Both sociologists and legal experts concur that a gender bias ingrained in society is the primary factor contributing to the issue of women in the workforce.
• Gender Inequality at Work in Developed Countries In France, the Netherlands, Spain, and Great Britain, men are disadvantaged throughout the employment process for professions where women predominate. These are the conclusions of a study conducted by the University of Amsterdam, the University […]
• Gender Inequality and Its Causes Analysis It is evident that the difference is so insignificant to the point where some women can be athletically stronger than men, and there is a vast difference in strength among men themselves.
• Gender Inequality and the Glass Ceiling The significant societal barriers that keep women from achieving the highest levels of their careers include, but are not limited to, organizational barriers, societal barriers, and Personal barriers.
• Human Objectification as a Tool of Gender Inequality Objectification and culture of suppressed emotions of the male gender lead to the further sexual objectification of the females resulting in unequal social positions.
• Gender Inequality in Media Representation The proportional presence of women and men in the news and current affairs will increasingly reflect the structure of society and demonstrate a more considerable diversity of human experience, attitudes, and concerns.
• The Issue of Gender Inequality After Covid-19 To date, the role of women in society has increased many times over, both in the economic, social, and political spheres of public life.
• Gender Inequality in the Construction Field It is important that the main actors in the sector understand that gender equality can help reduce the issue of shortage of skill that exists in that field.
• Social Enterprises and Gender Inequality in Dubai In the context of UAE demographics, the population of Dubai has been rightfully considered the most diverse in terms of age, income, and socio-ethnic background, as this city is a conglomerate for tourists, business visitors, […]
• Gender Inequality in Relation to the Military Service In his article, Soutik Biswas refers to the intention of India’s Supreme Court to influence the government and give women commanding roles in the army.
• The Relationship Between Gender Inequality and Women’s Economic Independence In a scenario where the wife is employed, either of the parents has the means of supporting themselves as well as other dependents, and this is the most remarkable benefit of emancipation.
• Gender Inequality and Its Implications on American Society It is not just the fight for the women’s rights, elimination of the gender pay gap or the harassment phenomenon. The voices of those who disagree with the fact that the resolution of one case […]
• Women From the Downtown Eastside: Gender Inequality One of the main questions that bother many people around the whole world is the identification of the conditions under which the citizens of the Downtown Eastside disappeared.
• Women Labour: Gender Inequality Issues Sexual category or gender is an ingredient of the wider socio-cultural framework that encompasses the societal attributes and opportunities connected with individual male and female and the conduit between women and men and girls and […]
• Issues Surrounding Gender Inequality in the Workplace The main objective of the constructionist point of view is that it is aimed at uncovering how the individuals and the groups tend to participate in the creation of their perceptions of gender and women […]
• Public Policy Analysis on Gender Inequality in Education in South Sudan The major challenges related to the development of the educational system are the ongoing violent attacks and natural disasters. The General Education Strategic Plan, 2017-2022 is the government’s response to the most burning issues in […]
• Race & Gender Inequality and Economic Empowerment This means that the study will analyze the problem of race and gender inequality and examine how it is related to poverty.
• Gender Inequality: “Caliban and the Witch” by Federici Federici shows the fall of female ability for autonomy and the rise of patriarchal societies as a result of an emerging emphasis on global trade and the perceived notion that the wealth of the country […]
• Gender Inequality and Health Disparities Thus, Wacquant not only mentions the problem of gender inequality but also stresses that this issue has a rather long history of development, which is rooted in the past.
• Gender Inequality Index 2013 in the Gulf Countries However, the ratio of women in the parliament is noticeably lower, and that explains why the GII of Kuwait is slightly higher than the one of the UEA.
• Gender Inequality: Reginald Murphy College To establish the accuracy of the allegations raised as a group, the factors to ensuring the retrieval of the correct information about the issue in question are the involvement of all members of the administration […]
• Gender Inequality at the China’s Workplaces Although researchers have quantified the extent of gender pay inequality in the workplace, they hold different opinions regarding the best strategies to use in addressing the problem.
• Gender Inequality and Its Historical Origin Seeing that the effects of the two factors are reciprocal, it can be assumed that, though both have had a tangible impact on the contemporary representation of women in the society, traditions have a significantly […]
• Gender Inequality in Family Business One of the problems that every woman faces in a family business is that of succession. In the model of Royal Families, the right to lead the business belongs to the oldest son.
• Gender Inequality in Europe, America, Asia, Africa The laws and customs of the countries located in Africa and the Middle East are shaped by many factors. Some of the laws in the Middle East are clearly unfair towards women.
• Women in the Workplace: Gender Inequality I examine the idea of work-and-life balance that is proposed as a solution to the problem of having a family and career at the same time and point out the fact that it is typically […]
• Indian Gender Inequality and Reduction Initiatives Coontz discusses these issues from the context of the economic status of American women and their limited role in society at the time.
• Bill Myers’ Leadership and Gender Inequality In this case, the bartenders, wait staff and the busboys all possess the required skills and knowledge for the job, and thus ought to be treated equally.
• Gender Inequality in the Labor Force The aim of this article is to assess the assertion that gender inequality exists in the labor force. The table below shows global adult employment-to-population by gender for 1998 and 2008.
• Gender Inequality in Afghanistan Thirdly, there is social gender inequality, which is demonstrated by women being the victims of domestic violence and sexual assault, inequalities in education attainment, lack of freedom to marry and divorce, and unequal access to […]
• Gender Inequality and Socio-Economic Development Gender inequality in the US determines who is to be in the kitchen and who is to sit in the White House.
• Gender Inequality in America This event highlighted the extent to which women were vulnerable to the prejudices of the society. This particular event is important because it lead to the exclusion of women from the political life of the […]
• Gender inequality in Algeria The fact that women helped to build back the ruins of society and the heroism they showed in the war efforts, was forgotten by their husbands and the government.
• Gender Inequality in the US Of more importance in the enhancement of gender inequality is the role of the media. The natural constrains described above and the multiplier effects from the historical insubordination of women still play to men’s favor […]
• Observations on the Gender Inequality This is the best way to preserve the stability and order in a gendered society, although the young woman in the street cannot accept this order of things.
• The Effects of International Trade on Gender Inequality: Women Carpet Weavers of Iran
• The Prevailing Gender Inequality in USA
• Perspectives On Gender Inequality And The Barrier Of Culture On Education
• Race, Ethnicity and Gender Inequality in the Rwanda Genocide
• The Scarcity Of Water And Its Effect On Gender Inequality
• Unequal Division Of Economic Growth And Gender Inequality
• The Measurement of Multidimensional Gender Inequality
• The Growing Issue of Gender Inequality in the Workplace
• Understanding Gender Inequality in Employment and Retirement
• The Violation of Women and the Practice of Gender Inequality Through Female Genital Mutilation (FGM)
• The Different Elements That Affect Gender Inequality in Society
• How Gender Inequality Is Defined As The Unequal Treatment
• The Controversial Issue of Gender Inequality in the Twentieth Century
• The Correlation between Poverty and Gender Inequality
• The Problem of Gender Inequality in the United States and Its Negative Impact on American Society
• National Culture, Gender Inequality and Women’s Success in Micro, Small and Medium Enterprises
• The Institutional Basis of Gender Inequality: The Social Institutions and Gender Index (SIGI)
• The Issue of Gender Stereotypes and Its Contribution to Gender Inequality in the Second Presidential Debate
• Women´s Right Movement: Gender Inequality
• International Relations: Gender Inequality Issues
• Problems of Gender Inequality for Women in India and Other
• The Role of Women Discrimination and Gender Inequality in Development: The Cross-Section Analysis by Different Income Groups
• The Effect of Gender Inequality on Economic Development: Case of African Countries
• The Role of Historical Resource Constraints in Modern Gender Inequality: A Cross-Country Analysis
• The Influence of Gender Budgeting in Indian States on Gender Inequality and Fiscal Spending
• Identity, Society, and Gender Inequality of Women in North West India
• How Debates of Gender Inequality and Gender Roles are Conflicted With Family Structures
• The Features of the Problem of Gender Inequality in the World
• Untapped Potential in the Study of Negotiation and Gender Inequality in Organizations
• The Impact of the Sectoral Allocation of Foreign aid on Gender Inequality
• The Impact Of Gender Inequality On Employee Satisfaction
• The Issue of Gender Inequality Between the North and South in the United States
• The Problem of Gender Inequality in South Asia and Its Effects on Girls and Women in Society
• Whether Patriarchy Is The Leading Cause Of Gender Inequality
• The Issues of Gender Inequality in the Book a Woman on the Edge
• Women Deserve For A Girl : A Real Issue Of Gender Inequality
• The Main Causes And Consequences Of Gender Inequality
• The Experience of Gender Inequality in The Awakening, a Novel by Kate Chopin
• The Issues of Gender Inequality in the Political Landscape Despite the Legal and Theoretical Attempts to Overcome the Gender Gap
• Measuring Key Disparities in Human Development: The Gender Inequality Index
• The Relationship of the Cultural and Historical Specificity of Gender Inequality in Mitchell’s Not Enough of the Past
• Stange Journeys and Gender Inequality in Pullman and Dangarembga
• Help or Hindrance? Religion’s Impact on Gender Inequality in Attitudes and Outcomes
• Should Women Continue Fighting Against Gender Inequality
• Women ‘s Gender Inequality By Chinua Achebe ‘s Things Fall Apart
• Legislation and Labour Market Gender Inequality: An Analysis of OECD Countries
• What Are the Types of Gender Inequality?
• Does Gender Inequality Hinder Development and Economic Growth?
• What Does Gender Inequality Mean?
• Does Trade Liberalization Help to Reduce Gender Inequality?
• What are the main issues of gender inequality?
• How Has Gender Inequality Impacted Contemporary Catholicism?
• What Determines Gender Inequality in Household Food Security in Kenya?
• Who Is Affected by Gender Inequality?
• What Causes Gender Inequality?
• Where Is Gender Inequality Most Common?
• What Are the Effects of Gender Equality?
• How Can We Stop Gender Inequality?
• What Is an Example of Gender Equality?
• Does Gender Inequality Still Exist Today?
• What Is the Impact of Gender Inequality in the Society?
• When Did Gender Inequality Become an Issue?
• What Are the Three Main Areas of Gender Inequality in the World?
• How Does Gender Inequality Affect Development?
• What Is the Difference Between Gender Equity, Gender Equality, and Women’s Empowerment?
• Why Is Gender Equality Important?
• Is Gender Equality a Concern for Men?
• What Are the Manifestations of Gender Inequality in the Modern Society?
• Is Gender Inequality Still a Pending and Pressing Issue in the Modern World?
• What Are the Causes and Effects of Gender Inequality in the European Society?
• Can Gender Inequality Issues Be a Boost for Women’s Progress, Development, and Improvement in the Workplace?
• What Are the Future Consequences and Outcomes of the Present-Day Gender Inequality?
• Where Does Gender Inequality Step From?
• Is It Possible at All to Achieve Gender Equality?
• What Is Gender Blindness and How Does It Impact the Overall Concept of Gender Inequality?
• Is Education a Solution to Solve Inequality Between the Sexes?
• Chicago (A-D)
• Chicago (N-B)

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100 Gender Research Topics For Academic Papers

Gender research topics are very popular across the world. Students in different academic disciplines are often asked to write papers and essays about these topics. Some of the disciplines that require learners to write about gender topics include:

Sociology Psychology Gender studies Business studies

When pursuing higher education in these disciplines, learners can choose what to write about from a wide range of gender issues topics. However, the wide range of issues that learners can research and write about when it comes to gender makes choosing what to write about difficult. Here is a list of the top 100 gender and sexuality topics that students can consider.

Controversial Gender Research Topics

Do you like the idea of writing about something controversial? If yes, this category has some of the best gender topics to write about. They touch on issues like gender stereotypes and issues that are generally associated with members of a specific gender. Here are some of the best controversial gender topics that you can write about.

• How human behavior is affected by gender misconceptions
• How are straight marriages influenced by gay marriages
• Explain the most common sex-role stereotypes
• What are the effects of workplace stereotypes?
• What issues affect modern feminism?
• How sexuality affects sex-role stereotyping
• How does the media break sex-role stereotypes
• Explain the dual approach to equality between women and men
• What are the most outdated sex-role stereotypes
• Are men better than women?
• How equal are men and women?
• How do politics and sexuality relate?
• How can films defy gender-based stereotypes
• What are the advantages of being a woman?
• What are the disadvantages of being a woman?
• What are the advantages of being a man?
• Discuss the disadvantages of being a woman
• Should governments legalize prostitution?
• Explain how sexual orientation came about?
• Women communicate better than men
• Women are the stronger sex
• Explain how the world can be made better for women
• Discuss the future gender norms
• How important are sex roles in society
• Discuss the transgender and feminism theory
• How does feminism help in the creation of alternative women’s culture?
• Gender stereotypes in education and science
• Discuss racial variations when it comes to gender-related attitudes
• Women are better leaders
• Men can’t survive without women

This category also has some of the best gender debate topics. However, learners should be keen to pick topics they are interested in. This will enable them to ensure that they enjoy the research and writing process.

Interesting Gender Inequality Topics

Gender-based inequality is witnessed almost every day. As such, most learners are conversant with gender inequality research paper topics. However, it’s crucial to pick topics that are devoid of discrimination of members of a specific gender. Here are examples of gender inequality essay topics.

• Sex discrimination aspects in schools
• How to identify inequality between sexes
• Sex discrimination causes
• The inferior role played by women in relationships
• Discuss sex differences in the education system
• How can gender discrimination be identified in sports?
• Can inequality issues between men and women be solved through education?
• Why are professional opportunities for women in sports limited?
• Why are there fewer women in leadership positions?
• Discuss gender inequality when it comes to work-family balance
• How does gender-based discrimination affect early childhood development?
• Can sex discrimination be reduced by technology?
• How can sex discrimination be identified in a marriage?
• Explain where sex discrimination originates from
• Discuss segregation and motherhood in labor markets
• Explain classroom sex discrimination
• How can inequality in American history be justified?
• Discuss different types of sex discrimination in modern society
• Discuss various factors that cause gender-based inequality
• Discuss inequality in human resource practices and processes
• Why is inequality between women and men so rampant in developing countries?
• How can governments bridge gender gaps between women and men?
• Work-home conflict is a sign of inequality between women and men
• Explain why women are less wealthy than men
• How can workplace gender-based inequality be addressed?

After choosing the gender inequality essay topics they like, students should research, brainstorm ideas, and come up with an outline before they start writing. This will ensure that their essays have engaging introductions and convincing bodies, as well as, strong conclusions.

Amazing Gender Roles Topics for Academic Papers and Essays

This category has ideas that slightly differ from gender equality topics. That’s because equality or lack of it can be measured by considering the representation of both genders in different roles. As such, some gender roles essay topics might not require tiresome and extensive research to write about. Nevertheless, learners should take time to gather the necessary information required to write about these topics. Here are some of the best gender topics for discussion when it comes to the roles played by men and women in society.

• Describe gender identity
• Describe how a women-dominated society would be
• Compare gender development theories
• How equally important are maternity and paternity levees for babies?
• How can gender-parity be achieved when it comes to parenting?
• Discuss the issues faced by modern feminism
• How do men differ from women emotionally?
• Discuss gender identity and sexual orientation
• Is investing in the education of girls beneficial?
• Explain the adoption of gender-role stereotyped behaviors
• Discuss games and toys for boys and girls
• Describe patriarchal attitudes in families
• Explain patriarchal stereotypes in family relationships
• What roles do women and men play in politics?
• Discuss sex equity and academic careers
• Compare military career opportunities for both genders
• Discuss the perception of women in the military
• Describe feminine traits
• Discus gender-related issues faced by women in gaming
• Men should play major roles in the welfare of their children
• Explain how the aging population affects the economic welfare of women?
• What has historically determined modern differences in gender roles?
• Does society need stereotyped gender roles?
• Does nature have a role to play in stereotyped gender roles?
• The development and adoption of gender roles

The list of gender essay topics that are based on the roles of each sex can be quite extensive. Nevertheless, students should be keen to pick interesting gender topics in this category.

Important Gender Issues Topics for Research Paper

If you want to write a paper or essay on an important gender issue, this category has the best ideas for you. Students can write about different issues that affect individuals of different genders. For instance, this category can include gender wage gap essay topics. Wage variation is a common issue that affects women in different countries. Some of the best gender research paper topics in this category include:

• Discuss gender mainstreaming purpose
• Discuss the issue of gender-based violence
• Why is the wage gap so common in most countries?
• How can society promote equality in opportunities for women and men in sports?
• Explain what it means to be transgender
• Discuss the best practices of gender-neutral management
• What is women’s empowerment?
• Discuss how human trafficking affects women
• How problematic is gender-blindness for women?
• What does the glass ceiling mean in management?
• Why are women at a higher risk of sexual exploitation and violence?
• Why is STEM uptake low among women?
• How does ideology affect the determination of relations between genders
• How are sporting women fighting for equality?
• Discuss sports, women, and media institutions
• How can cities be made safer for girls and women?
• Discuss international trends in the empowerment of women
• How do women contribute to the world economy?
• Explain how feminism on different social relations unites men and women as groups
• Explain how gender diversity influence scientific discovery and innovation

This category has some of the most interesting women’s and gender studies paper topics. However, most of them require extensive research to come up with hard facts and figures that will make academic papers or essays more interesting.

Students in high schools and colleges can pick what to write about from a wide range of gender studies research topics. However, some gender studies topics might not be ideal for some learners based on the given essay prompt. Therefore, make sure that you have understood what the educator wants you to write about before you pick a topic. Our experts can help you choose a good thesis topic . Choosing the right gender studies topics enables learners to answer the asked questions properly. This impresses educators to award them top grades.

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Gender gaps remain for many women scientists, study finds

by Sherri Buri McDonald, University of Oregon

As more women have entered the biomedical field, they're getting a bigger share of research grants, and the gender gap in research funding appears to be narrowing, but the gains have been uneven.

That's because, at U.S. universities, most of those research dollars are going to senior women scientists, and their younger counterparts are missing out on the large grants that can advance science and careers, according to a new study by a University of Oregon researcher and collaborators.

Their findings were published May 17 in Nature Biotechnology .

"As the resources are increasingly flowing toward women, the disparity between senior men scientists and senior women scientists is closing," said co-author Chris Liu, an associate professor of management with the UO's Lundquist College of Business. "But the gap is persisting between junior men and women."

Liu collaborated with Andy S. Back, assistant professor in management and strategy at the University of Hong Kong Business School, and two researchers at the University of Maryland's Robert H. Smith School of Business: Waverly Ding, associate professor of management and organization, and Beril Yalcinkaya, a doctoral candidate in strategic management and entrepreneurship.

They examined the distribution of 2.3 million U.S. National Institutes of Health grants to biomedical scientists from 1985 to 2017.

Also, the researchers were struck by the contrast between two different sets of data. The first shows a steady climb in the percentage of life sciences doctoral degree recipients who are women, from roughly 30% in 1985 to 55% in 2020.

The second shows a persistent gender gap in the probability of holding a full-time tenured academic position in biomedicine. For the past three decades, the probability has been about 20% for women and nearly 40% for men.

"This is an important trend that has been overlooked," Liu said. "To fully realize the benefits of diversity, it is important that disadvantaged groups achieve the academic freedom afforded by grant funding and tenure. Our study reveals a systemic issue that needs to be addressed for young women scientists to advance through the ranks and have the greatest possible impact on science and society."

Possible solutions could include earmarking research funding for young women scientists and offering grant-writing assistance and other supports, Liu said.

Journal information: Nature Biotechnology

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• Open access
• Published: 16 May 2024

Promoting equality, diversity and inclusion in research and funding: reflections from a digital manufacturing research network

• Oliver J. Fisher 1 ,
• Debra Fearnshaw   ORCID: orcid.org/0000-0002-6498-9888 2 ,
• Nicholas J. Watson 3 ,
• Peter Green 4 ,
• Fiona Charnley 5 ,
• Duncan McFarlane 6 &
• Sarah Sharples 2  

Research Integrity and Peer Review volume  9 , Article number:  5 ( 2024 ) Cite this article

146 Accesses

Metrics details

Equal, diverse, and inclusive teams lead to higher productivity, creativity, and greater problem-solving ability resulting in more impactful research. However, there is a gap between equality, diversity, and inclusion (EDI) research and practices to create an inclusive research culture. Research networks are vital to the research ecosystem, creating valuable opportunities for researchers to develop their partnerships with both academics and industrialists, progress their careers, and enable new areas of scientific discovery. A feature of a network is the provision of funding to support feasibility studies – an opportunity to develop new concepts or ideas, as well as to ‘fail fast’ in a supportive environment. The work of networks can address inequalities through equitable allocation of funding and proactive consideration of inclusion in all of their activities.

This study proposes a strategy to embed EDI within research network activities and funding review processes. This paper evaluates 21 planned mitigations introduced to address known inequalities within research events and how funding is awarded. EDI data were collected from researchers engaging in a digital manufacturing network activities and funding calls to measure the impact of the proposed method.

Quantitative analysis indicates that the network’s approach was successful in creating a more ethnically diverse network, engaging with early career researchers, and supporting researchers with care responsibilities. However, more work is required to create a gender balance across the network activities and ensure the representation of academics who declare a disability. Preliminary findings suggest the network’s anonymous funding review process has helped address inequalities in funding award rates for women and those with care responsibilities, more data are required to validate these observations and understand the impact of different interventions individually and in combination.

Conclusions

In summary, this study offers compelling evidence regarding the efficacy of a research network's approach in advancing EDI within research and funding. The network hopes that these findings will inform broader efforts to promote EDI in research and funding and that researchers, funders, and other stakeholders will be encouraged to adopt evidence-based strategies for advancing this important goal.

Peer Review reports

Introduction

Achieving equality, diversity, and inclusion (EDI) is an underpinning contributor to human rights, civilisation and society-wide responsibility [ 1 ]. Furthermore, promoting and embedding EDI within research environments is essential to make the advancements required to meet today’s research challenges [ 2 ]. This is evidenced by equal, diverse and inclusive teams leading to higher productivity, creativity and greater problem-solving ability [ 3 ], which increases the scientific impact of research outputs and researchers [ 4 ]. However, there remains a gap between EDI research and the everyday implementation of inclusive practices to achieve change [ 5 ]. This paper presents and reflects on the EDI measures trialled by the UK Engineering and Physical Sciences Research Council (EPSRC) funded digital manufacturing research network, Connected Everything (grant number: EP/S036113/1) [ 6 ]. The EPSRC is a UK research council that funds engineering and physical sciences research. By sharing these reflections, this work aims to contribute to the wider effort of creating an inclusive research culture. The perceptions of equality, diversity, and inclusion may vary among individuals. For the scope of this study, the following definitions are adopted:

Equality: Equality is about ensuring that every individual has an equal opportunity to make the most of their lives and talents. No one should have poorer life chances because of the way they were born, where they come from, what they believe, or whether they have a disability.

Diversity: Diversity concerns understanding that each individual is unique, recognising our differences, and exploring these differences in a safe, positive, and nurturing way to value each other as individuals.

Inclusion: Inclusion is an effort and practice in which groups or individuals with different backgrounds are culturally and socially accepted, welcomed and treated equally. This concerns treating each person as an individual, making them feel valued, and supported and being respectful of who they are.

Research networks have varied goals, but a common purpose is to create new interdisciplinary research communities, by fostering interactions between researchers and appropriate scientific, technological and industrial groups. These networks aim to offer valuable career progression opportunities for researchers, through access to research funding, forming academic and industrial collaborations at network events, personal and professional development, and research dissemination. However, feedback from a 2021 survey of 19 UK research networks, suggests that these research networks are not always diverse, and whilst on the face of it they seem inclusive, they are perceived as less inclusive by minority groups (including non-males, those with disabilities, and ethnic minority respondents) [ 7 ]. The exclusivity of these networks further exacerbates the inequality within the academic community as it prevents certain groups from being able to engage with all aspects of network activities.

Research investigating the causes of inequality and exclusivity has identified several suggestions to make research culture more inclusive, including improving diverse representation within event programmes and panels [ 8 , 9 ]; ensuring events are accessible to all [ 10 ]; providing personalised resources and training to build capacity and increase engagement [ 11 ]; educating institutions and funders to understand and address the barriers to research [ 12 ]; and increasing diversity in peer review and funding panels [ 13 ]. Universities, research institutions and research funding bodies are increasingly taking responsibility to ensure the health of the research and innovation system and to foster inclusion. For example, the EPSRC has set out their own ‘Expectation for EDI’ to promote the formation of a diverse and inclusive research culture [ 14 ]. To drive change, there is an emphasis on the importance of measuring diversity and links to measured outcomes to benchmark future studies on how interventions affect diversity [ 5 ]. Further, collecting and sharing EDI data can also drive aspirations, provide a target for actions, and allow institutions to consider common issues. However, there is a lack of available data regarding the impact of EDI practices on diversity that presents an obstacle, impeding the realisation of these benefits and hampering progress in addressing common issues and fostering diversity and inclusion [ 5 ].

Funding acquisition is important to an academic’s career progression, yet funding may often be awarded in ways that feel unequal and/or non-transparent. The importance of funding in academic career progression means that, if credit for obtaining funding is not recognised appropriately, careers can be damaged, and, as a result of the lack of recognition for those who have been involved in successful research, funding bodies may not have a complete picture of the research community, and are unable to deliver the best value for money [ 15 ]. Awarding funding is often a key research network activity and an area where networks can have a positive impact on the wider research community. It is therefore important that practices are established to embed EDI consideration within the funding process and to ensure that network funding is awarded without bias. Recommendations from the literature to make the funding award process fairer include: ensuring a diverse funding panel; funders instituting reviewer anti-bias training; anonymous review; and/or automatic adjustments to correct for known biases [ 16 ]. In the UK, the government organisation UK Research and Innovation (UKRI), tasked with overseeing research and innovation funding, has pledged to publish data to enhance transparency. This initiative aims to furnish an evidence base for designing interventions and evaluating their efficacy. While the data show some positive signs (e.g., the award rates for male and female PI applicants were equal at 29% in 2020–21), Ottoline Leyser (UKRI Chief Executive) highlights the ‘persistent pernicious disparities for under-represented groups in applying for and winning research funding’ [ 17 ]. This suggests that a more radical approach to rethinking the traditional funding review process may be required.

This paper describes the approach taken by the ‘Connected Everything’ EPSRC-funded Network to embed EDI in all aspects of its research funding process, and evaluates the impact of this ambition, leading to recommendations for embedding EDI in research funding allocation.

Connected everything’s equality diversity and inclusion strategy

Connected Everything aims to create a multidisciplinary community of researchers and industrialists to address key challenges associated with the future of digital manufacturing. The network is managed by an investigator team who are responsible for the strategic planning and, working with the network manager, to oversee the delivery of key activities. The network was first funded between 2016–2019 (grant number: EP/P001246/1) and was awarded a second grant (grant number: EP/S036113/1). The network activities are based around three goals: building partnerships, developing leadership and accelerating impact.

The Connected Everything network represents a broad range of disciplines, including manufacturing, computer science, cybersecurity, engineering, human factors, business, sociology, innovation and design. Some of the subject areas, such as Computer Science and Engineering, tend to be male-dominated (e.g., in 2021/22, a total of 185,42 higher education student enrolments in engineering & technology subjects was broken down as 20.5% Female and 79.5% Male [ 18 ]). The networks also face challenges in terms of accessibility for people with care responsibilities and disabilities. In 2019, Connected Everything committed to embedding EDI in all its network activities and published a guiding principle and goals for improving EDI (see Additional file 1 ). When designing the processes to deliver the second iteration of Connected Everything, the team identified several sources of potential bias/exclusion which have the potential to impact engagement with the network. Based on these identified factors, a series of mitigation interventions were implemented and are outlined in Table  1 .

Connected everything anonymous review process

A key Connected Everything activity is the funding of feasibility studies to enable cross-disciplinary, foresight, speculative and risky early-stage research, with a focus on low technology-readiness levels. Awards are made via a short, written application followed by a pitch to a multidisciplinary diverse panel including representatives from industry. Six- to twelve-month-long projects are funded to a maximum value of £60,000.

The current peer-review process used by funders may reveal the applicants’ identities to the reviewer. This can introduce dilemmas to the reviewer regarding (a) deciding whether to rely exclusively on information present within the application or search for additional information about the applicants and (b) whether or not to account for institutional prestige [ 34 ]. Knowing an applicant’s identity can bias the assessment of the proposal, but by focusing the assessment on the science rather than the researcher, equality is more frequently achieved between award rates (i.e., the proportion of successful applications) [ 15 ]. To progress Connected Everything’s commitment to EDI, the project team created a 2-stage review process, where the applicants’ identity was kept anonymous during the peer review stage. This anonymous process, which is outlined in Fig.  1 , was created for the feasibility study funding calls in 2019 and used for subsequent funding calls.

Connected Everything’s anonymous review process [EDI: Equality, diversity, and inclusion]

To facilitate the anonymous review process, the proposal was submitted in two parts: part A the research idea and part B the capability-to-deliver statement. All proposals were first anonymously reviewed by a random selection of two members from the Connected Everything executive group, which is a diverse group of digital manufacturing experts and peers from academia, industry and research institutions that provide guidance and leadership on Connected Everything activities. The reviewers rated the proposals against the selection criteria (see Additional file 1 , Table 1) and provided overall comments alongside a recommendation on whether or not the applicant should be invited to the panel pitch. This information was summarised and shared with a moderation sift panel, made up of a minimum of two Connected Everything investigators and a minimum of one member of the executive group, that tensioned the reviewers’ comments (i.e. comments and evaluations provided by the peer reviewers are carefully considered and weighed against each other) and ultimately decided which proposals to invite to the panel. This tension process included using the identifying information to ensure the applicants did have the capability to deliver the project. If this remained unclear, the applicants were asked to confirm expertise in an area the moderation sift panel thought was key or asked to bring in additional expertise to the project team during the panel pitch.

During stage two the applicants were invited to pitch their research idea to a panel of experts who were selected to reflect the diversity of the community. The proposals, including applicants’ identities, were shared with the panel at least two weeks ahead of the panel. Individual panel members completed a summary sheet at the end of the pitch session to record how well the proposal met the selection criteria (see Additional file 1 , Table 1). Panel members did not discuss their funding decision until all the pitches had been completed. A panel chair oversaw the process but did not declare their opinion on a specific feasibility study unless the panel could not agree on an outcome. The panel and panel chair were reminded to consider ways to manage their unconscious bias during the selection process.

Due to the positive response received regarding the anonymous review process, Connected Everything extended its use when reviewing other funded activities. As these awards were for smaller grant values (~ £5,000), it was decided that no panel pitch was required, and the researcher’s identity was kept anonymous for the entire process.

Data collection and analysis methods

Data collection.

Equality, diversity and inclusion data were voluntarily collected from applicants for Connected Everything research funding and from participants who won scholarships to attend Connected Everything funded activities. Responses to the EDI data requests were collected from nine Connected Everything coordinated activities between 2019 and 2022. Data requests were sent after the applicant had applied for Connected Everything funding or had attended a Connected Everything funded activity. All data requests were completed voluntarily, with reassurance given that completion of the data requested in no way affected their application. In total 260 responses were received, of which the three feasibility study calls comprised 56.2% of the total responses received. Overall, there was a 73.8% response rate.

To understand the diversity of participants engaging with Connected Everything activities and funding, the data requests asked for details of specific diversity characteristics: gender, transgender, disability, ethnicity, age, and care responsibilities. Although sex and gender are terms that are often used interchangeably, they are two different concepts. To clarify, the definitions used by the UK government describe sex as a set of biological attributes that is generally limited to male or female, and typically attributed to individuals at birth. In contrast, gender identity is a social construction related to behaviours and attributes, and is self-determined based on a person’s internal perception, identification and experience. Transgender is a term used to describe people whose gender identity is not the same as the sex they were registered at birth. Respondents were first asked to identify their gender and then whether their gender was different from their birth sex.

For this study, respondents were asked to (voluntarily) self-declare whether they consider themselves to be disabled or not. Ethnicity within the data requests was based on the 2011 census classification system. When reporting ethnicity data, this study followed the AdvanceHE example to aggregate the census categories into six groups to enable benchmarking against the available academic ethnicity data. AdvanceHE is a UK charity that works to improve the higher education system for staff, students and society. However, it was acknowledged that there were limitations with this grouping, including the assumption that minority ethnic staff or students are a homogenous group [ 16 ]. Therefore, this study made sure to breakdown these groups during the discussion of the results. The six groups are:

Asian: Asian/Asian British: Indian, Pakistani, Bangladeshi, and any other Asian background;

Black: Black/African/Caribbean/Black British: African, Caribbean, and any other Black/African/Caribbean background;

Other ethnic backgrounds, including Arab.

White: all white ethnic groups.

Benchmarking data

Published data from the Higher Education Statistics Agency [ 26 ] (a UK organisation responsible for collecting, analysing, and disseminating data related to higher education institutions and students), UKRI funding data [ 19 , 35 ] and 2011 census data [ 36 ] were used to benchmark the EDI data collected within this study. The responses to the data collected were compared to the engineering and technology cluster of academic disciplines, as this is most represented by Connected Everything’s main funded EPSRC. The Higher Education Statistics Agency defines the engineering and technology cluster as including the following subject areas: general engineering; chemical engineering; mineral, metallurgy & materials engineering; civil engineering; electrical, electronic & computer engineering; mechanical, aero & production engineering and; IT, systems sciences & computer software engineering [ 37 ].

When assessing the equality in funding award rates, previous studies have focused on analysing the success rates of only the principal investigators [ 15 , 16 , 38 ]; however, Connected Everything recognised that writing research proposals is a collaborative task, so requested diversity data from the whole research team. The average of the last six years of published principal investigator and co-investigator diversity data for UKRI and EPSRC funding awards (2015–2021) was used to benchmark the Connected Everything funding data [ 35 ]. The UKRI and EPSRC funding review process includes a peer review stage followed by panel pitch and assessment stage; however, the applicant's track record is assessed during the peer review stage, unlike the Connected Everything review process.

The data collected have been used to evaluate the success of the planned migrations to address EDI factors affecting the higher education research ecosystem, as outlined in Table  1 (" Connected Everything’s Equality Diversity and Inclusion Strategy " Section).

Dominance of small number of research-intensive universities receiving funding from network

The dominance of a small number of research-intensive universities receiving funding from a network can have implications for the field of research, including: the unequal distribution of resources; a lack of diversity of research, limited collaboration opportunities; and impact on innovation and progress. Analysis of published EPSRC funding data between 2015 and 2021 [ 19 ], shows that the funding has been predominately (74.1%, 95% CI [71.%, 76.9%] out of £3.98 billion) awarded to Russell Group universities. The Russell Group is a self-selected association of 24 research-intensive universities (out of the 174 universities) in the UK, established in 1994. Evaluation of the universities that received Connected Everything feasibility study funding between 2016–2019, shows that Connected Everything awarded just over half (54.6%, 95% CI [25.1%, 84.0%] out of 11 awards) to Russell Group universities. Figure  2 shows that the Connected Everything funding awarded to Russell Group universities reduced to 44.4%, 95% CI [12.0%, 76.9%] of 9 awards between 2019–2022.

A comparison of funding awarded by EPSRC (total = £3.98 billion) across Russell Group universities and non-Russell Group universities, alongside the allocations for Connected Everything I (total = £660 k) and Connected Everything II (total = £540 k)

Dominance of successful applications from men

The percentage point difference between the award rates of researchers who identified as female, those who declare a disability, or identified as ethnic minority applicants and carers and their respective counterparts have been plotted in Fig.  3 . Bars to the right of the axis mean that the award rate of the female/declared-disability/ethnic-minority/carer applicants is greater than that of male/non- disability/white/not carer applicants.

Percentage point (PP) differences in award rate by funding provider for gender, disability status, ethnicity and care responsibilities (data not collected by UKRI and EPSRC [ 35 ]). The total number of applicants for each funder are as follows: Connected Everything = 146, EPSRC = 37,960, and UKRI = 140,135. *The numbers of applicants were too small (< 5) to enable a meaningful discussion

Figure  3 (A) shows that between 2015 and 2021 research team applicants who identified as male had a higher award rate than those who identified as female when applying for EPSRC and wider UKRI research council funding. Connected Everything funding applicants who identified as female achieved a higher award rate (19.4%, 95% CI [6.5%, 32.4%] out of 146) compared to male applicants (15.6%, 95% CI [8.8%, 22.4%] out of 146). These data suggest that biases have been reduced by the Connected Everything review process and other mitigation strategies (e.g., visible gender diversity in panel pitch members and publishing CE principal and goals to demonstrate commitment to equality and fairness). This finding aligns with an earlier study that found gender bias during the peer review process, resulting in female investigators receiving less favourable evaluations than their male counterparts [ 15 ].

Over-representation of people identifying as male in engineering and technology academic community

Figure  4 shows the response to the gender question, with 24.2%, 95% CI [19.0%, 29.4%] of 260 responses identifying as female. This aligns with the average for the engineering and technology cluster (21.4%, 95% CI [20.9%, 21.9%] female of 27,740 academic staff), which includes subject areas representative of our main funder, EPSRC [ 22 ]. We also sought to understand the representation of transgender researchers within the network. However, following the rounding policy outlined by UK Government statistics policies and procedures [ 39 ], the number of responses that identified as a different sex to birth was too low (< 5) to enable a meaningful discussion.

Gender question responses from a total of 260 respondents

Dominance of successful applications from white academics

Figure  3 (C) shows that researchers with a minority ethnicity consistently have a lower award rate than white researchers when applying for EPSRC and UKRI funding. Similarly, the results in Fig.  3 (C) indicate that white researchers are more successful (8.0% percentage point, 95% CI [-8.6%, 24.6%]) when applying for Connected Everything funding. These results indicate that more measures should be implemented to support the ethnic minority researchers applying for Connected Everything funding, as well as sense checking there is no unconscious bias in any of the Connected Everything funding processes. The breakdown of the ethnicity diversity of applicants at different stages of the Connected Everything review process (i.e. all applications, applicants invited to panel pitch and awarded feasibility studies) has been plotted in Fig.  5 to help identify where more support is needed. Figure  5 shows an increase in the proportion of white researchers from 54%, 95% CI [45.4%, 61.8%] of all 146 applicants to 66%, 95% CI [52.8%, 79.1%] of the 50 researchers invited to the panel pitch. This suggests that stage 1 of the Connected Everything review process (anonymous review of written applications) may favour white applicants and/or introduce unconscious bias into the process.

Ethnicity questions responses from different stages during the Connected Everything anonymous review process. The total number of applicants is 146, with 50 at the panel stage and 23 ultimately awarded

Under-representation of those from black or minority ethnic backgrounds

Connected Everything appears to have a wide range of ethnic diversity, as shown in Fig.  6 . The ethnicities Asian (18.3%, 95% CI [13.6%, 23.0%]), Black (5.1%, 95% CI [2.4%, 7.7%]), Chinese (12.5%, 95% CI [8.4%, 16.5%]), mixed (3.5%, 95% CI [1.3%, 5.7%]) and other (7.8%, 95% CI [4.5%, 11.1%]) have a higher representation among the 260 individuals engaging with network’s activities, in contrast to both the engineering and technology academic community and the wider UK population. When separating these groups into the original ethnic diversity answers, it becomes apparent that there is no engagement with ‘Black or Black British: Caribbean’, ‘Mixed: White and Black Caribbean’ or ‘Mixed: White and Asian’ researchers within Connected Everything activities. The lack of engagement with researchers from a Caribbean heritage is systemic of a lack of representation within the UK research landscape [ 25 ].

Ethnicity question responses from a total of 260 respondents compared to distribution of the 13,085 UK engineering and technology (E&T) academic staff [ 22 ] and 56 million people recorded in the UK 2011 census data [ 36 ]

Under-representation of disabilities, chronic conditions, invisible illnesses and neurodiversity in funded activities and events.

Figure  7 (A) shows that 5.7%, 95% CI [2.4%, 8.9%] of 194 responses declared a disability. This is higher than the average of engineering and technology academics that identify as disabled (3.4%, 95% CI [3.2%, 3.7%] of 27,730 academics). Between Jan-March 2022, 9.0 million people of working age (16–64) within the UK were identified as disabled by the Office for National Statistics [ 40 ], which is 21% of the working age population [ 27 ]. Considering these statistics, there is a stark under-representation of disabilities, chronic conditions, invisible illnesses and neurodiversity amongst engineering and technology academic staff and those engaging in Connected Everything activities.

Responses to A  Disability and B  Care responsibilities questions colected from a total of 194 respondents

Between 2015 and 2020 academics that declared a disability have been less successful than academics without a disability in attracting UKRI and EPSRC funding, as shown in Fig.  3 (B). While Fig.  3 (B) shows that those who declare a disability have a higher Connected Everything funding award rate, the number of applicants who declared a disability was too small (< 5) to enable a meaningful discussion regarding this result.

Under-representation of those with care responsibilities in funded activities and events

In response to the care responsibilities question, Fig.  7 (B) shows that 27.3%, 95% CI [21.1%, 33.6%] of 194 respondents identified as carers, which is higher than the 6% of adults estimated to be providing informal care across the UK in a UK Government survey of the 2020/2021 financial year [ 41 ]. However, the ‘informal care’ definition used by the 2021 survey includes unpaid care to a friend or family member needing support, perhaps due to illness, older age, disability, a mental health condition or addiction [ 41 ]. The Connected Everything survey included care responsibilities across the spectrum of care that includes partners, children, other relatives, pets, friends and kin. It is important to consider a wide spectrum of care responsibilities, as key academic events, such as conferences, have previously been demonstrably exclusionary sites for academics with care responsibilities [ 42 ]. Breakdown analysis of the responses to care responsibilities by gender in Fig.  8 reveals that 37.8%, 95% CI [25.3%, 50.3%] of 58 women respondents reported care responsibilities, compared to 22.6%, 95% CI [61.1%, 76.7%] of 136 men respondents. Our findings reinforce similar studies that conclude the burden of care falls disproportionately on female academics [ 43 ].

Responses to care responsibilities when grouped by A  136 males and B  58 females

Figure  3 (D) shows that researchers with careering responsibilities applying for Connected Everything funding have a higher award rate than those researchers applying without care responsibilities. These results suggest that the Connected Everything review process is supportive of researchers with care responsibilities, who have faced barriers in other areas of academia.

Reduced opportunities for ECRs

Early-career researchers (ECRs) represent the transition stage between starting a PhD and senior academic positions. EPSRC defines an ECR as someone who is either within eight years of their PhD award, or equivalent professional training or within six years of their first academic appointment [ 44 ]. These periods exclude any career break, for example, due to family care; health reasons; and reasons related to COVID-19 such as home schooling or increased teaching load. The median age for starting a PhD in the UK is 24 to 25, while PhDs usually last between three and four years [ 45 ]. Therefore, these data would imply that the EPSRC median age of ECRs is between 27 and 37 years. It should be noted, however, that this definition is not ideal and excludes ECRs who may have started their research career later in life.

Connected Everything aims to support ECRs via measures that include mentoring support, workshops, summer schools and podcasts. Figure  9 shows a greater representation of researchers engaging with Connected Everything activities that are aged between 30–44 (62.4%, 95% CI [55.6%, 69.2%] of 194 respondents) when compared to the wider engineering and technology academic community (43.7%, 95% CI [43.1%, 44.3%] of 27,780 academics) and UK population (26.9%, 95% CI [26.9%, 26.9%]).

Age question responses from a total of 194 respondents compared to distribution of the 27,780 UK engineering and technology (E&T) academic staff [ 22 ] and 56 million people recorded in the UK 2011 census data [ 36 ]

High competition for funding has a greater impact on ECRs

Figure  10 shows that the largest age bracket applying for and winning Connected Everything funding is 31–45, whereas 72%, CI 95% [70.1%, 74.5%] of 12,075 researchers awarded EPSRC grants between 2015 and 2021 were 40 years or older. These results suggest that measures introduced by Connected Everything has been successful at providing funding opportunities for researchers who are likely to be early-mid career stage.

Age of researchers at applicant and awarded funding stages for A  Connected Everything between 2019–2022 (total of 146 applicants and 23 awarded) and B  EPSRC funding between 2015–2021 [ 35 ] (total of 35,780 applicants and 12,075 awarded)

The results of this paper provide insights into the impact that Connected Everything’s planned mitigations have had on promoting equality, diversity, and inclusion (EDI) in research and funding. Collecting EDI data from individuals who engage with network activities and apply for research funding enabled an evaluation of whether these mitigations have been successful in achieving the intended outcomes outlined at the start of the study, as summarised in Table  2 .

The results in Table  2 indicate that Connected Everything’s approach to EDI has helped achieve the intended outcome to improve representation of women, ECRs, those with a declared disability and black/minority ethnic backgrounds engaging with network events when compared to the engineering and technology academic community. In addition, the network has helped raise awareness of the high presence of researchers with care responsibilities at network events, which can help to track progress towards making future events inclusive and accessible towards these carers. The data highlights two areas for improvement: (1) ensuring a gender balance; and (2) increasing representation of those with declared disabilities. Both these discrepancies are indicative of the wider imbalances and underrepresentation of these groups in the engineering and technology academic community [ 26 ], yet represent areas where networks can strive to make a difference. Possible strategies include: using targeted outreach; promoting greater representation of these groups in event speakers; and going further to create a welcoming and inclusive environment. One barrier that can disproportionately affect women researchers is the need to balance care responsibilities with attending network events [ 46 ]. This was reflected in the Connected Everything data that reported 37.8%, 95% CI [25.3%, 50.3%] of women engaging with network activities had care responsibilities, compared to 22.6%, 95% CI [61.1%, 76.7%] of men. Providing accommodations such as on-site childcare, flexible scheduling, or virtual attendance options can therefore help to promote inclusivity and allow more women researchers to attend.

Only 5.7%, 95% CI [2.4%, 8.9%] of responses engaging with Connected Everything declared a disability, which is higher than the engineering and technology academic community (3.4%, 95% CI [3.2%, 3.7%]) [ 26 ], but unrepresentative of the wider UK population. It has been suggested that academics can be uncomfortable when declaring disabilities because scholarly contributions and institutional citizenship are so prized that they feel they cannot be honest about their issues or health concerns and keep them secret [ 47 ]. In research networks, it is important to be mindful of this hidden group within higher education and ensure that measures are put in place to make the network’s activities inclusive to all. Future considerations for accommodations to improve research events inclusivity include: improving physical accessibility of events; providing assistive technology such as screen readers, audio descriptions, and captioning can help individuals with visual or hearing impairments to access and participate; providing sign language interpreters; offering flexible scheduling options; and the provision of quiet rooms, written materials in accessible formats, and support staff trained to work with individuals with cognitive disabilities.

Connected Everything introduced measures (e.g., anonymised reviewing process, Q&A sessions before funding calls, inclusive design of panel pitch) to help address inequalities in how funding is awarded. Table 2 shows success in reducing the dominance of researchers who identify as male and research-intensive universities in winning research funding and that researchers with care responsibilities were more successful at winning funding than those without care responsibilities. The data revealed that the proposed measures were unable to address the inequality in award rates between white and ethnic minority researchers, which is an area to look to improve. The inequality appears to occur during the anonymous review stage, with a greater proportion of white researchers being invited to panel. Recommendations to make the review process fairer include: ensuring greater diversity of reviewers; reviewer anti-bias training; and automatic adjustments to correct for known biases in writing style [ 16 , 32 ].

When reflecting on the development of a strategy to embed EDI throughout the network, Connected Everything has learned several key lessons that may benefit other networks undergoing a similar activity. These include:

EDI is never ‘done’: There is a constant need to review approaches to EDI to ensure they remain relevant to the network community. Connected Everything could review its principles to include the concept of justice in its approach to diversity and inclusion. The concept of justice concerning EDI refers to the removal of systematic barriers that stop fair and equitable distribution of resources and opportunities among all members of society, regardless of their individual characteristics or backgrounds. The principles and subsequent actions could be reviewed against the EDI expectations [ 14 ], paying particular attention to areas where barriers may still be present. For example, shifting from welcoming people into existing structures and culture to creating new structures and culture together, with specific emphasis on decision or advisory mechanisms within the network. This activity could lend itself to focusing more on tailored support to overcome barriers, thus achieving equity, if it is not within the control of the network to remove the barrier itself (justice).

Widen diversity categories: By collecting data on a broad range of characteristics, we can identify and address disparities and biases that might otherwise be overlooked. A weakness of this dataset is that ignores the experience of those with intersectional identities, across race, ethnicity, gender, class, disability and/ or LGBTQI. The Wellcome Trust noted how little was known about the socio-economic background of scientists and researchers [ 48 ].

Collect data on whole research teams: For the first two calls for feasibility study funding, Connected Everything only asked the Principal Investigator to voluntarily provide their data. We realised that this was a limited approach and, in the third call, asked for the data regarding the whole research team to be shared anonymously. Furthermore, we do not currently measure the diversity of our event speakers, panellists or reviewers. Collecting these data in the future will help to ensure the network is accountable and will ensure that all groups are represented during our activities and in the funding decision-making process.

High response rate: Previous surveys measuring network diversity (e.g., [ 7 ]) have struggled to get responses when surveying their memberships; whereas, this study achieved a response rate of 73.8%. We attribute this high response rate to sending EDI data requests on the point of contact with the network (e.g., on submitting funding proposals or after attending network events), rather than trying to survey the entire network membership at anyone point in time.

Improve administration: The administration associated with collecting EDI data requires a commitment to transparency, inclusivity, and continuous improvement. For example, during the first feasibility funding call, Connected Everything made it clear that the review process would be anonymous, but the application form was not in separate documents. This made anonymising the application forms extremely time-consuming. For the subsequent calls, separate documents were created – Part A for identifying information (Principal Investigator contact details, Project Team and Industry collaborators) and Part B for the research idea.

Accepting that this can be uncomfortable: Trying to improve EDI can be uncomfortable because it often requires challenging our assumptions, biases, and existing systems and structures. However, it is essential if we want to make real progress towards equity and inclusivity. Creating processes to support embedding EDI takes time and Connected Everything has found it is rare to get it right the first time. Connected Everything is sharing its learning as widely as possible both to support others in their approaches and continue our learning as we reflect on how to continually improve, even when it is challenging.

Enabling individual engagement with EDI: During this work, Connected Everything recognised that methods for engaging with such EDI issues in research design and delivery are lacking. Connected Everything, with support from the Future Food Beacon of Excellence at the University of Nottingham, set out to develop a card-based tool [ 49 ] to help researchers and stakeholders identify questions around how their work may promote equity and increase inclusion or have a negative impact towards one or more protected groups and how this can be overcome. The results of this have been shared at conference presentations [ 50 ] and will be published later.

While this study provides insights into how EDI can be improved in research network activities and funding processes, it is essential to acknowledge several limitations that may impact the interpretation of the findings.

Sample size and generalisability: A total of 260 responses were received, which may not be representative of our overall network of 500 + members. Nevertheless, this data provides a sense of the current diversity engaging in Connected Everything activities and funding opportunities, which we can compare with other available data to steer action to further diversify the network.

Handling of missing data: Out of the 260 responses, 66 data points were missing for questions regarding age, disability, and caring responsibilities. These questions were mistakenly omitted from a Connected Everything summer school survey, contributing to 62 missing data points. While we assumed the remainer of missing data to be at random during analysis, it's important to acknowledge it could be related to other factors, potentially introducing bias into our results.

Emphasis on quantitative data: The study relies on using quantitative data to evaluate the impact of the EDI measures introduced by Connected Everything. However, relying solely on quantitative metrics may overlook nuanced aspects of EDI that cannot be easily quantified. For example, EDI encompasses multifaceted issues influenced by historical, cultural, and contextual factors. These nuances may not be fully captured by numbers alone. In addition, some EDI efforts may not yield immediate measurable outcomes but still contribute to a more inclusive environment.

Diversity and inclusion are not synonymous: The study proposes 21 measures to contribute towards creating an equal, diverse and inclusive research culture and collects diversity data to measure the impact of these measures. However, while diversity is simpler to monitor, increasing diversity alone does not guarantee equality or inclusion. Even with diverse research groups, individuals from underrepresented groups may still face barriers, microaggressions, or exclusion.

Balancing anonymity and rigour in grant reviews:The proposed anonymous review process proposed by Connected Everything removes personal and organisational details from the research ideas under reviewer evaluation. However, there exists a possibility that a reviewer could discern the identity of the grant applicant based on the research idea. Reviewers are expected to be subject matter experts in the field relevant to the grant proposal they are evaluating. Given the specialised nature of scientific research, it is conceivable that a well-known applicant could be identified through the specifics of the work, the methodologies employed, and even the writing style.

Expanding gender identity options: A limitation of this study emerged from the restricted gender options (male, female, other, prefer not to say) provided to respondents when answering the gender identity question. This limitation reflects the context of data collection in 2018, a time when diversity monitoring guidance was still limited. As our understanding of gender identity evolves beyond binary definitions, future data collection efforts should embrace a more expansive and inclusive approach, recognising the diverse spectrum of gender identities.

In conclusion, this study provides evidence of the effectiveness of a research network's approach to promoting equality, diversity, and inclusion (EDI) in research and funding. By collecting EDI data from individuals who engage with network activities and apply for research funding, this study has shown that the network's initiatives have had a positive impact on representation and fairness in the funding process. Specifically, the analysis reveals that the network is successful at engaging with ECRs, and those with care responsibilities and has a diverse range of ethnicities represented at Connected Everything events. Additionally, the network activities have a more equal gender balance and greater representation of researchers with disabilities when compared to the engineering and technology academic community, though there is still an underrepresentation of these groups compared to the national population.

Connected Everything introduced measures to help address inequalities in how funding is awarded. The measures introduced helped reduce the dominance of researchers who identified as male and research-intensive universities in winning research funding. Additionally, researchers with care responsibilities were more successful at winning funding than those without care responsibilities. However, inequality persisted with white researchers achieving higher award rates than those from ethnic minority backgrounds. Recommendations to make the review process fairer include: ensuring greater diversity of reviewers; reviewer anti-bias training; and automatic adjustments to correct for known biases in writing style.

Connected Everything’s approach to embedding EDI in network activities has already been shared widely with other EPSRC-funded networks and Hubs (e.g. the UKRI Circular Economy Hub and the UK Acoustics Network Plus). The network hopes that these findings will inform broader efforts to promote EDI in research and funding and that researchers, funders, and other stakeholders will be encouraged to adopt evidence-based strategies for advancing this important goal.

Availability of data and materials

The data collected was anonymously, however, it may be possible to identify an individual by combining specific records of the data request form data. Therefore, the study data has been presented in aggregate form to protect the confidential of individuals and the data utilised in this study cannot be made openly accessible due to ethical obligations to protect the privacy and confidentiality of the data providers.

Abbreviations

Early career researcher

Equality, diversity and inclusion

Engineering physical sciences research council

UK research and innovation

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Acknowledgements

The authors would like to acknowledge the support Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/S036113/1], Connected Everything II: Accelerating Digital Manufacturing Research Collaboration and Innovation. The authors would also like to gratefully acknowledge the Connected Everything Executive Group for their contribution towards developing Connected Everything’s equality, diversity and inclusion strategy.

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/S036113/1].

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School of Engineering, University of Liverpool, Liverpool, UK

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Centre for Circular Economy, University of Exeter, Exeter, UK

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OJF analysed and interpreted the data, and was the lead author in writing and revising the manuscript. DF led the data acquisition and supported the interpretation of the data. DF was also a major contributor to the design of the equality diversity and inclusion (EDI) strategy proposed in this work. NJW supported the design of the EDI strategy and was a major contributor in reviewing and revising the manuscript. PG supported the design of the EDI strategy, and was a major contributor in reviewing and revising the manuscript. FC supported the design of the EDI strategy and the interpretation of the data. DM supported the design of the EDI strategy. SS led the development EDI strategy proposed in this work, and was a major contributor in data interpretation and reviewing and revising the manuscript. All authors read and approved the final manuscript.

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Correspondence to Debra Fearnshaw .

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Fisher, O.J., Fearnshaw, D., Watson, N.J. et al. Promoting equality, diversity and inclusion in research and funding: reflections from a digital manufacturing research network. Res Integr Peer Rev 9 , 5 (2024). https://doi.org/10.1186/s41073-024-00144-w

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At Harvard Kennedy School, experts debated diversity policies, academic freedom and free speech

Faculty members Danielle Allen, Arthur Applbaum, and Khalil Gibran Muhammad examine diversity, equity, inclusion and belonging policies through the lens of academic freedom and free speech. 

The final Harvard Kennedy School Dean’s Discussion of the semester addressed the relationship of diversity, equity, inclusion and belonging (DEIB) to academic freedom, and put the spotlight on difficult conversations dealing with racial justice in education—including on the Harvard campus.  

Professors Danielle Allen , Arthur Applbaum MPP 1982 PhD 1988, and Khalil Gibran Muhammad provided historic context, defined usage, and offered real-life examples of DEIB principles in action. Sarah Wald , senior policy advisor, chief of staff, and adjunct lecturer in public policy, moderated.  

Wald asked the faculty panelists to first identify what they saw as the distinctions between freedom of speech and academic freedom.  

“Some people think that academic freedom is simply the local instantiation of free speech,” began Applbaum, the Adams Professor of Political Leadership and Democratic Values. “I think there are interactions, but we need to keep them separate.”  

“Academic freedom is the idea that we should be free to engage in open and rigorous inquiry[.] … When it works, it has high epistemic value, even if it turns out that we're not actually speaking the truth.”

Arthur applbaum.

He defined freedom of speech as a constitutional right we have against governments to say pretty much whatever we want: “It doesn't have to be speech of particularly high epistemic value,” in other words, it does not necessarily have to be based in knowledge.

“Academic freedom is the idea that we should be free to engage in open and rigorous inquiry,” Applbaum said, “what Habermas calls the unforced forced of the better argument.”  It is the exercise of the power of reason, and “when it works, it has high epistemic value, even if it turns out that we're not actually speaking the truth.”

Applbaum argued that the power of reason may need to be protected from protest speech, which is mainly the exercise of causal power. “Free speech often is pursued through causal power,” the use of incentives and disincentives, political mobilization, and the exercise of political pressure. “Free speech often gets in the way of academic freedom.”  

Muhammad, the Ford Foundation Professor of History, Race, and Public Policy, considered the context of college campuses.

“Free speech exists within a constitutional framework and governs notions of liberal democracy and open societies,” he noted, “Academic freedom is also the protection of faculty to do unpopular research. Its core value in a university setting is to ensure that powerful people do not crush the act of research itself by asking certain questions that will question the power arrangements in and of themselves.”  

Using a story from her own college years, Allen, professor of public policy at HKS, and the James Bryant Conant University Professor at Harvard, illustrated a point about free speech and academic freedom. While at Princeton working on her senior thesis, she was called a racist word. She said she was not hurt by the hateful insult because she felt she was part of a trusted community.  

“I realized that for anybody who doesn't have that basic level of trust in their community, that moment would've been quite damaging, destabilizing, unsettling, and affect the ability to continue work on the thesis,” she said.  

“Academic freedom is also the protection of faculty to do unpopular research ... to ensure that powerful people do not crush the act of research itself by asking certain questions that will question the power arrangements in and of themselves.”

Khalil gibran muhammad.

Academic freedom, she said, protects the ability to follow your curiosity wherever it leads. “Freedom of expression is about the public sphere,” said Allen. “We have to deal with problematic, discriminatory, and harassing speech on campus to protect the space where people are trying to pursue academic freedom.”  

Wald then moved the conversation towards the role of DEIB efforts, and Muhammad provided historical context.  

Emerging from the 1960s civil rights movement, the United States more formally examined how to address diversity in the face of discrimination. “Under [President] Johnson you get the first rationale for essentially an affirmative effort to address the ways in which legalized  discrimination had minimized, and in some cases, eliminated opportunities for people based on race,” said Muhammad.  

Federal efforts on affirmative action became more prominent under President Nixon, especially in the construction trades. In the realm of higher education, a landmark 1978 Supreme Court decision, Regents of the University of California v. Bakke, ruled it unconstitutional for a university to use racial quotas but held that affirmative action programs could be constitutional.    

“On one hand, the Court essentially rejects quotas as a form of discrimination, and they embrace a concept that Justice Powell argued is a diversity rationale,” explained Muhammad. It's of compelling interest, he noted, that our institutions reflect the diversity of the society we live in. “This has benefits that will accrue to both the institution and the individual students.”

The Court's Decision, to some degree, brought a cohort of Black people to higher education and prominent professional positions in an unprecedented way. 

But with diversity came discomfort. Muhammad recalled the 2014 “I, Too, Am Harvard” campaign, calling out instances of microaggressions experienced by Black Harvard students. “Microaggressions were becoming a national problem,” said Muhammad, referring to indirect forms of discrimination and the ways in which people of color had to justify their existence, their right to be on campus.  

A newer framing highlighting equity, he continued, demonstrates a more committed institutional focus on the policies and practices of institutions. By shifting from “equality” to “equity” institutions were figuring out what policies and practices were needed to make sure that everyone got access to opportunities.  

“That is the issue of DEI. They’re a good thing to be annoyed about and to rile people up with, and there’s a lot of political mileage that you can get from doing so.”

Danielle allen.

Allen brought up the politicization of DEIB activities. “If you look at Trump's 2020 executive order, one of the last things he did before leaving office, he banned diversity and inclusion training in federal agencies,” she said. “And one of President Biden's first executive orders in January 2021 is the Equity Action Plan to advance equity for all.  

“That is the issue of DEI,” she continued. “They're a good thing to be annoyed about and to rile people up with, and there's a lot of political mileage that you can get from doing so.”  

Applbaum noted that Justice Powell’s deciding opinion in the Bakke case introduced the educational benefits of a diverse student body as the sole justification for taking race into account in university admissions, a view that no other justice completely endorsed.  Powell excluded considerations of past societal discrimination or of achieving proportionality.

“We are trapped into using diversity as our term of art because it is the only constitutionally sound term that we can use,” he said.

“With the Harvard [Supreme Court] case last year [rejecting affirmative action programs], even diversity has been taken off the table,” Applbaum continued. “Now we're stuck with a term,” but we can't explicitly use race in our admissions even for diversity.  

“And,” he continued, “we have spent decades not being internally transparent because there are certain kinds of conversations that we can't have …. The court has demanded that we talk in terms of diversity, but I think it's been distorting and has shrunk the domain over which we can have these conversations.”

Wald “officially ended” this last discussion of the seven-year Dean’s Discussion series by thanking Dean Doug Elmendorf for his leadership in creating this series for the HKS community to engage in meaningful, enlightened conversation on topical issues.  

Photos by Winston Tang

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Gender and soliloquy: analyzing the internal lives of women on screen

Karla Oeler

How can cinema – a fundamentally visual and auditory medium – convey interiority? This was the question at the heart of the Clayman Institute faculty research fellows talk given last month by Karla Oeler, associate professor of film and media studies at Stanford University. Throughout her talk, Oeler gave a sneak peek of her upcoming book, The Surface of Things: Cinema and the Devices of Interiority . She investigated the ways films depict the act of thinking that the thinker does not share. This effort proves particularly challenging when the on-screen thinker is a woman, given cinema’s historical fixation with women’s surface appearance and patriarchal assumptions about women’s agency and subjectivity. 

According to Oeler, since the silent era, film critics have claimed soliloquy for the cinema, arguing that such cinematic techniques as the close-up and the point-of-view sequence fulfill soliloquy’s function—to show characters talking with themselves without expressing their thoughts to another character.  In this sense, film adopts a device that initially emerged in literature and theater. Yet, Oeler argued, early filmmakers and theorists like Béla Balázs believed that film was better suited for internalizing than other media. To convey interiority, films paradoxically used close-up shots of the face – that is, a visual surface – to convey the thoughts happening below that very surface.

To explore these contradictions, Oeler analyzed and interpreted two differing works of art by women artists, each of which grapples with female interiority on screen. The first, by Candice Breitz, is titled  The Soliloquy Trilogy  (2000). In the work, Breitz removes the reverse shots from the movies  Dirty Harry, Witches of Eastwick,  and  Basic Instinct,  instead only including shots of the respective main characters. Oeler noted that the new version of  Basic Instinct,  featuring only shots of Sharon Stone, is reduced to a mere seven and a half minutes of film. On one hand, Oeler argued, the new version of the movie becomes close to the literal meaning of “soliloquy”: a character talking alone on screen. On the other hand, the lines spoken by Stone are still communicated to others, making the “soliloquy” title somewhat ironic. According to Oeler, the only interiority truly on display in the art is Breitz’s own: Despite the mechanical nature of the re-edited film, the new choices reveal something of Breitz’s own subjectivity.

Oeler also explored a second work of art, this one by Iranian visual artist Shirin Neshat, titled  Soliloquy  (1999). In her piece, Neshat appears on two massive screens that face each other. On the right screen, she shows herself moving through various locations in New York State; on the left, she appears in Mardin, Turkey. At various points in the installation, each visual of herself stops, seemingly to contemplate the other one. According to Oeler, Neshat invented a powerful new way of conveying distanced self-reflection. By having two images of Neshat looking at each other from two different locations, the work of art presents a subjective reflection on her multiple senses of identity. For Oeler, this film exceeds soliloquy, since Neshat both makes the soliloquy and appears in it. 

Taken together, Oeler’s analyses reveal the thought-provoking ways that these women artists have moved beyond depictions of the woman as object on screen, as well as the differing approaches to filmic interiority. Through varied approaches, Oeler argues, women have inventively brought their own interiorities to bear on a fundamentally visual medium.

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• Women and Political Leadership Ahead of the 2024 Election

1. Views of the state of gender equality in politics

Table of contents.

• The ideal number of women and men in high elected positions
• Will there ever be as many women as men in high political offices?
• Traits people think help or hurt men and women running for office
• Views of how a candidate’s gender, race and ethnicity impact their chances of election
• How a woman president would compare with presidents who are men in handling several policy areas
• How a woman president would impact the world’s respect for the U.S.
• How important is it that the U.S. elects a woman president?
• Will there be a woman president in the near future?
• Acknowledgments
• The American Trends Panel survey methodology

A narrow majority of U.S. adults (53%) say there are too few women in high political offices in the United States today. Some 37% say there are about the right number of women and 8% say there are too many women elected to higher offices.

The share saying there are too few women in high political offices is down from 59% since we last asked this question in 2018 .

Views on this differ widely by gender and political affiliation. And there are also differences between Democratic men and women and between Republican men and women.

Most women (63%) say there are too few women in high political offices. Three-in-ten say there are about the right number of women and just 5% say there are too many.

Views are more divided among men: 42% say there are too few women and 46% say there are about the right number. About one-in-ten men (11%) say there are too many women in high political offices.

By partisanship

Three-quarters of Democrats and Democratic leaners say there are too few women in high political offices today. A much smaller share of Republicans and Republican leaners (29%) say the same. A majority of Republicans (56%) say there are about the right number of women in these offices.

Republican women are about twice as likely as Republican men to say there are too few women in high political offices (40% vs. 19%). Republican men are about as likely to say there are too few women in these elected offices as they are to say there are too many.

About six-in-ten Republican men (62%) say there are about the right number of women in high political offices, compared with 51% of Republican women.

Majorities of Democratic men and women say there are too few women in high political offices. But Democratic women (82%) are more likely than Democratic men (67%) to say this.

Most people (77%) who say there are too few women in high political offices say it would be ideal to have about an equal number of men and women in these offices. About one-in-ten (9%) say it would be ideal if there were more women than there are now but still not as many women as men . And 13% say it would be ideal to have more women than men in these positions.

Majorities of Democrats and Republicans who say there are too few women in high elected offices say it would be ideal for there to be about an equal number of men and women . Still, there are some differences in these views by party. Among those who say there are too few women in these offices:

• 18% of Democrats – but just 4% of Republicans – say it would be ideal for there to be more women than men in high political offices.
• Republicans (15%) are about twice as likely as Democrats (7%) to say it would be ideal to have more women in high political offices than there are now, but still not as many women as men .

Looking ahead, about half of Americans (52%) say that, as more women run for office, it is only a matter of time before there are as many women as men in high political offices. A smaller but sizeable share (46%) say men will continue to hold more high political offices in the future. These views are unchanged from five years ago.

A majority of men (58%) say it’s only a matter of time before there are as many women as men in high political offices. A smaller share of women (46%) say the same, while 51% say men will continue to hold more of these positions, even as more women run for office.

More than half of Republicans (54%) say it’s only a matter of time before there are as many women as men in high elected offices. Democrats are more divided: 51% agree, while 48% say men will continue to hold more high political offices in the future.

Majorities of Republican and Democratic men (59% and 57%, respectively) say there will eventually be as many women as men in high political offices. Republican women are about evenly divided, while Democratic women are somewhat more likely to say men will continue to hold more of these offices (53%) than to say it’s only a matter of time before there are as many women as men in these positions (45%).

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