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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).

• View Article
• PubMed/NCBI
• Google Scholar
• 9. UN. Transforming our world: The 2030 Agenda for Sustainable Development. General Assembley 70 Session; 2015.
• 11. Nature. Get the Sustainable Development Goals back on track. Nature. 2020;577(January 2):7–8
• 37. Fronzetti Colladon A, Grippa F. Brand intelligence analytics. In: Przegalinska A, Grippa F, Gloor PA, editors. Digital Transformation of Collaboration. Cham, Switzerland: Springer Nature Switzerland; 2020. p. 125–41. https://doi.org/10.1371/journal.pone.0233276 pmid:32442196
• 39. Griffiths TL, Steyvers M, editors. Finding scientific topics. National academy of Sciences; 2004.
• 40. Mimno D, Wallach H, Talley E, Leenders M, McCallum A, editors. Optimizing semantic coherence in topic models. 2011 Conference on Empirical Methods in Natural Language Processing; 2011.
• 41. Wang C, Blei DM, editors. Collaborative topic modeling for recommending scientific articles. 17th ACM SIGKDD international conference on Knowledge discovery and data mining 2011.
• 46. Straka M, Straková J, editors. Tokenizing, pos tagging, lemmatizing and parsing ud 2.0 with udpipe. CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies; 2017.
• 49. Lu Y, Li, R., Wen K, Lu Z, editors. Automatic keyword extraction for scientific literatures using references. 2014 IEEE International Conference on Innovative Design and Manufacturing (ICIDM); 2014.
• 55. Roelleke T, Wang J, editors. TF-IDF uncovered. 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval—SIGIR ‘08; 2008.
• 56. Mihalcea R, Tarau P, editors. TextRank: Bringing order into text. 2004 Conference on Empirical Methods in Natural Language Processing; 2004.
• 58. Iannone F, Ambrosino F, Bracco G, De Rosa M, Funel A, Guarnieri G, et al., editors. CRESCO ENEA HPC clusters: A working example of a multifabric GPFS Spectrum Scale layout. 2019 International Conference on High Performance Computing & Simulation (HPCS); 2019.
• 60. Wasserman S, Faust K. Social network analysis: Methods and applications: Cambridge University Press; 1994.
• 141. Williams JE, Best DL. Measuring sex stereotypes: A multination study, Rev: Sage Publications, Inc; 1990.
• 172. Steele CM, Aronson J. Stereotype threat and the test performance of academically successful African Americans. In: Jencks C, Phillips M, editors. The Black–White test score gap. Washington, DC: Brookings; 1998. p. 401–27

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Gender inequalities in the workplace: the effects of organizational structures, processes, practices, and decision makers’ sexism

Gender inequality in organizations is a complex phenomenon that can be seen in organizational structures, processes, and practices. For women, some of the most harmful gender inequalities are enacted within human resources (HRs) practices. This is because HR practices (i.e., policies, decision-making, and their enactment) affect the hiring, training, pay, and promotion of women. We propose a model of gender discrimination in HR that emphasizes the reciprocal nature of gender inequalities within organizations. We suggest that gender discrimination in HR-related decision-making and in the enactment of HR practices stems from gender inequalities in broader organizational structures, processes, and practices. This includes leadership, structure, strategy, culture, organizational climate, as well as HR policies. In addition, organizational decision makers’ levels of sexism can affect their likelihood of making gender biased HR-related decisions and/or behaving in a sexist manner while enacting HR practices. Importantly, institutional discrimination in organizational structures, processes, and practices play a pre-eminent role because not only do they affect HR practices, they also provide a socializing context for organizational decision makers’ levels of hostile and benevolent sexism. Although we portray gender inequality as a self-reinforcing system that can perpetuate discrimination, important levers for reducing discrimination are identified.

Introduction

The workplace has sometimes been referred to as an inhospitable place for women due to the multiple forms of gender inequalities present (e.g., Abrams, 1991 ). Some examples of how workplace discrimination negatively affects women’s earnings and opportunities are the gender wage gap (e.g., Peterson and Morgan, 1995 ), the dearth of women in leadership ( Eagly and Carli, 2007 ), and the longer time required for women (vs. men) to advance in their careers ( Blau and DeVaro, 2007 ). In other words, workplace discrimination contributes to women’s lower socio-economic status. Importantly, such discrimination against women largely can be attributed to human resources (HR) policies and HR-related decision-making. Furthermore, when employees interact with organizational decision makers during HR practices, or when they are told the outcomes of HR-related decisions, they may experience personal discrimination in the form of sexist comments. Both the objective disadvantages of lower pay, status, and opportunities at work, and the subjective experiences of being stigmatized, affect women’s psychological and physical stress, mental and physical health ( Goldenhar et al., 1998 ; Adler et al., 2000 ; Schmader et al., 2008 ; Borrel et al., 2010 ),job satisfaction and organizational commitment ( Hicks-Clarke and Iles, 2000 ), and ultimately, their performance ( Cohen-Charash and Spector, 2001 ).

Within this paper, we delineate the nature of discrimination within HR policies, decisions, and their enactment, as well as explore the causes of such discrimination in the workplace. Our model is shown in Figure ​ Figure1 1 . In the Section “Discrimination in HR Related Practices: HR Policy, Decisions, and their Enactment,” we explain the distinction between HR policy, HR-related decision-making, and HR enactment and their relations to each other. Gender inequalities in HR policy are a form of institutional discrimination. We review evidence of institutional discrimination against women within HR policies set out to determine employee selection, performance evaluations, and promotions. In contrast, discrimination in HR-related decisions and their enactment can result from organizational decision makers’ biased responses: it is a form of personal discrimination. Finally, we provide evidence of personal discrimination against women by organizational decision makers in HR-related decision-making and in the enactment of HR policies.

A model of the root causes of gender discrimination in HR policies, decision-making, and enactment .

In the Section “The Effect of Organizational Structures, Processes, and Practices on HR Practices,” we focus on the link between institutional discrimination in organizational structures, processes, and practices that can lead to personal discrimination in HR practices (see Figure ​ Figure1 1 ). Inspired by the work of Gelfand et al. (2007) , we propose that organizational structures, processes, and practices (i.e., leadership, structure, strategy, culture, climate, and HR policy) are interrelated and may contribute to discrimination. Accordingly, gender inequalities in each element can affect the others, creating a self-reinforcing system that can perpetuate institutional discrimination throughout the organization and that can lead to discrimination in HR policies, decision-making, and enactment. We also propose that these relations between gender inequalities in the organizational structures, processes, and practices and discrimination in HR practices can be bidirectional (see Figure ​ Figure1 1 ). Thus, we also review how HR practices can contribute to gender inequalities in organizational structures, processes, and practices.

In the Section “The Effect of Hostile and Benevolent Sexism on How Organizational Decision Makers’ Conduct HR Practices,” we delineate the link between organizational decision makers’ levels of sexism and their likelihood of making gender-biased HR-related decisions and/or behaving in a sexist manner when enacting HR policies (e.g., engaging in gender harassment). We focus on two forms of sexist attitudes: hostile and benevolent sexism ( Glick and Fiske, 1996 ). Hostile sexism involves antipathy toward, and negative stereotypes about, agentic women. In contrast, benevolent sexism involves positive but paternalistic views of women as highly communal. Whereas previous research on workplace discrimination has focused on forms of sexism that are hostile in nature, we extend this work by explaining how benevolent sexism, which is more subtle, can also contribute in meaningful yet distinct ways to gender discrimination in HR practices.

In the Section “The Effect of Organizational Structures, Processes, and Practices on Organizational Decision Makers’ Levels of Hostile and Benevolent Sexism,” we describe how institutional discrimination in organizational structures, processes, and practices play a critical role in our model because not only do they affect HR-related decisions and the enactment of HR policies, they also provide a socializing context for organizational decision makers’ levels of hostile and benevolent sexism. In other words, where more institutional discrimination is present, we can expect higher levels of sexism—a third link in our model—which leads to gender bias in HR practices.

In the Section “How to Reduce Gender Discrimination in Organizations,” we discuss how organizations can reduce gender discrimination. We suggest that, to reduce discrimination, organizations should focus on: HR practices, other closely related organizational structures, processes, and practices, and the reduction of organizational decision makers’ level of sexism. Organizations should take such a multifaceted approach because, consistent with our model, gender discrimination is a result of a complex interplay between these factors. Therefore, a focus on only one factor may not be as effective if all the other elements in the model continue to promote gender inequality.

The model we propose for understanding gender inequalities at work is, of course, limited and not intended to be exhaustive. First, we only focus on women’s experience of discrimination. Although men also face discrimination, the focus of this paper is on women because they are more often targets ( Branscombe, 1998 ; Schmitt et al., 2002 ; McLaughlin et al., 2012 ) and discrimination is more psychologically damaging for women than for men ( Barling et al., 1996 ; Schmitt et al., 2002 ). Furthermore, we draw on research from Western, individualistic countries conducted between the mid-1980s to the mid-2010s that might not generalize to other countries or time frames. In addition, this model derives from research that has been conducted primarily in sectors dominated by men. This is because gender discrimination ( Mansfield et al., 1991 ; Welle and Heilman, 2005 ) and harassment ( Mansfield et al., 1991 ; Berdhal, 2007 ) against women occur more in environments dominated by men. Now that we have outlined the sections of the paper and our model, we now turn to delineating how gender discrimination in the workplace can be largely attributed to HR practices.

Discrimination in HR Related Practices: HR Policy, Decisions, and their Enactment

In this section, we explore the nature of gender discrimination in HR practices, which involves HR policies, HR-related decision-making, and their enactment by organizational decision makers. HR is a system of organizational practices aimed at managing employees and ensuring that they are accomplishing organizational goals ( Wright et al., 1994 ). HR functions include: selection, performance evaluation, leadership succession, and training. Depending on the size and history of the organization, HR systems can range from those that are well structured and supported by an entire department, led by HR specialists, to haphazard sets of policies and procedures enacted by managers and supervisors without formal training. HR practices are critically important because they determine the access employees have to valued reward and outcomes within an organization, and can also influence their treatment within an organization ( Levitin et al., 1971 ).

Human resource practices can be broken down into formal HR policy, HR-related decision-making, and the enactment of HR policies and decisions. HR policy codifies practices for personnel functions, performance evaluations, employee relations, and resource planning ( Wright et al., 1994 ). HR-related decision-making occurs when organizational decision makers (i.e., managers, supervisors, or HR personnel) employ HR policy to determine how it will be applied to a particular situation and individual. The enactment of HR involves the personal interactions between organizational decision makers and job candidates or employees when HR policies are applied. Whereas HR policy can reflect institutional discrimination, HR-related decision-making and enactment can reflect personal discrimination by organizational decision makers.

Institutional Discrimination in HR Policy

Human resource policies that are inherently biased against a group of people, regardless of their job-related knowledge, skills, abilities, and performance can be termed institutional discrimination. Institutional discrimination against women can occur in each type of HR policy from the recruitment and selection of an individual into an organization, through his/her role assignments, training, pay, performance evaluations, promotion, and termination. For instance, if women are under-represented in a particular educational program or a particular job type and those credentials or previous job experience are required to be considered for selection, women are being systematically, albeit perhaps not intentionally, discriminated against. In another example, there is gender discrimination if a test is used in the selection battery for which greater gender differences emerge, than those that emerge for job performance ratings ( Hough et al., 2001 ). Thus, institutional discrimination can be present within various aspects of HR selection policy, and can negatively affect women’s work outcomes.

Institutional discrimination against women also occurs in performance evaluations that are used to determine organizational rewards (e.g., compensation), opportunities (e.g., promotion, role assignments), and punishments (e.g., termination). Gender discrimination can be formalized into HR policy if criteria used by organizational decision makers to evaluate job performance systematically favor men over women. For instance, “face time” is a key performance metric that rewards employees who are at the office more than those who are not. Given that women are still the primary caregivers ( Acker, 1990 ; Fuegen et al., 2004 ), women use flexible work arrangements more often than men and, consequently, face career penalties because they score lower on face time ( Glass, 2004 ). Thus, biased criteria in performance evaluation policies can contribute to gender discrimination.

Human resource policies surrounding promotions and opportunities for advancement are another area of concern. In organizations with more formal job ladders that are used to dictate and constrain workers’ promotion opportunities, women are less likely to advance ( Perry et al., 1994 ). This occurs because job ladders tend to be divided by gender, and as such, gender job segregation that is seen at entry-level positions will be strengthened as employees move up their specific ladder with no opportunity to cross into other lines of advancement. Thus, women will lack particular job experiences that are not available within their specific job ladders, making them unqualified for advancement ( De Pater et al., 2010 ).

In sum, institutional discrimination can be present within HR policies set out to determine employee selection, performance evaluations, and promotions. These policies can have significant effects on women’s careers. However, HR policy can only be used to guide HR-related decision-making. In reality, it is organizational decision-makers, that is, managers, supervisors, HR personnel who, guided by policy, must evaluate job candidates or employees and decide how policy will be applied to individuals.

Personal Discrimination in HR-Related Decision-Making

The practice of HR-related decision-making involves social cognition in which others’ competence, potential, and deservingness are assessed by organizational decision makers. Thus, like all forms of social cognition, HR-related decision-making is open to personal biases. HR-related decisions are critically important because they determine women’s pay and opportunities at work (e.g., promotions, training opportunities). Personal discrimination against women by organizational decision makers can occur in each stage of HR-related decision-making regarding recruitment and selection, role assignments, training opportunities, pay, performance evaluation, promotion, and termination.

Studies with varying methodologies show that women face personal discrimination when going through the selection process (e.g., Goldberg, 1968 ; Rosen and Jerdee, 1974 ). Meta-analyses reveal that, when being considered for male-typed (i.e., male dominated, believed-to-be-for-men) jobs, female candidates are evaluated more negatively and recommended for employment less often by study participants, compared with matched male candidates (e.g., Hunter et al., 1982 ; Tosi and Einbender, 1985 ; Olian et al., 1988 ; Davison and Burke, 2000 ). For example, in audit studies, which involve sending ostensibly real applications for job openings while varying the gender of the applicant, female applicants are less likely to be interviewed or called back, compared with male applicants (e.g., McIntyre et al., 1980 ; Firth, 1982 ). In a recent study, male and female biology, chemistry, and physics professors rated an undergraduate science student for a laboratory manager position ( Moss-Racusin et al., 2012 ). The male applicant was rated as significantly more competent and hireable, offered a higher starting salary (about $4000), and offered more career mentoring than the female applicant was. In summary, women face a distinct disadvantage when being considered for male-typed jobs.

There is ample evidence that women experience biased performance evaluations on male-typed tasks. A meta-analysis of experimental studies reveals that women in leadership positions receive lower performance evaluations than matched men; this is amplified when women act in a stereotypically masculine, that is, agentic fashion ( Eagly et al., 1992 ). Further, in masculine domains, women are held to a higher standard of performance than men are. For example, in a study of military cadets, men and women gave their peers lower ratings if they were women, despite having objectively equal qualifications to men ( Boldry et al., 2001 ). Finally, women are evaluated more poorly in situations that involve complex problem solving; in these situations, people are skeptical regarding women’s expertise and discredit expert women’s opinions but give expert men the benefit of the doubt ( Thomas-Hunt and Phillips, 2004 ).

Sometimes particular types of women are more likely to be discriminated against in selection and performance evaluation decisions. Specifically, agentic women, that is, those who behave in an assertive, task-oriented fashion, are rated as less likeable and less hireable than comparable agentic male applicants ( Heilman and Okimoto, 2007 ; Rudman and Phelan, 2008 ; Rudman et al., 2012 ). In addition, there is evidence of discrimination against pregnant women when they apply for jobs ( Hebl et al., 2007 ; Morgan et al., 2013 ). Further, women who are mothers are recommended for promotion less than women who are not mothers or men with or without children ( Heilman and Okimoto, 2008 ). Why might people discriminate specifically against agentic women and pregnant women or mothers, who are seemingly very different? The stereotype content model, accounts for how agentic women, who are perceived to be high in competence and low in warmth, will be discriminated against because of feelings of competition; whereas, pregnant women and mothers, who are seen as low in competence, but high in warmth, will be discriminated against because of a perceived lack of deservingness ( Fiske et al., 1999 , 2002 ; Cuddy et al., 2004 ). Taken together, research has uncovered that different forms of bias toward specific subtypes of women have the same overall effect—bias in selection and performance evaluation decisions.

Women are also likely to receive fewer opportunities at work, compared with men, resulting in their under-representation at higher levels of management and leadership within organizations ( Martell et al., 1996 ; Eagly and Carli, 2007 ). Managers give women fewer challenging roles and fewer training opportunities, compared with men ( King et al., 2012 ; Glick, 2013 ). For instance, female managers ( Lyness and Thompson, 1997 ) and midlevel workers ( De Pater et al., 2010 ) have less access to high-level responsibilities and challenges that are precursors to promotion. Further, men are more likely to be given key leadership assignments in male-dominated fields and in female-dominated fields (e.g., Maume, 1999 ; De Pater et al., 2010 ). This is detrimental given that challenging roles, especially developmental ones, help employees gain important skills needed to excel in their careers ( Spreitzer et al., 1997 ).

Furthermore, managers rate women as having less promotion potential than men ( Roth et al., 2012 ). Given the same level of qualifications, managers are less likely to grant promotions to women, compared with men ( Lazear and Rosen, 1990 ). Thus, men have a faster ascent in organizational hierarchies than women ( Cox and Harquail, 1991 ; Stroh et al., 1992 ; Blau and DeVaro, 2007 ). Even minimal amounts of gender discrimination in promotion decisions for a particular job or level can have large, cumulative effects given the pyramid structure of most hierarchical organizations ( Martell et al., 1996 ; Baxter and Wright, 2000 ). Therefore, discrimination by organizational decision makers results in the under-promotion of women.

Finally, women are underpaid, compared with men. In a comprehensive US study using data from 1983 to 2000, after controlling for human capital factors that could affect wages (e.g., education level, work experience), the researchers found that women were paid 22% less than men ( U.S. Government Accountability Office, 2003 ). Further, within any given occupation, men typically have higher wages than women; this “within-occupation” wage gap is especially prominent in more highly paid occupations ( U.S. Census Bureau, 2007 ). In a study of over 2000 managers, women were compensated less than men were, even after controlling for a number of human capital factors ( Ostroff and Atwater, 2003 ). Experimental work suggests that personal biases by organizational decision makers contribute to the gender wage gap. When participants are asked to determine starting salaries for matched candidates that differ by gender, they pay men more (e.g., Steinpreis et al., 1999 ; Moss-Racusin et al., 2012 ). Such biases are consequential because starting salaries determine life-time earnings ( Gerhart and Rynes, 1991 ). In experimental studies, when participants evaluate a man vs. a woman who is matched on job performance, they choose to compensate men more ( Marini, 1989 ; Durden and Gaynor, 1998 ; Lips, 2003 ). Therefore, discrimination in HR-related decision-making by organizational decision makers can contribute to women being paid less than men are.

Taken together, we have shown that there is discrimination against women in decision-making related to HR. These biases from organizational decision makers can occur in each stage of HR-related decision-making and these biased HR decisions have been shown to negatively affect women’s pay and opportunities at work. In the next section, we review how biased HR practices are enacted, which can involve gender harassment.

Personal Discrimination in HR Enactment

By HR enactment, we refer to those situations where current or prospective employees go through HR processes or when they receive news of their outcomes from organizational decision makers regarding HR-related issues. Personal gender discrimination can occur when employees are given sexist messages, by organizational decision makers, related to HR enactment. More specifically, this type of personal gender discrimination is termed gender harassment, and consists of a range of verbal and non-verbal behaviors that convey sexist, insulting, or hostile attitudes about women ( Fitzgerald et al., 1995a , b ). Gender harassment is the most common form of sex-based discrimination ( Fitzgerald et al., 1988 ; Schneider et al., 1997 ). For example, across the military in the United States, 52% of the 9,725 women surveyed reported that they had experienced gender harassment in the last year ( Leskinen et al., 2011 , Study 1). In a random sample of attorneys from a large federal judicial circuit, 32% of the 1,425 women attorneys surveyed had experienced gender harassment in the last 5 years ( Leskinen et al., 2011 , Study 2). When examining women’s experiences of gender harassment, 60% of instances were perpetrated by their supervisor/manager or a person in a leadership role (cf. Crocker and Kalemba, 1999 ; McDonald et al., 2008 ). Thus, personal discrimination in the form of gender harassment is a common behavior; however, is it one that organizational decision makers engage in when enacting HR processes and outcomes?

Although it might seem implausible that organizational decision makers would convey sexist sentiments to women when giving them the news of HR-related decisions, there have been high-profile examples from discrimination lawsuits where this has happened. For example, in a class action lawsuit against Walmart, female workers claimed they were receiving fewer promotions than men despite superior qualifications and records of service. In that case, the district manager was accused of confiding to some of the women who were overlooked for promotions that they were passed over because he was not in favor of women being in upper management positions ( Wal-Mart Stores, Inc. v. Dukes, 2004/2011 ). In addition, audit studies, wherein matched men and women apply to real jobs, have revealed that alongside discrimination ( McIntyre et al., 1980 ; Firth, 1982 ; Moss-Racusin et al., 2012 ), women experience verbal gender harassment when applying for sex atypical jobs, such as sexist comments as well as skeptical or discouraging responses from hiring staff ( Neumark, 1996 ). Finally, gender harassment toward women when HR policies are enacted can also take the form of offensive comments and denying women promotions due to pregnancy or the chance of pregnancy. For example, in Moore v. Alabama , an employee was 8 months pregnant and the woman’s supervisor allegedly looked at her belly and said “I was going to make you head of the office, but look at you now” ( Moore v. Alabama State University, 1996 , p. 431; Williams, 2003 ). Thus, organizational decision makers will at times convey sexist sentiments to women when giving them the news of HR-related decisions.

Interestingly, whereas discrimination in HR policy and in HR-related decision-making is extremely difficult to detect ( Crosby et al., 1986 ; Major, 1994 ), gender harassment in HR enactment provides direct cues to recipients that discrimination is occurring. In other words, although women’s lives are negatively affected in concrete ways by discrimination in HR policy and decisions (e.g., not receiving a job, being underpaid), they may not perceive their negative outcomes as due to gender discrimination. Indeed, there is a multitude of evidence that women and other stigmatized group members are loath to make attributions to discrimination ( Crosby, 1984 ; Vorauer and Kumhyr, 2001 ; Stangor et al., 2003 ) and instead are likely to make internal attributions for negative evaluations unless they are certain the evaluator is biased against their group ( Ruggiero and Taylor, 1995 ; Major et al., 2003 ). However, when organizational decision makers engage in gender harassment during HR enactment women should be more likely to interpret HR policy and HR-related decisions as discriminatory.

Now that we have specified the nature of institutional gender discrimination in HR policy and personal discrimination in HR-related decision-making and in HR enactment, we turn to the issue of understanding the causes of such discrimination: gender discrimination in organizational structures, processes, and practices, and personal biases of organizational decision makers.

The Effect of Organizational Structures, Processes, and Practices on HR Practices

The first contextual factor within which gender inequalities can be institutionalized is leadership. Leadership is a process wherein an individual (e.g., CEOs, managers) influences others in an effort to reach organizational goals ( Chemers, 1997 ; House and Aditya, 1997 ). Leaders determine and communicate what the organization’s priorities are to all members of the organization. Leaders are important as they affect the other organizational structures, processes, and practices. Specifically, leaders set culture, set policy, set strategy, and are role models for socialization. We suggest that one important way institutional gender inequality in leadership exists is when women are under-represented, compared with men—particularly when women are well-represented at lower levels within an organization.

An underrepresentation of women in leadership can be perpetuated easily because the gender of organizational leaders affects the degree to which there is gender discrimination, gender supportive policies, and a gender diversity supportive climate within an organization ( Ostroff et al., 2012 ). Organizational members are likely to perceive that the climate for women is positive when women hold key positions in the organization ( Konrad et al., 2010 ). Specifically, the presence of women in key positions acts as a vivid symbol indicating that the organization supports gender diversity. Consistent with this, industries that have fewer female high status managers have a greater gender wage gap ( Cohen and Huffman, 2007 ). Further, women who work with a male supervisor perceive less organizational support, compared with those who work with a female supervisor ( Konrad et al., 2010 ). In addition, women who work in departments that are headed by a man report experiencing more gender discrimination, compared with their counterparts in departments headed by women ( Konrad et al., 2010 ). Some of these effects may be mediated by a similar-to-me bias ( Tsui and O’Reilly, 1989 ), where leaders set up systems that reward and promote individuals like themselves, which can lead to discrimination toward women when leaders are predominantly male ( Davison and Burke, 2000 ; Roth et al., 2012 ). Thus, gender inequalities in leadership affect women’s experiences in the workplace and their likelihood of facing discrimination.

The second contextual factor to consider is organizational structure. The formal structure of an organization is how an organization arranges itself and it consists of employee hierarchies, departments, etc. ( Grant, 2010 ). An example of institutional discrimination in the formal structure of an organization are job ladders, which are typically segregated by gender ( Perry et al., 1994 ). Such gender-segregated job ladders typically exist within different departments of the organization. Women belonging to gender-segregated networks within organizations ( Brass, 1985 ) have less access to information about jobs, less status, and less upward mobility within the organization ( Ragins and Sundstrom, 1989 ; McDonald et al., 2009 ). This is likely because in gender-segregated networks, women have less visibility and lack access to individuals with power ( Ragins and Sundstrom, 1989 ). In gender-segregated networks, it is also difficult for women to find female mentors because there is a lack of women in high-ranking positions ( Noe, 1988 ; Linehan and Scullion, 2008 ). Consequently, the organizational structure can be marked by gender inequalities that reduce women’s chances of reaching top-level positions in an organization.

Gender inequalities can be inherent in the structure of an organization when there are gender segregated departments, job ladders, and networks, which are intimately tied to gender discrimination in HR practices. For instance, if HR policies are designed such that pay is determined based on comparisons between individuals only within a department (e.g., department-wide reporting structure, job descriptions, performance evaluations), then this can lead to a devaluation of departments dominated by women. The overrepresentation of women in certain jobs leads to the lower status of those jobs; consequently, the pay brackets for these jobs decrease over time as the number of women in these jobs increase (e.g., Huffman and Velasco, 1997 ; Reilly and Wirjanto, 1999 ). Similarly, networks led by women are also devalued for pay. For example, in a study of over 2,000 managers, after controlling for performance, the type of job, and the functional area (e.g., marketing, sales, accounting), those who worked with female mangers had lower wages than those who worked with male managers ( Ostroff and Atwater, 2003 ). Thus, gender inequalities in an organization’s structure in terms of gender segregation have reciprocal effects with gender discrimination in HR policy and decision-making.

Another contextual factor in our model is organizational strategy and how institutional discrimination within strategy is related to discrimination in HR practices. Strategy is a plan, method, or process by which an organization attempts to achieve its objectives, such as being profitable, maintaining and expanding its consumer base, marketing strategy, etc. ( Grant, 2010 ). Strategy can influence the level of inequality within an organization ( Morrison and Von Glinow, 1990 ; Hunter et al., 2001 ). For example, Hooters, a restaurant chain, has a marketing strategy to sexually attract heterosexual males, which has led to discrimination in HR policy, decisions, and enactment because only young, good-looking women are considered qualified ( Schneyer, 1998 ). When faced with appearance-based discrimination lawsuits regarding their hiring policies, Hooters has responded by claiming that such appearance requirements are bona fide job qualifications given their marketing strategy (for reviews, see Schneyer, 1998 ; Adamitis, 2000 ). Hooters is not alone, as many other establishments attempt to attract male cliental by requiring their female servers to meet a dress code involving a high level of grooming (make-up, hair), a high heels requirement, and a revealing uniform ( McGinley, 2007 ). Thus, sexist HR policies and practices in which differential standards are applied to male and female employees can stem from a specific organizational strategy ( Westall, 2015 ).

We now consider institutional gender bias within organizational culture and how it relates to discrimination in HR policies. Organizational culture refers to collectively held beliefs, assumptions, and values held by organizational members ( Trice and Beyer, 1993 ; Schein, 2010 ). Cultures arise from the values of the founders of the organization and assumptions about the right way of doing things, which are learned from dealing with challenges over time ( Ostroff et al., 2012 ). The founders and leaders of an organization are the most influential in forming, maintaining, and changing culture over time (e.g., Trice and Beyer, 1993 ; Jung et al., 2008 ; Hartnell and Walumbwa, 2011 ). Organizational culture can contribute to gender inequalities because culture constrains people’s ideas of what is possible: their strategies of action ( Swidler, 1986 ). In other words, when people encounter a problem in their workplace, the organizational culture—who we are, how we act, what is right—will provide only a certain realm of behavioral responses. For instance, in organizational cultures marked by greater gender inequality, women may have lower hopes and expectations for promotion, and when they are discriminated against, may be less likely to imagine that they can appeal their outcomes ( Kanter, 1977 ; Cassirer and Reskin, 2000 ). Furthermore, in organizational cultures marked by gender inequality, organizational decision makers should hold stronger descriptive and proscriptive gender stereotypes: they should more strongly believe that women have less ability to lead, less career commitment, and less emotional stability, compared with men ( Eagly et al., 1992 ; Heilman, 2001 ). We expand upon this point later.

Other aspects of organizational culture that are less obviously related to gender can also lead to discrimination in HR practices. For instance, an organizational culture that emphasizes concerns with meritocracy, can lead organizational members to oppose HR efforts to increase gender equality. This is because when people believe that outcomes ought to go only to those who are most deserving, it is easy for them to fall into the trap of believing that outcomes currently do go to those who are most deserving ( Son Hing et al., 2011 ). Therefore, people will believe that men deserve their elevated status and women deserve their subordinated status at work ( Castilla and Benard, 2010 ). Furthermore, the more people care about merit-based outcomes, the more they oppose affirmative action and diversity initiatives for women ( Bobocel et al., 1998 ; Son Hing et al., 2011 ), particularly when they do not recognize that discrimination occurs against women in the absence of such policies ( Son Hing et al., 2002 ). Thus, a particular organizational culture can influence the level of discrimination against women in HR and prevent the adoption of HR policies that would mitigate gender discrimination.

Finally, gender inequalities can be seen in organizational climates. An organizational climate consists of organizational members’ shared perceptions of the formal and informal organizational practices, procedures, and routines ( Schneider et al., 2011 ) that arise from direct experiences of the organization’s culture ( Ostroff et al., 2012 ). Organizational climates tend to be conceptualized and studied as “climates for” an organizational strategy ( Schneider, 1975 ; Ostroff et al., 2012 ). Gender inequalities are most clearly reflected in two forms of climate: climates for diversity and climates for sexual harassment.

A positive climate for diversity exists when organizational members perceive that diverse groups are included, empowered, and treated fairly. When employees perceive a less supportive diversity climate, they perceive greater workplace discrimination ( Cox, 1994 ; Ragins and Cornwall, 2001 ; Triana and García, 2009 ), and experience lower organizational commitment and job satisfaction ( Hicks-Clarke and Iles, 2000 ), and higher turnover intentions ( Triana et al., 2010 ). Thus, in organizations with a less supportive diversity climate, women are more likely to leave the organization, which contributes to the underrepresentation of women in already male-dominated arenas ( Miner-Rubino and Cortina, 2004 ).

A climate for sexual harassment involves perceptions that the organization is permissive of sexual harassment. In organizational climates that are permissive of harassment, victims are reluctant to come forward because they believe that their complaints will not be taken seriously ( Hulin et al., 1996 ) and will result in negative personal consequences (e.g., Offermann and Malamut, 2002 ). Furthermore, men with a proclivity for harassment are more likely to act out these behaviors when permissive factors are present ( Pryor et al., 1993 ). Therefore, a permissive climate for sexual harassment can result in more harassing behaviors, which can lead women to disengage from their work and ultimately leave the organization ( Kath et al., 2009 ).

Organizational climates for diversity and for sexual harassment are inextricably linked to HR practices. For instance, a factor that leads to perceptions of diversity climates is whether the HR department has diversity training (seminars, workshops) and how much time and money is devoted to diversity efforts ( Triana and García, 2009 ). Similarly, a climate for sexual harassment depends on organizational members’ perceptions of how strict the workplace’s sexual harassment policy is, and how likely offenders are to be punished ( Fitzgerald et al., 1995b ; Hulin et al., 1996 ). Thus, HR policies, decision-making, and their enactment strongly affect gender inequalities in organizational climates and gender inequalities throughout an organization.

In summary, gender inequalities can exist within organizational structures, processes, and practices. However, organizational leadership, structure, strategy, culture, and climate do not inherently need to be sexist. It could be possible for these organizational structures, processes, and practices to promote gender equality. We return to this issue in the conclusion section.

The Effect of Hostile and Benevolent Sexism on How Organizational Decision Makers’ Conduct HR Practices

In this section, we explore how personal biases can affect personal discrimination in HR-related decisions and their enactment. Others have focused on how negative or hostile attitudes toward women predict discrimination in the workplace. However, we extend this analysis by drawing on ambivalent sexism theory, which involves hostile sexism (i.e., antagonistic attitudes toward women) and benevolent sexism (i.e., paternalistic attitudes toward women; see also Glick, 2013 ), both of which lead to discrimination against women.

Stereotyping processes are one possible explanation of how discrimination against women in male-typed jobs occurs and how women are relegated to the “pink ghetto” ( Heilman, 1983 ; Eagly and Karau, 2002 ; Rudman et al., 2012 ). Gender stereotypes, that is, expectations of what women and men are like, and what they should be like, are one of the most powerful schemas activated when people encounter others ( Fiske et al., 1991 ; Stangor et al., 1992 ). According to status characteristics theory, people’s group memberships convey important information about their status and their competence on specific tasks ( Berger et al., 1974 ; Berger et al., 1998 ; Correll and Ridgeway, 2003 ). Organizational decision makers will, for many jobs, have different expectations for men’s and women’s competence and job performance. Expectations of stereotyped-group members’ success can affect gender discrimination that occurs in HR-related decisions and enactment ( Roberson et al., 2007 ). For example, men are preferred over women for masculine jobs and women are preferred over men for feminine jobs ( Davison and Burke, 2000 ). Thus, the more that a workplace role is inconsistent with the attributes ascribed to women, the more a particular woman might be seen as lacking “fit” with that role, resulting in decreased performance expectations ( Heilman, 1983 ; Eagly and Karau, 2002 ).

Furthermore, because women are associated with lower status, and men with higher status, women experience backlash for pursuing high status roles (e.g., leadership) in the workplace ( Rudman et al., 2012 ). In other words, agentic women who act competitively and confidently in a leadership role, are rated as more socially deficient, less likeable and less hireable, compared with men who act the same way ( Rudman, 1998 ; Rudman et al., 2012 ). Interestingly though, if women pursue roles in the workplace that are congruent with traditional gender expectations, they will elicit positive reactions ( Eagly and Karau, 2002 ).

Thus, cultural, widely known, gender stereotypes can affect HR-related decisions. However, such an account does not take into consideration individual differences among organizational decision makers (e.g., managers, supervisors, or HR personnel) who may vary in the extent to which they endorse sexist attitudes or stereotypes. Individual differences in various forms of sexism (e.g., modern sexism, neosexism) have been demonstrated to lead to personal discrimination in the workplace ( Hagen and Kahn, 1975 ; Beaton et al., 1996 ; Hitlan et al., 2009 ). Ambivalent sexism theory builds on earlier theories of sexism by including attitudes toward women that, while sexist, are often experienced as positive in valence by perceivers and targets ( Glick and Fiske, 1996 ). Therefore, we draw on ambivalent sexism theory, which conceptualizes sexism as a multidimensional construct that encompasses both hostile and benevolent attitudes toward women ( Glick and Fiske, 1996 , 2001 ).

Hostile sexism involves antipathy and negative stereotypes about women, such as beliefs that women are incompetent, overly emotional, and sexually manipulative. Hostile sexism also involves beliefs that men should be more powerful than women and fears that women will try to take power from men ( Glick and Fiske, 1996 ; Cikara et al., 2008 ). In contrast, benevolent sexism involves overall positive views of women, as long as they occupy traditionally feminine roles. Individuals with benevolently sexist beliefs characterize women as weak and needing protection, support, and adoration. Importantly, hostile and benevolent sexism tend to go hand-in-hand (with a typical correlation of 0.40; Glick et al., 2000 ). This is because ambivalent sexists, people who are high in benevolent and hostile sexism, believe that women should occupy restricted domestic roles and that women are weaker than men are ( Glick and Fiske, 1996 ). Ambivalent sexists reconcile their potentially contradictory attitudes about women by acting hostile toward women whom they believe are trying to steal men’s power (e.g., feminists, professionals who show competence) and by acting benevolently toward traditional women (e.g., homemakers) who reinforce conventional gender relations and who serve men ( Glick et al., 1997 ). An individual difference approach allows us to build on the earlier models ( Heilman, 1983 ; Eagly and Karau, 2002 ; Rudman et al., 2012 ), by specifying who is more likely to discriminate against women and why.

Organizational decision makers who are higher (vs. lower) in hostile sexism should discriminate more against women in HR-related decisions ( Glick et al., 1997 ; Masser and Abrams, 2004 ). For instance, people high in hostile sexism have been found to evaluate candidates, who are believed to be women, more negatively and give lower employment recommendations for a management position, compared with matched candidates believed to be men ( Salvaggio et al., 2009 ) 1 . In another study, among participants who evaluated a female candidate for a managerial position, those higher in hostile sexism were less likely to recommend her for hire, compared with those lower in hostile sexism ( Masser and Abrams, 2004 ). Interestingly, among those evaluating a matched man for the same position, those higher (vs. lower) in hostile sexism were more likely to recommend him for hire ( Masser and Abrams, 2004 ). According to ambivalent sexism theorists ( Glick et al., 1997 ), because people high in hostile sexism see women as a threat to men’s status, they act as gatekeepers denying women access to more prestigious or masculine jobs.

Furthermore, when enacting HR policies and decisions, organizational decision makers who are higher (vs. lower) in hostile sexism should discriminate more against women in the form of gender harassment. Gender harassment can involve hostile terms of address, negative comments regarding women in management, sexist jokes, and sexist behavior ( Fitzgerald et al., 1995a , b ). It has been found that people higher (vs. lower) in hostile sexism have more lenient attitudes toward the sexual harassment of women, which involves gender harassment, in the workplace ( Begany and Milburn, 2002 ; Russell and Trigg, 2004 ). Furthermore, men who more strongly believe that women are men’s adversaries tell more sexist jokes to a woman ( Mitchell et al., 2004 ). Women also report experiencing more incivility (i.e., low level, rude behavior) in the workplace than men ( Björkqvist et al., 1994 ; Cortina et al., 2001 , 2002 ), which could be due to hostile attitudes toward women. In summary, the evidence is consistent with the idea that organizational decision makers’ hostile sexism should predict their gender harassing behavior during HR enactment; however, more research is needed for such a conclusion.

In addition, organizational decision makers who are higher (vs. lower) in benevolent sexism should discriminate more against women when making HR-related decisions. It has been found that people higher (vs. lower) in benevolent sexism are more likely to automatically associate men with high-authority and women with low-authority roles and to implicitly stereotype men as agentic and women as communal ( Rudman and Kilianski, 2000 ). Thus, organizational decision makers who are higher (vs. lower) in benevolent sexism should more strongly believe that women are unfit for organizational roles that are demanding, challenging, and requiring agentic behavior. Indeed, in studies of male MBA students those higher (vs. lower) in benevolent sexism assigned a fictional woman less challenging tasks than a matched man ( King et al., 2012 ). The researchers reasoned that this occurred because men are attempting to “protect” women from the struggles of challenging work. Although there has been little research conducted that has looked at benevolent sexism and gender discrimination in HR-related decisions, the findings are consistent with our model.

Finally, organizational decision makers who are higher (vs. lower) in benevolent sexism should engage in a complex form of gender discrimination when enacting HR policy and decisions that involves mixed messages: women are more likely to receive messages of positive verbal feedback (e.g., “stellar work,” “excellent work”) but lower numeric ratings on performance appraisals, compared with men ( Biernat et al., 2012 ). It is proposed that this pattern of giving women positive messages about their performance while rating them poorly reflects benevolent sexists’ desire to protect women from harsh criticism. However, given that performance appraisals are used for promotion decisions and that constructive feedback is needed for learning, managers’ unwillingness to give women negative verbal criticisms can lead to skill plateau and career stagnation.

Furthermore, exposure to benevolent sexism can harm women’s motivation, goals and performance. Adolescent girls whose mothers are high in benevolent (but not hostile) sexism display lower academic goals and academic performance ( Montañés et al., 2012 ). Of greater relevance to the workplace, when role-playing a job candidate, women who interacted with a hiring manager scripted to make benevolently sexist statements became preoccupied with thoughts about their incompetence, and consequently performed worse in the interview, compared with those in a control condition ( Dardenne et al., 2007 ). These findings suggest that benevolent sexism during the enactment of HR practices can harm women’s work-related motivation and goals, as well as their performance, which can result in a self-fulfilling prophecy ( Word et al., 1974 ). In other words, the low expectations benevolent sexists have of women can be confirmed by women as they are undermined by paternalistic messages.

Ambivalent sexism can operate to harm women’s access to jobs, opportunities for development, ratings of performance, and lead to stigmatization. However, hostile and benevolent sexism operate in different ways. Hostile sexism has direct negative consequences for women’s access to high status, male-typed jobs ( Masser and Abrams, 2004 ; Salvaggio et al., 2009 ), and it is related to higher rates of sexual harassment ( Fitzgerald et al., 1995b ; Mitchell et al., 2004 ; Russell and Trigg, 2004 ), which negatively affect women’s health, well-being, and workplace withdrawal behaviors ( Willness et al., 2007 ). In contrast, benevolent sexism has indirect negative consequences for women’s careers, for instance, in preventing access to challenging tasks ( King et al., 2012 ) and critical developmental feedback ( Vescio et al., 2005 ). Interestingly, exposure to benevolent sexism results in worsened motivation and cognitive performance, compared with exposure to hostile sexism ( Dardenne et al., 2007 ; Montañés et al., 2012 ). This is because women more easily recognize hostile sexism as a form of discrimination and inequality, compared with benevolent sexism, which can be more subtle in nature ( Dardenne et al., 2007 ). Thus, women can externalize hostile sexism and mobilize against it, but the subtle nature of benevolent sexism prevents these processes ( Kay et al., 2005 ; Becker and Wright, 2011 ). Therefore, hostile and benevolent sexism lead to different but harmful forms of HR discrimination. Future research should more closely examine their potentially different consequences.

Thus far, we have articulated how gender inequalities in organizational structures, processes, and practices can affect discrimination in HR policy and in HR-related decision-making and enactment. Furthermore, we have argued that organizational decision makers’ levels of hostile and benevolent sexism are critical factors leading to personal discrimination in HR-related decision-making and enactment, albeit in different forms. We now turn to an integration of these two phenomena.

The Effect of Organizational Structures, Processes, and Practices on Organizational Decision Makers’ Levels of Hostile and Benevolent Sexism

Organizational decision makers’ beliefs about men and women should be affected by the work environments in which they are embedded. Thus, when there are more gender inequalities within organizational structures, processes, and practices, organizational decision makers should have higher levels of hostile sexism and benevolent sexism. Two inter-related processes can account for this proposition: the establishment of who becomes and remains an organizational member, and the socialization of organizational members.

First, as organizations develop over time, forces work to attract, select, and retain an increasingly homogenous set of employees in terms of their hostile and benevolent sexism ( Schneider, 1983 , 1987 ). In support of this perspective, an individual’s values tend to be congruent with the values in his or her work environment (e.g., Holland, 1996 ; Kristof-Brown et al., 2005 ). People are attracted to and choose to work for organizations that have characteristics similar to their own, and organizations select individuals who are likely to fit with the organization. Thus, more sexist individuals are more likely to be attracted to organizations with greater gender inequality in leadership, structure, strategy, culture, climate, and HR policy; and they will be seen as a better fit during recruitment and selection. Finally, individuals who do not fit with the organization tend to leave voluntarily through the process of attrition. Thus, less (vs. more) sexist individuals would be more likely to leave a workplace with marked gender inequalities in organizational structures, processes, and practices. The opposite should be true for organizations with high gender equality. Through attraction, selection, and attrition processes it is likely that organizational members will become more sexist in a highly gender unequal organization and less sexist in a highly gender equal organization.

Second, socialization processes can change organizational members’ personal attributes, goals, and values to match those of the organization ( Ostroff and Rothausen, 1997 ). Organizational members’ receive both formal and informal messages about gender inequality—or equality—within an organization through their orientation and training, reading of organizational policy, perceptions of who rises in the ranks, how women (vs. men) are treated within the organization, as well as their perception of climates for diversity and sexual harassment. Socialization of organizational members over time has been shown to result in organizational members’ values and personalities changing to better match the values of the organization ( Kohn and Schooler, 1982 ; Cable and Parsons, 2001 ).

These socialization processes can operate to change organizational members’ levels of sexism. It is likely that within more sexist workplaces, people’s levels of hostile and benevolent sexism increase because their normative beliefs shift due to exposure to institutional discrimination against women, others’ sexist attitudes and behavior, and gender bias in culture and climate ( Schwartz and DeKeseredy, 2000 ; Ford et al., 2008 ; Banyard et al., 2009 ). These processes can also lead organizational decision makers to adopt less sexist attitudes in a workplace context marked by greater gender equality. Thus, organizational members’ levels of hostile and benevolent sexism can be shaped by the degree of gender inequalities in organizational structures, processes, and practices and by the sexism levels of their work colleagues.

In addition, organizational decision makers can be socialized to act in discriminatory ways without personally becoming more sexist. If organizational decision makers witness others acting in a discriminatory manner with positive consequences, or acting in an egalitarian way with negative consequences, they can learn to become more discriminatory in their HR practices through observational learning ( Bandura, 1977 , 1986 ). So, organizational decision makers could engage in personal discrimination without being sexist if they perceive that the fair treatment of women in HR would encounter resistance given the broader organizational structures, processes, and practices promoting gender inequality. Yet over time, given cognitive dissonance ( Festinger, 1962 ), it is likely that discriminatory behavior could induce attitude change among organizational decision makers to become more sexist.

Thus far we have argued that gender inequalities in organizational structures, processes, and practices, organizational decision makers’ sexist attitudes, and gender discrimination in HR practices can have reciprocal, reinforcing relationships. Thus, it may appear that we have created a model that is closed and determinate in nature; however, this would be a misinterpretation. In the following section, we outline how organizations marked by gender inequalities can reduce discrimination against women.

How to Reduce Gender Discrimination in Organizations

The model we present for understanding gender discrimination in HR practices is complex. We believe that such complexity is necessary to accurately reflect the realities of organizational life. The model demonstrates that many sources of gender inequality are inter-related and have reciprocal effects. By implication, there are no simple or direct solutions to reduce gender discrimination in organizations. Rather, this complex problem requires multiple solutions. In fact, as discussed by Gelfand et al. (2007) , if an organization attempts to correct discrimination in only one aspect of organizational structure, process, or practice, and not others, such change attempts will be ineffective due to mixed messages. Therefore, we outline below how organizations can reduce gender discrimination by focusing on (a) HR policies (i.e., diversity initiatives and family friendly policies) and closely related organizational structures, processes, and practices; (b) HR-related decision-making and enactment; as well as, (c) the organizational decision makers who engage in such actions.

Reducing Gender Discrimination in HR Policy and Associated Organizational Structures, Processes, and Practices

Organizations can take steps to mitigate discrimination in HR policies. As a first example, let us consider how an organization can develop, within its HR systems, diversity initiatives aimed at changing the composition of the workforce that includes policies to recruit, retain, and develop employees from underrepresented groups ( Jayne and Dipboye, 2004 ). Diversity initiatives can operate like affirmative action programs in that organizations track and monitor (a) the number of qualified candidates from different groups (e.g., women vs. men) in a pool, and (b) the number of candidates from each group hired or promoted. When the proportion of candidates from a group successfully selected varies significantly from their proportion in the qualified pool then action, such as targeted recruitment efforts, needs to be taken.

Importantly, such efforts to increase diversity can be strengthened by other HR policies that reward managers, who select more diverse personnel, with bonuses ( Jayne and Dipboye, 2004 ). Organizations that incorporate diversity-based criteria into their performance and promotion policies and offer meaningful incentives to managers to identify and develop successful female candidates for promotion are more likely to succeed in retaining and promoting diverse talent ( Murphy and Cleveland, 1995 ; Cleveland et al., 2000 ). However, focusing on short-term narrowly defined criteria, such as increasing the number of women hired, without also focusing on candidates’ merit and providing an adequate climate or support for women are unlikely to bring about any long-term change in diversity, and can have detrimental consequences for its intended beneficiaries ( Heilman et al., 1992 , 1997 ). Rather, to be successful, HR policies for diversity need to be supported by the other organizational structures, processes, and practices, such as strategy, leadership, and climate.

For instance, diversity initiatives should be linked to strategies to create a business case for diversity ( Jayne and Dipboye, 2004 ). An organization with a strategy to market to more diverse populations can justify that a more diverse workforce can better serve potential clientele ( Jayne and Dipboye, 2004 ). Alternatively, an organization that is attempting to innovate and grow might justify a corporate strategy to increase diversity on the grounds that diverse groups have multiple perspectives on a problem with the potential to generate more novel, creative solutions ( van Knippenberg et al., 2004 ). Furthermore, organizational leaders must convey strong support for the HR policies for them to be successful ( Rynes and Rosen, 1995 ). Given the same HR policy within an organization, leaders’ personal attitudes toward the policy affects the discrimination levels found within their unit ( Pryor, 1995 ; Pryor et al., 1995 ). Finally, diversity programs are more likely to succeed in multicultural organizations with strong climates for diversity ( Elsass and Graves, 1997 ; Jayne and Dipboye, 2004 ). An organization’s climate for diversity consists of employees’ shared perceptions that the organization’s structures, processes, and practices are committed to maintaining diversity and eliminating discrimination ( Nishii and Raver, 2003 ; Gelfand et al., 2007 ). In organizations where employees perceive a strong climate for diversity, diversity programs result in greater employee attraction and retention among women and minorities, at all levels of the organization ( Cox and Blake, 1991 ; Martins and Parsons, 2007 ).

As a second example of how HR policies can mitigate gender inequalities, we discuss HR policies to lessen employees’ experience of work-family conflict. Work-family conflict is a type of role conflict that workers experience when the demands (e.g., emotional, cognitive, time) of their work role interfere with the demands of their family role or vice versa ( Greenhaus and Beutell, 1985 ). Work-family conflict has the negative consequences of increasing employee stress, illness-related absence, and desire to turnover ( Grandey and Cropanzano, 1999 ). Importantly, women are more adversely affected by work-family conflict than men ( Martins et al., 2002 ). Work-family conflict can be exacerbated by HR policies that evaluate employees based on face time (i.e., number of hours present at the office), as a proxy for organizational commitment ( Perlow, 1995 ; Elsbach et al., 2010 ).

Formal family friendly HR policies can be adopted to relieve work-family conflict directly, which differentially assists women in the workplace. For instance, to reduce work-family conflict, organizations can implement HR policies such as flexible work arrangements, which involve flexible schedules, telecommuting, compressed work weeks, job-shares, and part-time work ( Galinsky et al., 2008 ). In conjunction with other family friendly policies, such as the provision of childcare, elderly care, and paid maternity leave, organizations can work to reduce stress and improve the retention of working mothers ( Burke, 2002 ).

Unfortunately, it has been found that the enactment of flexible work policies can still lead to discrimination. Organizational decision makers’ sexism can lead them to grant more flexible work arrangements to white men than to women and other minorities because white men are seen as more valuable ( Kelly and Kalev, 2006 ). To circumvent this, organizations need to formalize HR policies relating to flexible work arrangements ( Kelly and Kalev, 2006 ). For instance, formal, written policies should articulate who can adopt flexible work arrangements (e.g., employees in specific divisions or with specific job roles) and what such arrangements look like (e.g., core work from 10 am to 3 pm with flexible work hours from 7 to 10 am or from 3 to 6 pm). When the details of such policies are formally laid out, organizational decision makers have less latitude and therefore less opportunity for discrimination in granting access to these arrangements.

To be successful, family friendly HR policies should be tied to other organizational structures, processes, and practices such as organizational strategy, leadership, culture, and climate. A business case for flexible work arrangements can be made because they attract and retain top-talent, which includes women ( Baltes et al., 1999 ). Furthermore, organizational leaders must convey strong support for family friendly programs ( Jayne and Dipboye, 2004 ). Leaders can help bolster the acceptance of family friendly policies through successive interactions, communications, visibility, and role modeling with employees. For instance, a leader who sends emails at 2 o’clock in the morning is setting a different expectation of constant availability than a leader who never sends emails after 7:00 pm. Family friendly HR policies must also be supported by simultaneously changing the underlying organizational culture that promotes face time. Although it is difficult to change the culture of an organization, the leaders’ of the organization play an influential role in instilling such change because the behaviors of leaders are antecedents and triggers of organizational culture ( Kozlowski and Doherty, 1989 ; Ostroff et al., 2012 ). In summary, HR policies must be supported by other organizational structures, processes, and practices in order for these policies to be effective.

Adopting HR diversity initiative policies and family friendly policies can reduce gender discrimination and reshape the other organizational structures, processes, and practices and increase gender equality in them. Specifically, such policies, if successful, should increase the number of women in all departments and at all levels of an organization. Further, having more women in leadership positions signals to organizational members that the organization takes diversity seriously, affecting the diversity climate of the organization, and ultimately its culture ( Konrad et al., 2010 ). Thus, particular HR policies can reduce gender inequalities in all of the other organizational structures, processes, and practices.

Reducing Gender Discrimination in HR-Related Decision-Making and Enactment

A wealth of research demonstrates that an effective means of reducing personal bias by organizational decision makers in HR practices is to develop HR policies that standardize and objectify performance data (e.g., Konrad and Linnehan, 1995 ; Reskin and McBrier, 2000 ). To reduce discrimination in personnel decisions (i.e., employee hiring and promotion decisions) a job analysis should be performed to determine the appropriate knowledge skills and abilities needed for specific positions ( Fine and Cronshaw, 1999 ). This ensures that expectations about characteristics of the ideal employee for that position are based on accurate knowledge of the job and not gender stereotypes about the job ( Welle and Heilman, 2005 ). To reduce discrimination in performance evaluations, HR policies should necessitate the use of reliable measures based on explicit objective performance expectations and apply these practices consistently across all worker evaluations ( Bernardin et al., 1998 ; Ittner et al., 2003 ). Employees’ performance should be evaluated using behaviorally anchored rating scales ( Smith and Kendall, 1963 ) that allow supervisors to rate subordinates on examples of actual work behaviors. These evaluations should be done regularly, given that delays require retrieving memories of work performance and this process can be biased by gender stereotypes ( Sanchez and De La Torre, 1996 ). Finally, if greater gender differences are found on selection tests than on performance evaluations, then the use of such biased selection tests needs to be revisited ( Chung-Yan and Cronshaw, 2002 ). In summary, developing HR policies that standardize and objectify the process of employee/candidate evaluations can reduce personal bias in HR practices.

Importantly, the level of personal discrimination enacted by organizational decision makers can be reduced by formalizing HR policies, and by controlling the situations under which HR-related decisions are made. We have articulated how HR-related decisions involve social cognition and are therefore susceptible to biases introduced by the use of gender stereotypes. This can occur unwittingly by those who perceive themselves to be unprejudiced but who are affected by stereotypes or negative automatic associations nonetheless ( Chugh, 2004 ; Son Hing et al., 2008 ). For instance, when HR policies do not rely on objective criteria, and the context for evaluation is ambiguous, organizational decision makers will draw on gender (and other) stereotypes to fill in the blanks when evaluating candidates ( Heilman, 1995 , 2001 ). Importantly, the context can be constructed in such a way as to reduce these biases. For instance, organizational decision makers will make less biased judgments of others if they have more time available to evaluate others, are less cognitively busy ( Martell, 1991 ), have higher quality of information available about candidates, and are accountable for justifying their ratings and decisions ( Kulik and Bainbridge, 2005 ; Roberson et al., 2007 ). Thus, if they have the time, motivation, and opportunity to make well-informed, more accurate judgments, then discrimination in performance ratings can be reduced.

Reducing Organizational Decision Makers’ Sexism

Another means to reduce gender discrimination in HR-related decision-making and enactment is to focus directly on reducing the hostile and benevolent sexist beliefs of organizational decision makers. Interventions aimed at reducing these beliefs typically involve diversity training, such as a seminar, course, or workshop. Such training involves one or more sessions that involve interactive discussions, lectures, and practical assignments. During the training men and women are taught about sexism and how gender roles in society are socially constructed. Investigations have shown these workshop-based interventions are effective at reducing levels of hostile sexism but have inconsistent effects on benevolent sexism ( Case, 2007 ; de Lemus et al., 2014 ). The subtle, and in some ways positive nature of benevolent sexism makes it difficult to confront and reduce using such interventions. However, levels of benevolent sexism are reduced when individuals are explicitly informed about the harmful implications of benevolent sexism ( Becker and Swim, 2012 ). Unfortunately, these interventions have not been tested in organizational settings. So their efficacy in the field is unknown.

Gender inequality in organizations is a complex phenomenon that can be seen in HR practices (i.e., policies, decision-making, and their enactment) that affects the hiring, training, pay, and promotion of women. We propose that gender discrimination in HR-related decision-making and the enactment of HR practices stems from gender inequalities in broader organizational structures, processes, and practices, including HR policy but also leadership, structure, strategy, culture, and organizational climate. Moreover, reciprocal effects should occur, such that discriminatory HR practices can perpetuate gender inequalities in organizational leadership, structure, strategy, culture, and climate. Organizational decision makers also play an important role in gender discrimination. We propose that personal discrimination in HR-related decisions and enactment arises from organizational decision makers’ levels of hostile and benevolent sexism. While hostile sexism can lead to discrimination against women because of a desire to keep them from positions of power, benevolent sexism can lead to discrimination against women because of a desire to protect them. Finally, we propose that gender inequalities in organizational structures, processes, and practices affect organizational decision makers’ sexism through attraction, selection, socialization, and attrition processes. Thus, a focus on organizational structure, processes, and practices is critical.

The model we have developed extends previous work by Gelfand et al. (2007) in a number of substantive ways. Gelfand et al. (2007) proposed that aspects of the organization, that is, structure, organizational culture, leadership, strategy, HR systems, and organizational climates, are all interrelated and may contribute to or attenuate discrimination (e.g., racism, sexism, ableism, homophobia). First, we differ from their work by emphasizing that workplace discrimination is most directly attributable to HR practices. Consequently, we emphasize how inequalities in other organizational structures, processes, and practices affect institutional discrimination in HR policy. Second, our model differs from that of Gelfand et al. (2007) in that we focus on the role of organizational decision makers in the enactment of HR policy. The attitudes of these decision makers toward specific groups of employees are critical. However, the nature of prejudice differs depending on the target group ( Son Hing and Zanna, 2010 ). Therefore, we focus on one form of bias—sexism—in the workplace. Doing so, allows us to draw on more nuanced theories of prejudice, namely ambivalent sexism theory ( Glick and Fiske, 1996 ). Thus, third, our model differs from the work of Gelfand et al. (2007) by considering how dual beliefs about women (i.e., hostile and benevolent beliefs) can contribute to different forms of gender discrimination in HR practices. Fourth, we differ from Gelfand et al. (2007) by reviewing how organizational decision makers’ level of sexism within an organization is affected by organizational structures, processes, and practices via selection-attraction-attrition processes and through socialization processes.

However, the model we have developed is not meant to be exhaustive. There are multiple issues that we have not addressed but should be considered: what external factors feed into our model? What other links within the model might arise? What are the limits to its generalizability? What consequences derive from our model? How can change occur given a model that is largely recursive in nature? We focus on these issues throughout our conclusion.

In this paper, we have illustrated what we consider to be the dominant links in our model; however, additional links are possible. First, we do not lay out the factors that feed into our model, such as government regulations, the economy, their competitors, and societal culture. In future work, one could analyze the broader context that organizations operate in, which influences its structures, processes, and practices, as well as its members. For instance, in societies marked by greater gender inequalities, the levels of hostile and benevolent sexism of organizational decision makers will be higher ( Glick et al., 2000 ). Second, there is no link demonstrating how organizational decision makers who are more sexist have the capacity, even if they sit lower in the organizational hierarchy, to influence the amount of gender inequality in organizational structures, processes, and practices. It is possible for low-level managers or HR personnel who express more sexist sentiments to—through their own behavior—affect others’ perceptions of the tolerance for discrimination in the workplace ( Ford et al., 2001 ) and others’ perceptions of the competence and hireability of female job candidates ( Good and Rudman, 2010 ). Thus, organizational decision makers’ levels of hostile and benevolent sexism can affect organizational climates, and potentially other organizational structures, processes, and practices. Third, it is possible that organizational structures, processes, and practices could moderate the link between organizational decision makers’ sexist attitudes and their discriminatory behavior in HR practices. The ability of people to act in line with their attitudes depends on the strength of the constraints in the social situation and the broader context ( Lewin, 1935 , 1951 ). Thus, if organizational structures, processes, and practices clearly communicate the importance of gender equality then the discriminatory behavior of sexist organizational decision makers should be constrained. Accordingly, organizations should take steps to mitigate institutional discrimination by focusing on organizational structures, processes, and practices rather than focusing solely on reducing sexism in individual employees.

Our model does not consider how women’s occupational status is affected by their preferences for gender-role-consistent careers and their childcare and family responsibilities, which perhaps should not be underestimated (e.g., Manne, 2001 ; Hakim, 2006 ; Ceci et al., 2009 ). In other words, lifestyle preferences could contribute to gender differences in the workplace. However, it is important to consider how women’s agency in choosing occupations and managing work-life demands is constrained. Gender imbalances (e.g., in pay) in the workplace (e.g., Moss-Racusin et al., 2012 ; Sheltzer and Smith, 2014 ) and gender imbalances in the home (e.g., in domestic labor, childcare; Bianchi, 2000 ; Bianchi et al., 2000 ) shape the decisions that couples (when they consist of a woman and a man) make about how to manage dual careers. For instance, research has uncovered that women with professional degrees leave the labor force at roughly three times the rate of men ( Baker, 2002 ). Women’s decisions to interrupt their careers were difficult and were based on factors, such as workplace inflexibility, and their husbands’ lack of domestic responsibilities, rather than a preference to stay at home with their children ( Stone and Lovejoy, 2004 ). Thus, both factors inside and outside the workplace constrain and shape women’s career decisions.

Our model is derived largely from research that has been conducted in male-dominated organizations; however, we speculate that it should hold for female-dominated organizations. There is evidence that tokenism does not work against men in terms of their promotion potential in female-dominated environments. Rather, there is some evidence for a glass-escalator effect for men in female-dominated fields, such as nursing, and social work ( Williams, 1992 ). In addition, regardless of the gender composition of the workplace, men are advantaged, compared with women in terms of earnings and wage growth ( Budig, 2002 ). Finally, even in female-dominated professions, segregation along gender lines occurs in organizational structure ( Snyder and Green, 2008 ). Thus, the literature suggests that our model should hold for female-dominated environments.

Some might question if our model assumes that organizational decision makers enacting HR practices are men. It does not. There is evidence that decision makers who are women also discriminate against women (e.g., the Queen Bee phenomenon; Ellemers et al., 2004 ). Further, although men are higher in hostile sexism, compared with women ( Glick et al., 1997 , 2000 ), they are not necessarily higher in benevolent sexism ( Glick et al., 2000 ). More importantly, the effects of hostile and benevolent sexism are not moderated by participant gender ( Masser and Abrams, 2004 ; Salvaggio et al., 2009 ; Good and Rudman, 2010 ). Thus, those who are higher in hostile or benevolent sexism respond in a more discriminatory manner, regardless of whether they are men or women. Thus, organizational decision makers, regardless of their sex, should discriminate more against women in HR practices when they are higher in hostile or benevolent sexism.

In future work, the consequences of our model for women discriminated against in HR practices should be considered. The negative ramifications of sexism and discrimination on women are well known: physical and psychological stress, worse physical health (e.g., high blood pressure, ulcers, anxiety, depression; Goldenhar et al., 1998 ); lower job satisfaction, organizational commitment, and attachment to work ( Murrell et al., 1995 ; Hicks-Clarke and Iles, 2000 ); lower feelings of power and prestige ( Gutek et al., 1996 ); and performance decrements through stereotype threat ( Spencer et al., 1999 ). However, how might these processes differ depending on the proximal cause of the discrimination?

Our model lays out two potential paths by which women might be discriminated against in HR practices: institutional discrimination stemming from organizational structures, processes, and practices and personal discrimination stemming from organizational decision makers’ levels of sexism. In order for the potential stressor of stigmatization to lead to psychological and physical stress it must be seen as harmful and self-relevant ( Son Hing, 2012 ). Thus, if institutional discrimination in organizational structures, processes, and practices are completely hidden then discrimination might not cause stress reactions associated with stigmatization because it may be too difficult for women to detect ( Crosby et al., 1986 ; Major, 1994 ), and label as discrimination ( Crosby, 1984 ; Stangor et al., 2003 ). In contrast, women should be adversely affected by stigmatization in instances where gender discrimination in organizational structures, processes, and practices is more evident. For instance, greater perceptions of discrimination are associated with lower self-esteem in longitudinal studies ( Schmitt et al., 2014 ).

It might appear that we have created a model, which is a closed system, with no opportunities to change an organization’s trajectory: more unequal organizations will become more hierarchical, and more equal organizations will become more egalitarian. We do not believe this to be true. One potential impetus for organizations to become more egalitarian may be some great shock such as sex-based discrimination lawsuits that the organization either faces directly or sees its competitors suffer. Large corporations have been forced to settle claims of gender harassment and gender discrimination with payouts upward of $21 million ( Gilbert v. DaimlerChrysler Corp., 2004 ; LexisNexis, 2010 ; Velez, et al. v. Novartis Pharmaceuticals Crop, et al., 2010 ). Discrimination lawsuits are time consuming and costly ( James and Wooten, 2006 ), resulting in lower shares, lower public perceptions, higher absenteeism, and higher turnover ( Wright et al., 1995 ). Expensive lawsuits experienced either directly or indirectly should act as a big driver in the need for change.

Furthermore, individual women can work to avoid stigmatization. Women in the workplace are not simply passive targets of stereotyping processes. People belonging to stigmatized groups can engage in a variety of anti-stigmatization techniques, but their response options are constrained by the cultural repertoires available to them ( Lamont and Mizrachi, 2012 ). In other words, an organization’s culture will provide its members with a collective imaginary for how to behave. For instance, it might be unimaginable for a woman to file a complaint of sexual harassment if she knows that complaints are never taken seriously. Individuals do negotiate stigmatization processes; however, this is more likely when stigmatization is perceived as illegitimate and when they have the resources to do so ( Major and Schmader, 2001 ). Thus, at an individual level, people engage in strategies to fight being discriminated against but these strategies are likely more constrained for those who are most stigmatized.

Finally, possibly the most efficacious way for organizational members (men and women) to challenge group-based inequality and to improve the status of women as a whole is to engage in collective action (e.g., participate in unions, sign petitions, organize social movements, recruit others to join a movement; Klandermans, 1997 ; Wright and Lubensky, 2009 ). People are most likely to engage in collective action when they perceive group differences as underserved or illegitimate ( Wright, 2001 ). Such a sense of relative deprivation involves feelings of injustice and anger that prompt a desire for wide scale change ( van Zomeren et al., 2008 ). Interestingly, people are more likely to experience relative deprivation when inequalities have begun to be lessened, and thus their legitimacy questioned ( Crosby, 1984 ; Kawakami and Dion, 1993 ; Stangor et al., 2003 ). If organizational leaders respond to such demands for change by altering previously gender oppressive organizational structures, processes, and practices, this can, in people’s minds, open the door for additional changes. Therefore, changes to mitigate gender inequalities within any organizational structure, policy, or practice could start a cascade of transformations leading to a more equal organization for men and women.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

This research was supported by funding from the Canadian Institute for Advanced Research (CIFAR) awarded to Leanne S. Son Hing.

1 In this study, candidates were identified with initials and participants were asked to indicate the presumed gender of the candidate after evaluating them.

• Abrams K. (1991). Social construction, roving biologism, and reasonable women: a response to Professor Epstein. DePaul Law Rev. 41 1021–1040. [ Google Scholar ]
• Acker J. (1990). Hierarchies, jobs, bodies: a theory of gendered organizations. Gend. Soc. 4 139–158. 10.1177/089124390004002002 [ CrossRef ] [ Google Scholar ]
• Adamitis E. M. (2000). Appearance matters: a proposal to prohibit appearance discrimination in employment. Wash. Law Rev. 75 195–223. [ Google Scholar ]
• Adler N. E., Epel E. S., Castellazzo G., Ickovics J. R. (2000). Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy White women. Health Psychol. 19 586–592. 10.1037/0278-6133.19.6.586 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Baker J. G. (2002). The influx of women into legal professions: an economic analysis. Mon. Labor Rev. 125 12–24. [ Google Scholar ]
• Baltes B. B., Briggs T. E., Huff J. W., Wright J. A., Neuman G. A. (1999). Flexible and compressed workweek schedules: a meta-analysis of their effects on work-related criteria. J. Appl. Psychol. 84 496–513. 10.1037/0021-9010.84.4.496 [ CrossRef ] [ Google Scholar ]
• Bandura A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychol. Rev. 84 191–215. 10.1037/0033-295X.84.2.191 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bandura A. (1986). The explanatory and predictive scope of self-efficacy theory. J. Soc. Clin. Psychol. 4 359–373. 10.1521/jscp.1986.4.3.359 [ CrossRef ] [ Google Scholar ]
• Banyard V. L., Moynihan M. M., Crossman M. T. (2009). Reducing sexual violence on campus: the role of student leaders as empowered bystanders. J. Coll. Stud. Dev. 50 446–457. 10.1353/csd.0.0083 [ CrossRef ] [ Google Scholar ]
• Barling J., Dekker I., Loughlin C. A., Kelloway E. K., Fullagar C., Johnson D. (1996). Prediction and replication of the organizational and personal consequences of workplace sexual harassment. J. Manag. Psychol. 11 4–25. 10.1108/02683949610124771 [ CrossRef ] [ Google Scholar ]
• Baxter J., Wright E. O. (2000). The glass ceiling hypothesis: a comparative study of the United States, Sweden, and Australia. Gend. Soc. 14 275–294. 10.1177/089124300014002004 [ CrossRef ] [ Google Scholar ]
• Beaton A. M., Tougas F., Joly S. (1996). Neosexism among male managers: is it a matter of numbers? J. Appl. Soc. Psychol. 26 2189–2203. 10.1111/j.1559-1816.1996.tb01795.x [ CrossRef ] [ Google Scholar ]
• Becker J. C., Swim J. K. (2012). Reducing endorsement of benevolent and modern sexist beliefs: differential effects of addressing harm versus pervasiveness of benevolent sexism. Soc. Psychol. 43 127–137. 10.1027/1864-9335/a000091 [ CrossRef ] [ Google Scholar ]
• Becker J. C., Wright S. C. (2011). Yet another dark side of chivalry: benevolent sexism undermines and hostile sexism motivates collective action for social change. J. Pers. Soc. Psychol. 101 62–77. 10.1037/a0022615 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Begany J. J., Milburn M. A. (2002). Psychological predictors of sexual harassment: authoritarianism, hostile sexism, and rape myths. Psychol. Men Masc. 3 119–126. 10.1037/1524-9220.3.2.119 [ CrossRef ] [ Google Scholar ]
• Berdhal J. L. (2007). The sexual harassment of uppity women. J. Appl. Psychol. 92 425–437. 10.1037/0021-9010.92.2.425 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Berger J., Conner T. L., Fisek M. H. (eds). (1974). Expectation States Theory: A Theoretical Research Program. Cambridge, MA: Winthrop Publishers. [ Google Scholar ]
• Berger J., Fisek M. H., Norman R. Z., Wagner D. G. (1998). “Formation of reward expectations in status situations,” in Status, Power, and Legitimacy eds Berger J., Zelditch M., Jr. (New Brunswick, NJ: Transaction Publishers; ) 121–153. [ Google Scholar ]
• Bernardin H. J., Hagan C. M., Kane J. S., Villanova P. (1998). “Effective performance management: a focus on precision, customers, and situational constraints,” in Performance Appraisal: State of the Art in Practice ed. Smither J. W. (San Francisco, CA: Jossey-Bass; ) 3–48. [ Google Scholar ]
• Bianchi S. M. (2000). Maternal employment and time with children: dramatic change or surprising continuity? Demography 47 401–414. 10.1353/dem.2000.0001 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bianchi S. M., Milkie M. A., Sayer L. C., Robinson J. P. (2000). Is anyone doing the housework? Trends in the gender division of household labor. Soc. Forces 79 191–228. 10.1093/sf/79.1.191 [ CrossRef ] [ Google Scholar ]
• Biernat M., Tocci M. J., Williams J. C. (2012). The language of performance evaluations: gender-based shifts in content and consistency of judgment. Soc. Psychol. Personal. Sci. 3 186–192. 10.1177/1948550611415693 [ CrossRef ] [ Google Scholar ]
• Björkqvist K., Österman K., Hjelt-Bäck M. (1994). Aggression among university employees. Aggress. Behav. 20 173–184. 10.1002/1098-2337(1994)20:3<173::AID-AB2480200304>3.0.CO;2-D [ CrossRef ] [ Google Scholar ]
• Blau F. D., DeVaro J. (2007). New evidence on gender differences in promotion rates: an empirical analysis of a sample of new hires. Ind. Relat. 46 511–550. 10.1111/j.1468-232X.2007.00479.x [ CrossRef ] [ Google Scholar ]
• Bobocel R. D., Son Hing L. S., Davey L. M., Stanley D. J., Zanna M. P. (1998). Justice-based opposition to social policies: is it genuine? J. Pers. Soc. Psychol. 75 653–669. 10.1037/0022-3514.75.3.653 [ CrossRef ] [ Google Scholar ]
• Boldry J., Wood W., Kashy D. A. (2001). Gender stereotypes and the evaluation of men and women in military training. J. Soc. Issues 57 689–705. 10.1111/0022-4537.00236 [ CrossRef ] [ Google Scholar ]
• Borrel C., Artazcoz L., Gil-González D., Pérez G., Rohlfs I., Pérez K. (2010). Perceived sexism as a health determinant in Spain. J. Womens Health 19 741–750. 10.1089/jwh.2009.1594 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Branscombe N. R. (1998). Thinking about one’s gender group’s privileges or disadvantages: consequences for well-being in women and men. Br. J. Soc. Psychol. 37 167–184. 10.1111/j.2044-8309.1998.tb01163.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Brass D. J. (1985). Men’s and women’s networks: a study of interaction patterns and influence in an organization. Acad. Manag. J. 28 327–343. 10.2307/256204 [ CrossRef ] [ Google Scholar ]
• Budig M. J. (2002). Male advantage and the gender composition of jobs: who rides the glass escalator? Soc. Probl. 49 258–277. 10.1525/sp.2002.49.2.258 [ CrossRef ] [ Google Scholar ]
• Burke R. J. (2002). Organizational values, job experiences and satisfactions among managerial and professional women and men: advantage men? Women Manag. Rev. 17 228–236. 10.1108/09649420210433184 [ CrossRef ] [ Google Scholar ]
• Cable D. M., Parsons C. K. (2001). Socialization tactics and person-organization fit. Pers. Psychol. 54 1–23. 10.1111/j.1744-6570.2001.tb00083.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Case K. A. (2007). Raising male privilege awareness and reducing sexism: an evaluation of diversity courses. Psychol. Women Q. 31 426–435. 10.1111/j.1471-6402.2007.00391.x [ CrossRef ] [ Google Scholar ]
• Cassirer N., Reskin B. (2000). High Hopes: organizational position, employment experiences, and women and men’s promotion aspirations. Work Occup. 27 438–463. 10.1177/0730888400027004002 [ CrossRef ] [ Google Scholar ]
• Castilla E. J., Benard S. (2010). The paradox of meritocracy in organizations. Admin. Sci. Q. 55 543–576. 10.2189/asqu.2010.55.4.543 [ CrossRef ] [ Google Scholar ]
• Ceci S. J., Williams W. M., Barnett S. M. (2009). Women’s underrepresentation in science: sociocultural and biological considerations. Psychol. Bull. 135 218–261. 10.1037/a0014412 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chemers M. M. (1997). An Integrative Theory of Leadership. Mahwah, NJ: Lawrence Erlbaum Associates. [ Google Scholar ]
• Chugh D. (2004). Societal and managerial implications of implicit social cognition: why milliseconds matter. Soc. Justice Res. 17 203–222. 10.1023/B:SORE.0000027410.26010.40 [ CrossRef ] [ Google Scholar ]
• Chung-Yan G. A., Cronshaw S. F. (2002). A critical re-examination and analysis of cognitive ability tests using the Thorndike model of fairness. J. Occup. Organ. Psychol. 75 489–509. 10.1348/096317902321119709 [ CrossRef ] [ Google Scholar ]
• Cikara M., Lee T. L., Fiske S. T., Glick P. (2008). “Ambivalent sexism at home and at work: how attitudes toward women in relationships foster exclusion in the public sphere,” in Social and Psychological Bases of Ideology and System Justification eds Jost J. T., Kay A. C., Thorisdottir H. (New York: Oxford University Press; ) 444–462. [ Google Scholar ]
• Cleveland J. N., Stockdale M., Murphy K. R., Gutek B. A. (2000). Women and Men in Organizations: Sex and Gender Issues at Work. Mahwah, NJ: Lawrence Erlbaum Associates. [ Google Scholar ]
• Cohen P. N., Huffman M. L. (2007). Working for the woman? Female managers and the gender wage gap. Am. Sociol. Rev. 72 681–704. 10.1177/000312240707200502 [ CrossRef ] [ Google Scholar ]
• Cohen-Charash Y., Spector P. E. (2001). The role of justice in organizations: a meta-analysis. Organ. Behav. Hum. Decis. Process. 86 278–321. 10.1006/obhd.2001.2958 [ CrossRef ] [ Google Scholar ]
• Correll S. J., Ridgeway C. L. (2003). “Expectation states theory,” in Handbook of Social Psychology ed. Delamater J. (New York, NY: Kluwer Academic Press; ) 29–51. [ Google Scholar ]
• Cortina L. M., Lonsway K. A., Magley V. J., Freeman L. V., Collinsworth L. L., Hunter M., et al. (2002). What’s gender got to do with it? Incivility in the federal courts. Law Soc. Inq. 27 235–270. 10.1111/j.1747-4469.2002.tb00804.x [ CrossRef ] [ Google Scholar ]
• Cortina L. M., Magley V. J., Williams J. H., Langhout R. D. (2001). Incivility in the workplace: incidence and impact. J. Occup. Health Psychol. 6 64–80. 10.1037/1076-8998.6.1.64 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cox T. (1994). Cultural Diversity in Organizations: Theory, Research, and Practice. San Francisco, CA: Berrett-Koehler Publishers. [ Google Scholar ]
• Cox T. H., Blake S. (1991). Managing cultural diversity: implications for organizational competitiveness. Executive 5 45–56. 10.5465/AME.1991.4274465 [ CrossRef ] [ Google Scholar ]
• Cox T. H., Harquail C. V. (1991). Career paths and career success in the early career stages of male and female MBAs. J. Vocat. Behav. 39 54–75. 10.1016/0001-8791(91)90004-6 [ CrossRef ] [ Google Scholar ]
• Crocker D., Kalemba V. (1999). The incidence and impact of women’s experiences of sexual harassment in Canadian workplaces. Can. Rev. Sociol. 36 541–558. 10.1111/j.1755-618X.1999.tb00963.x [ CrossRef ] [ Google Scholar ]
• Crosby F. (1984). The denial of personal discrimination. Am. Behav. Sci. 27 371–386. 10.1177/000276484027003008 [ CrossRef ] [ Google Scholar ]
• Crosby F., Clayton S., Alksnis O., Hemker K. (1986). Cognitive biases in the perception of discrimination: the importance of format. Sex Roles 14 637–646. 10.1007/BF00287694 [ CrossRef ] [ Google Scholar ]
• Cuddy A. J. C., Fiske S. T., Glick P. (2004). When professionals become mothers, warmth doesn’t cut the ice. J. Soc. Issues 60 701–718. 10.1111/j.0022-4537.2004.00381.x [ CrossRef ] [ Google Scholar ]
• Dardenne B., Dumont M., Bollier T. (2007). Insidious dangers of benevolent sexism: consequences for women’s performance. J. Pers. Soc. Psychol. 93 764–779. 10.1037/0022-3514.93.5.764 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Davison H. K., Burke M. J. (2000). Sex discrimination in simulated employment contexts: a meta-analytic investigation. J. Vocat. Behav. 56 225–248. 10.1006/jvbe.1999.1711 [ CrossRef ] [ Google Scholar ]
• de Lemus S., Navarro L., Velázquez M. J., Ryan E., Megías J. L. (2014). From sex to gender: a university intervention to reduce sexism in Argentina, Spain, and El Salvador. J. Soc. Issues 70 741–762. 10.1111/josi.12089 [ CrossRef ] [ Google Scholar ]
• De Pater I. E., Van Vianen A. E. M., Bechtoldt M. N. (2010). Gender differences in job challenge: a matter of task allocation. Gend. Work Organ. 17 433–453. 10.1111/j.1468-0432.2009.00477.x [ CrossRef ] [ Google Scholar ]
• Durden G. C., Gaynor P. E. (1998). More on the cost of being other than white and male. Am. J. Econ. Sociol. 57 95–103. 10.1111/j.1536-7150.1998.tb03259.x [ CrossRef ] [ Google Scholar ]
• Eagly A. H., Carli L. L. (2007). Through the Labyrinth: The Truth about How Women become Leaders. Boston, MA: Harvard Business School Publishing. [ Google Scholar ]
• Eagly A. H., Karau S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychol. Rev. 109 573–598. 10.1037/0033-295X.109.3.573 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Eagly A. H., Makhijani M. G., Klonsky B. G. (1992). Gender and the evaluation of leaders: a meta-analysis. Psychol. Bull. 111 3–22. 10.1037/0033-2909.111.1.3 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ellemers N., Heuvel H., Gilder D., Maass A., Bonvini A. (2004). The underrepresentation of women in science: differential commitment or the queen bee syndrome? Br. J. Soc. Psychol. 43 315–338. 10.1348/0144666042037999 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Elsass P. M., Graves L. M. (1997). Demographic diversity in decision-making groups: the experiences of women and people of color. Acad. Manag. Rev. 22 946–973. 10.5465/AMR.1997.9711022111 [ CrossRef ] [ Google Scholar ]
• Elsbach K. D., Cable D. M., Sherman J. W. (2010). How passive ‘face time’ affects perceptions of employees: evidence of spontaneous trait inference. Hum. Relat. 63 735–760. 10.1177/0018726709353139 [ CrossRef ] [ Google Scholar ]
• Festinger L. (1962). A Theory of Cognitive Dissonance. Stanford, CA: Stanford University Press. [ Google Scholar ]
• Fine S. A., Cronshaw S. F. (1999). Functional Job Analysis: A Foundation for Human Resources Management. Mahwah, NJ: Lawrence Erlbaum Associates, Inc. [ Google Scholar ]
• Firth M. (1982). Sex discrimination in job opportunities for women. Sex Roles 8 891–901. 10.1007/BF00287858 [ CrossRef ] [ Google Scholar ]
• Fiske A. P., Haslam N., Fiske S. T. (1991). Confusing one person with another: what errors reveal about the elementary forms of social relations. J. Pers. Soc. Psychol. 60 656–674. 10.1037/0022-3514.60.5.656 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fiske S. T., Cuddy A. J. C., Glick P., Xu J. (2002). A model of (often mixed) stereotype content: competence and warmth respectively follow from perceived status and competition. J. Pers. Soc. Psychol. 82 878–902. 10.1037//0022-3514.82.6.878 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fiske S. T., Xu J., Cuddy A. J. C., Glick P. (1999). (Dis)respecting versus (dis)liking: status and interdependence predict ambivalent stereotypes of competence and warmth. J. Soc. Issues 55 473–489. 10.1111/0022-4537.00128 [ CrossRef ] [ Google Scholar ]
• Fitzgerald L. F., Gelfand M. J., Drasgow F. (1995a). Measuring sexual harassment: theoretical and psychometric advances. Basic Appl. Soc. Psychol. 17 425–445. 10.1207/s15324834basp1704_2 [ CrossRef ] [ Google Scholar ]
• Fitzgerald L. F., Hulin C. L., Drasgow F. (1995b). “The antecedents and consequences of sexual harassment in organizations: an integrated model,” in Job Stress in a Changing Workforce: Investigating Gender, Diversity, and Family Issues eds Keita G., Hurrell J., Jr. (Washington, DC: American Psychological Association; ) 55–73. [ Google Scholar ]
• Fitzgerald L. F., Shullman S. L., Bailey N., Richards M., Swecker J., Gold Y., et al. (1988). The incidence and dimensions of sexual harassment in academia and the workplace. J. Vocat. Behav. 32 152–175. 10.1016/0001-8791(88)90012-7 [ CrossRef ] [ Google Scholar ]
• Ford T. E., Boxer C. F., Armstrong J., Edel J. R. (2008). More than “just a joke”: the prejudice-releasing function of sexist humor. Pers. Soc. Psychol. Bull. 34 159–170. 10.1177/0146167207310022 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ford T. E., Wentzel E. R., Lorion J. (2001). Effects of exposure to sexist humor on perceptions of normative tolerance of sexism. Eur. J. Soc. Psychol. 31 677–691. 10.1002/ejsp.56 [ CrossRef ] [ Google Scholar ]
• Fuegen K., Biernat M., Haines E., Deaux K. (2004). Mothers and fathers in the workplace: how gender and parental status influence judgements of job-related competence. J. Soc. Issues 60 737–754. 10.1111/j.0022-4537.2004.00383.x [ CrossRef ] [ Google Scholar ]
• Galinsky E., Bond J., Sakai K. (2008). 2008 National Study of Employers. Available at: http://familiesandwork.org/site/research/reports/2008nse.pdf [ Google Scholar ]
• Gelfand M. J., Nishii L. H., Raver J. L., Schneider B. (2007). Discrimination in Organizations: An Organizational-Level Systems Perspective (CAHRS Working Paper #07-08). Ithaca, NY: Cornell University. Retrieved from Cornell University, School of Industrial and Labor Relations, Center for Advanced Human Resource Studies. [ Google Scholar ]
• Gerhart B., Rynes S. (1991). Determinants and consequences of salary negotiations by male and female MBA graduates. J. Appl. Psychol. 76 256–262. 10.1037/0021-9010.76.2.256 [ CrossRef ] [ Google Scholar ]
• Gilbert v. DaimlerChrysler Corp. (2004). 470 Mich. 749, 685 N.W.2d 391 2004 Lansing, MI: Supreme Court of Michigan. [ Google Scholar ]
• Glass J. (2004). Blessing or curse? Work-family policies and mother’s wage growth over time. Work Occup. 31 367–394. 10.1177/0730888404266364 [ CrossRef ] [ Google Scholar ]
• Glick P. (2013). “BS at work: how benevolent sexism undermines women and justifies backlash,” in Paper Presented at the Harvard Business School symposium Gender & Work: Challenging Conventional Wisdom Boston, MA. [ Google Scholar ]
• Glick P., Diebold J., Bailey-Werner B., Zhu L. (1997). The two faces of Adam: ambivalent sexism and polarized attitudes toward women. Pers. Soc. Psychol. Bull. 23 1323–1334. 10.1177/01461672972312009 [ CrossRef ] [ Google Scholar ]
• Glick P., Fiske S. T. (1996). The ambivalent sexism inventory: differentiating hostile and benevolent sexism. J. Pers. Soc. Psychol. 70 491–512. 10.1037/0022-3514.70.3.491 [ CrossRef ] [ Google Scholar ]
• Glick P., Fiske S. T. (2001). An ambivalent alliance: hostile and benevolent sexism as complementary justifications for gender inequality. Am. Psychol. 56 109–118. 10.1037/0003-066X.56.2.109 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Glick P., Fiske S. T., Mladinic A., Saiz J. L., Abrams D., Masser B., et al. (2000). Beyond prejudice as simple antipathy: hostile and benevolent sexism across culture. J. Pers. Soc. Psychol. 79 763–775. 10.1037/0022-3514.79.5.763 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Goldberg P. (1968). Are women prejudiced against women? Transaction 5 316–322. [ Google Scholar ]
• Goldenhar L. M., Swanson N. G., Hurrell J. J., Jr., Ruder A., Deddens J. (1998). Stressors and adverse outcomes for female construction workers. J. Occup. Health Psychol. 3 19–32. 10.1037/1076-8998.3.1.19 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Good J. J., Rudman L. A. (2010). When female applicants meet sexist interviewers: the costs of being a target of benevolent sexism. Sex Roles 62 481–493. 10.1007/s11199-009-9685-6 [ CrossRef ] [ Google Scholar ]
• Grandey A. A., Cropanzano R. (1999). The conservation of resources model applied to work-family conflict and strain. J. Vocat. Behav. 54 350–370. 10.1006/jvbe.1998.1666 [ CrossRef ] [ Google Scholar ]
• Grant R. M. (2010). Contemporary Strategy Analysis, Seventh Edition. New York, NY: Wiley. [ Google Scholar ]
• Greenhaus J. H., Beutell N. J. (1985). Sources of conflict between work and family roles. Acad. Manag. Rev. 10 76–88. 10.5465/AMR.1985.4277352 [ CrossRef ] [ Google Scholar ]
• Gutek B. A., Cohen A. G., Tsui A. (1996). Reactions to perceived sex discrimination. Hum. Relat. 49 791–813. 10.1177/001872679604900604 [ CrossRef ] [ Google Scholar ]
• Hagen R. L., Kahn A. (1975). Discrimination against competent women. J. Appl. Soc. Psychol. 5 362–376. 10.1111/j.1559-1816.1975.tb00688.x [ CrossRef ] [ Google Scholar ]
• Hakim C. (2006). Women, careers, and work-life preferences. Br. J. Guid. Counc. 34 279–294. 10.1080/03069880600769118 [ CrossRef ] [ Google Scholar ]
• Hartnell C. A., Walumbwa F. O. (2011). “Transformational leadership and organizational culture,” in The Handbook of Organizational Culture and Climate eds Ashkanasy N. M., Wilderom C. P. M., Peterson M. F. (Thousand Oaks, CA: Sage Publications; ) 225–248. [ Google Scholar ]
• Hebl M. R., King E. B., Glick P., Singletary S. L., Kazama S. (2007). Hostile and benevolent reactions toward pregnant women: complementary interpersonal punishments and rewards that maintain traditional roles. J. Appl. Psychol. 92 1499–1511. 10.1037/0021-9010.92.6.1499 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Heilman M. E. (1983). “Sex bias in work settings: the lack of fit model,” in Research in Organizational Behavior Vol. 5 eds Staw B., Cummings L. (Greenwich, CT: JAI press; ) 269–298. [ Google Scholar ]
• Heilman M. E. (1995). Sex stereotypes and their effects in the workplace: what we know and what we don’t know. J. Soc. Behav. Pers. 10 3–26. [ Google Scholar ]
• Heilman M. E. (2001). Description and prescription: how gender stereotypes prevent women’s ascent up the organizational ladder. J. Soc. Issues 57 657–674. 10.1111/0022-4537.00234 [ CrossRef ] [ Google Scholar ]
• Heilman M. E., Block C. J., Lucas J. A. (1992). Presumed incompetent? Stigmatization and affirmative action efforts. J. Appl. Psychol. 77 536–544. 10.1037/0021-9010.77.4.536 [ CrossRef ] [ Google Scholar ]
• Heilman M. E., Block C. J., Stathatos P. (1997). The affirmative action stigma of incompetence: effects of performance information ambiguity. Acad. Manag. J. 40 603–625. 10.2307/257055 [ CrossRef ] [ Google Scholar ]
• Heilman M., Okimoto T. G. (2007). Why are women penalized for success at male tasks? The implied communality deficit. J. Appl. Psychol. 92 81–92. 10.1037/0021-9010.92.1.81 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Heilman M., Okimoto T. G. (2008). Motherhood: a potential source of bias in employment decisions. J. Appl. Psychol. 93 189–198. 10.1037/0021-9010.93.1.189 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hicks-Clarke D., Iles P. (2000). Climate for diversity and its effects on career and organisational attitudes and perceptions. Person. Rev. 29 324–345. 10.1108/00483480010324689 [ CrossRef ] [ Google Scholar ]
• Hitlan R. T., Pryor J. B., Hesson-McInnis M. S., Olson M. (2009). Antecedents of gender harassment: an analysis of person and situation factors. Sex Roles 61 794–807. 10.1007/s11199-009-9689-2 [ CrossRef ] [ Google Scholar ]
• Holland J. L. (1996). Exploring careers with a typology: what we have learned and some new directions. Am. Psychol. 51 397–406. 10.1037/0003-066X.51.4.397 [ CrossRef ] [ Google Scholar ]
• Hough L. M., Oswald F. L., Ployhart R. E. (2001). Determinants, detection, and amelioration of adverse impact in personnel selection procedures: issues, evidence, and lessons learned. Int. J. Sel. Assess. 9 152–194. 10.1111/1468-2389.00171 [ CrossRef ] [ Google Scholar ]
• House R. J., Aditya R. N. (1997). The social scientific study of leadership: quo vadis? J. Manag. 23 409–473. 10.1177/014920639702300306 [ CrossRef ] [ Google Scholar ]
• Huffman M. L., Velasco S. C. (1997). When more is less: sex composition, organizations, and earnings in U.S. firms . Work Occup. 24 214–244. 10.1177/0730888497024002005 [ CrossRef ] [ Google Scholar ]
• Hulin C. L., Fitzgerald L. F., Drasgow F. (1996). “Organizational influences on sexual harassment,” in Sexual Harassment in the Workplace: Perspectives, Frontiers, and Response Strategies. Women and Work: A Research and Policy Series Vol. 5 ed. Stockdale M. S. (Thousand Oaks, CA: Sage Publications; ) 127–150. [ Google Scholar ]
• Hunter J. E., Schmidt F. L., Jackson G. B. (1982). Meta-Analysis: Cumulating Research Findings Across Studies. Thousand Oaks, CA: Sage Publications. [ Google Scholar ]
• Hunter L. W., Bernhardt A., Hughes K. L., Skuratowicz E. (2001). It’s not just the ATMs: technology, firm strategies, jobs, and earnings in retail banking. Ind. Labor Relat. Rev. 54 402–424. 10.1177/001979390105400222 [ CrossRef ] [ Google Scholar ]
• Ittner C. D., Larcker D. F., Meyer M. W. (2003). Subjectivity and the weighting of performance measures: evidence from a balanced scorecard. Account. Rev. 78 725–758. 10.2308/accr.2003.78.3.725 [ CrossRef ] [ Google Scholar ]
• James E. H., Wooten L. P. (2006). Diversity crises: how firms manage discrimination lawsuits. Acad. Manag. J. 49 1103–1118. 10.5465/AMJ.2006.23478091 [ CrossRef ] [ Google Scholar ]
• Jayne M. E., Dipboye R. L. (2004). Leveraging diversity to improve business performance: research findings and recommendations for organizations. Hum. Resour. Manag. 43 409–424. 10.1002/hrm.20033 [ CrossRef ] [ Google Scholar ]
• Jung D., Wu A., Chow C. W. (2008). Towards understanding the direct and indirect effects of CEOs’ transformational leadership on firm innovation. Leadersh. Q. 19 582–594. 10.1016/j.leaqua.2008.07.007 [ CrossRef ] [ Google Scholar ]
• Kanter R. M. (1977). Men and Women of the Corporation. New York, NY: Basic Books. [ Google Scholar ]
• Kath L. M., Swody C. A., Magley V. J., Bunk J. A., Gallus J. A. (2009). Cross-level, three-way interactions among work-group climate, gender, and frequency of harassment on morale and withdrawal outcomes of sexual harassment. J. Occup. Organ. Psychol. 82 159–182. 10.1348/096317908X299764 [ CrossRef ] [ Google Scholar ]
• Kawakami K., Dion K. L. (1993). The impact of salient self-identities on relative deprivation and action intentions. Eur. J. Soc. Psychol. 23 525–540. 10.1002/ejsp.2420230509 [ CrossRef ] [ Google Scholar ]
• Kay A. C., Jost J. T., Young S. (2005). Victim derogation and victim enhancement as alternate routes to system justification. Psychol. Sci. 16 240–246. 10.1111/j.0956-7976.2005.00810.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kelly E. L., Kalev A. (2006). Managing flexible work arrangements in US organizations: formalized discretion or a ‘right to ask’. Soc. Econ. Rev. 4 379–416. 10.1093/ser/mwl001 [ CrossRef ] [ Google Scholar ]
• King E. B., Botsford W., Hebl M. R., Kazama S., Dawson J. F., Perkins A. (2012). Benevolent sexism at work: gender differences in the distribution of challenging developmental experiences. J. Manag. 38 1835–1866. 10.1177/0149206310365902 [ CrossRef ] [ Google Scholar ]
• Klandermans B. (1997). The Social Psychology of Protest. Oxford: Basic Blackwell. [ Google Scholar ]
• Kohn M. L., Schooler C. (1982). Job conditions and personality: a longitudinal assessment of their reciprocal effects. Am. J. Sociol. 87 1257–1286. 10.1086/227593 [ CrossRef ] [ Google Scholar ]
• Konrad A. M., Cannings K., Goldberg C. B. (2010). Asymmetrical demography effects on psychological climate for gender diversity: differential effects of leader gender and work unit gender composition among Swedish doctors. Hum. Relat. 63 1661–1685. 10.1177/0018726710369397 [ CrossRef ] [ Google Scholar ]
• Konrad A. M., Linnehan F. (1995). Formalized HRM structures: coordinating equal employment opportunity or concealing organizational practices? Acad. Manag. J. 38 787–820. 10.2307/256746 [ CrossRef ] [ Google Scholar ]
• Kozlowski S. W., Doherty M. L. (1989). Integration of climate and leadership: examination of a neglected issue. J. Appl. Psychol. 74 546–553. 10.1037/0021-9010.74.4.546 [ CrossRef ] [ Google Scholar ]
• Kristof-Brown A. L., Zimmerman R. D., Johnson E. C. (2005). Consequences of individuals’ fit at work: a meta-analysis of person-job, person-organization, person-group, and person-supervisor fit. Pers. Psychol. 58 281–342. 10.1111/j.1744-6570.2005.00672.x [ CrossRef ] [ Google Scholar ]
• Kulik C. T., Bainbridge H. T. J. (2005). “Psychological perspectives on workplace diversity,” in Handbook of Workplace Diversity eds Konrad A. M., Prasad P., Pringle J. K. (Thousand Oaks, CA: Sage Publications; ) 25–52. [ Google Scholar ]
• Lamont M., Mizrachi N. (2012). Ordinary people doing extraordinary things: responses to stigmatization in comparative perspective. Ethn. Racial Stud. 35 365–381. 10.1080/01419870.2011.589528 [ CrossRef ] [ Google Scholar ]
• Lazear E. P., Rosen S. (1990). Male-female wage differentials in job ladders. J. Labor Econ. 8 106–123. 10.1016/j.sapharm.2011.06.003 [ CrossRef ] [ Google Scholar ]
• Leskinen E. A., Cortina L. M., Kabat D. B. (2011). Gender harassment: broadening our understanding of sex-based harassment at work. Law Hum. Behav. 35 25–39. 10.1007/s10979-010-9241-5 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Levitin T., Quinn R. P., Staines G. L. (1971). Sex discrimination against the American working woman. Am. Behav. Sci. 15 237–254. 10.1177/000276427101500207 [ CrossRef ] [ Google Scholar ]
• Lewin K. (1935). A Dynamic Theory of Personality. New York, NY: McGraw-Hill. [ Google Scholar ]
• Lewin K. (1951). Field Theory in Social Science: Selected Theoretical Papers. Oxford: Harpers. [ Google Scholar ]
• LexisNexis. (2010). Mealy’s Daily News Update: Pharmaceutical Firm Settles Gender Bias Class Claims for $ 175 Million. Available at: http://www.lexis.com [accessed July 15, 2010] [ Google Scholar ]
• Linehan M., Scullion H. (2008). The development of female global managers: the role of mentoring and networking. J. Bus. Ethics 83 29–40. 10.1007/s10551-007-9657-0 [ CrossRef ] [ Google Scholar ]
• Lips H. M. (2003). The gender pay gap: concrete indicator of women’s progress toward equality. Anal. Soc. Issues Public Policy 3 87–109. 10.1111/j.1530-2415.2003.00016.x [ CrossRef ] [ Google Scholar ]
• Lyness K. S., Thompson D. E. (1997). Above the glass ceiling? A comparison of matched samples of female and male executives. J. Appl. Psychol. 82 359–375. 10.1037/0021-9010.82.3.359 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Major B. (1994). From social inequality to personal entitlement: the role of social comparisons, legitimacy appraisals, and group membership. Adv. Exp. Soc. Psychol. 26 293–355. 10.1016/S0065-2601(08)60156-2 [ CrossRef ] [ Google Scholar ]
• Major B., Quinton W. J., Schmader T. (2003). Attributions to discrimination and self-esteem: impact of group identification and situational ambiguity. J. Exp. Soc. Psychol. 39 220–231. 10.1016/S0022-1031(02)00547-4 [ CrossRef ] [ Google Scholar ]
• Major B., Schmader T. (2001). “Legitimacy and the construal of social disadvantage,” in The Psychology of Legitimacy: Emerging Perspectives on Ideology, Justice, and Intergroup Relations eds Jost J. T., Major B. (Cambridge: Cambridge University Press; ) 176–200. [ Google Scholar ]
• Manne A. (2001). Women’s preferences, fertility and family policy: the case for diversity. People Place 9 6–25. [ Google Scholar ]
• Mansfield P., Koch P., Henderson J., Vicary J., Cohn M., Young E. (1991). The job climate for women in traditionally male blue-collar occupations. Sex Roles 25 63–79. 10.1007/BF00289317 [ CrossRef ] [ Google Scholar ]
• Marini M. M. (1989). Sex differences in earnings in the United States. Annu. Rev. Sociol. 15 343–380. 10.1146/annurev.so.15.080189.002015 [ CrossRef ] [ Google Scholar ]
• Martell R. F. (1991). Sex bias at work: the effects of attentional and memory demands on performance ratings of men and women. J. Appl. Soc. Psychol. 21 1939–1960. 10.1111/j.1559-1816.1991.tb00515.x [ CrossRef ] [ Google Scholar ]
• Martell R. F., Lane D. M., Emrich C. (1996). Male-female differences: a computer simulation. Am. Psychol. 51 157–158. 10.1037/0003-066X.51.2.157 [ CrossRef ] [ Google Scholar ]
• Martins L. L., Eddleston K. A., Veiga J. F. (2002). Moderators of the relationship between work-family conflict and career satisfaction. Acad. Manag. J. 45 399–409. 10.2307/3069354 [ CrossRef ] [ Google Scholar ]
• Martins L. L., Parsons C. K. (2007). Effects of gender diversity management on perceptions of organizational attractiveness: the role of individual differences in attitudes and beliefs. J. Appl. Psychol. 92 865–875. 10.1037/0021-9010.92.3.865 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Masser B. M., Abrams D. (2004). Reinforcing the glass ceiling: the consequences of hostile sexism for female managerial candidates. Sex Roles 51 609–615. 10.1007/s11199-004-5470-8 [ CrossRef ] [ Google Scholar ]
• Maume D. J. (1999). Glass ceilings and glass escalators: occupational segregation and race and sex differences in managerial promotions. Work Occup. 26 483–509. 10.1177/0730888499026004005 [ CrossRef ] [ Google Scholar ]
• McDonald P., Backstrom S., Dear K. (2008). Reporting sexual harassment: claims and remedies. Asia Pac. J. Hum. Resour. 46 173–195. 10.1177/1038411108091757 [ CrossRef ] [ Google Scholar ]
• McDonald S., Lin N., Ao D. (2009). Networks of Opportunity: gender, race, and job leads. Soc. Probl. 56 385–402. 10.1525/sp.2009.56.3.385 [ CrossRef ] [ Google Scholar ]
• McGinley A. (2007). Babes and beefcake: exclusive hiring arrangements and sexy dress codes. Duke J. Gend. Law Policy 14 257–283. [ Google Scholar ]
• McIntyre S., Moberg D. J., Posner B. Z. (1980). Preferential treatment in preselection decisions according to sex and race. Acad. Manag. J. 23 738–749. 10.2307/255560 [ CrossRef ] [ Google Scholar ]
• McLaughlin H., Uggen C., Blackstone A. (2012). Sexual harassment, workplace authority, and the paradox of power. Am. Sociol. Rev. 77 625–647. 10.1177/0003122412451728 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Miner-Rubino K., Cortina L. M. (2004). Working in a context of hostility toward women: implications for employees’ well-being. J. Occup. Health Psychol. 9 107–122. 10.1037/1076-8998.9.2.107 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Mitchell D., Hirschman R., Angelone D. J., Lilly R. S. (2004). A laboratory analogue for the study of peer sexual harassment. Psychol. Women Q. 28 194–203. 10.1111/j.1471-6402.2004.00136.x [ CrossRef ] [ Google Scholar ]
• Montañés P., de Lemus S., Bohner G., Megías J. L., Moya M., Garcia-Retamero R. (2012). Intergenerational transmission of benevolent sexism from mothers to daughters and its relation to daughters’ academic performance and goals. Sex Roles 66 468–478. 10.1007/s11199-011-0116-0 [ CrossRef ] [ Google Scholar ]
• Moore v. Alabama State University. (1996). 980 F. Supp. 426 (M.D. Ala. 1996) M.D. Alabama: United States District Court. [ Google Scholar ]
• Morgan W. B., Walker S. S., Hebl M. R., King E. B. (2013). A field experiment: reducing interpersonal discrimination toward pregnant job applicants. J. Appl. Psychol. 98 799–809. 10.1037/a0034040 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Morrison A. M., Von Glinow M. A. (1990). Women and minorities in management. Am. Psychol. 45 200–208. 10.1037/0003-066X.45.2.200 [ CrossRef ] [ Google Scholar ]
• Moss-Racusin C. A., Dovidio J. F., Brescoll V. L., Graham M. J., Handelsman J. (2012). Science faculty’s subtle gender biases favor male students. PNAS 109 16474–16479. 10.1073/pnas.1211286109 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Murphy K. R., Cleveland J. (1995). Understanding Performance Appraisal: Social, Organizational, and Goal-Based Perspectives. Thousand Oaks, CA: Sage Publications. [ Google Scholar ]
• Murrell A. J., Olson J. E., Frieze I. H. (1995). Sexual harassment and gender discrimination: a longitudinal study of women managers. J. Soc. Issues 51 139–149. 10.1111/j.1540-4560.1995.tb01313.x [ CrossRef ] [ Google Scholar ]
• Neumark D. (1996). Sex discrimination in restaurant hiring: an audit study. Q. J. Econ. 111 915–942. 10.2307/2946676 [ CrossRef ] [ Google Scholar ]
• Nishii L. H., Raver J. L. (2003). “Collective climates for diversity: evidence from a field study,” in Paper Presented at the Annual Conference of the Society for Industrial and Organizational Psychology Orlando, FL. [ Google Scholar ]
• Noe R. A. (1988). Women and mentoring: a review and research agenda. Acad. Manag. Rev. 13 65–78. 10.5465/AMR.1988.4306784 [ CrossRef ] [ Google Scholar ]
• Offermann L. R., Malamut A. B. (2002). When leaders harass: the impact of target perceptions of organizational leadership and climate on harassment reporting and outcomes. J. Appl. Psychol. 87 885–893. 10.1037/0021-9010.87.5.885 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Olian J. D., Schwab D. P., Haberfeld Y. (1988). The impact of applicant gender compared to qualifications on hiring recommendations: a meta-analysis of experimental studies. Organ. Behav. Hum. Decis. Process. 41 180–195. 10.1016/0749-5978(88)90025-8 [ CrossRef ] [ Google Scholar ]
• Ostroff C., Atwater L. E. (2003). Does whom you work with matter? Effects of referent group gender and age composition on managers’ compensation. J. Appl. Psychol. 88 725–740. 10.1037/0021-9010.88.4.725 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ostroff C., Kinicki A. J., Muhammad R. S. (2012). “Organizational culture and climate,” in Handbook of Psychology, Industrial and Organizational Psychology 2nd Edn Vol. 12 eds Schmitt N. W., Highhouse S. (New York, NY: Wiley and Sons; ) 643–676. [ Google Scholar ]
• Ostroff C., Rothausen T. J. (1997). The moderating effect of tenure in person—environment fit: a field study in educational organizations. J. Occup. Organ. Psychol. 70 173–188. 10.1111/j.2044-8325.1997.tb00641.x [ CrossRef ] [ Google Scholar ]
• Perlow L. A. (1995). Putting the work back into work/family. Group Organ. Manag. 20 227–239. 10.1177/1059601195202009 [ CrossRef ] [ Google Scholar ]
• Perry E. L., Davis-Blake A., Kulik C. T. (1994). Explaining gender-based selection decisions: a synthesis of contextual and cognitive approaches. Acad. Manag. Rev. 19 786–820. 10.5465/AMR.1994.9412190219 [ CrossRef ] [ Google Scholar ]
• Peterson T., Morgan L. A. (1995). Separate and unequal: occupation-establishment sex segregation and gender wage gap. Am. J. Sociol. 101 329–365. 10.1086/230727 [ CrossRef ] [ Google Scholar ]
• Pryor J. B. (1995). The psychosocial impact of sexual harassment on women in the US Military. Basic Appl. Soc. Psychol. 17 581–603. 10.1207/s15324834basp1704_9 [ CrossRef ] [ Google Scholar ]
• Pryor J. B., Giedd J. L., Williams K. B. (1995). A social psychological model for predicting sexual harassment. J. Soc. Issues 51 69–84. 10.1111/j.1540-4560.1995.tb01309.x [ CrossRef ] [ Google Scholar ]
• Pryor J. B., LaVite C. M., Stoller L. M. (1993). A social and psychological analysis of sexual harassment: the person/situation interaction. J. Vocat. Behav. 42 68–83. 10.1006/jvbe.1993.1005 [ CrossRef ] [ Google Scholar ]
• Ragins B. R., Cornwall J. M. (2001). Pink triangles: antecedents and consequences of perceived workplace discrimination against gay and lesbian employees. J. Appl. Psychol. 86 1244–1261. 10.1037/0021-9010.86.6.1244 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ragins B. R., Sundstrom E. (1989). Gender and power in organizations: a longitudinal perspective. Psychol. Bull. 105 51–88. 10.1037/0033-2909.105.1.51 [ CrossRef ] [ Google Scholar ]
• Reilly K. T., Wirjanto T. S. (1999). Does more mean less? The male/female wage gap and the proportion of females at the establishment level. Can. J. Econ. 32 906–929. 10.2307/136410 [ CrossRef ] [ Google Scholar ]
• Reskin B. F., McBrier D. B. (2000). Why not ascription? Organizations’ employment of male and female managers. Am. Sociol. Rev. 65 210–233. [ Google Scholar ]
• Roberson L., Galvin B. M., Charles A. C. (2007). When group identities matter: bias in performance appraisal. Acad. Manag. Ann. 1 617–650. 10.1080/078559818 [ CrossRef ] [ Google Scholar ]
• Rosen B., Jerdee T. H. (1974). Effects of applicant’s sex and difficulty of job on evaluations of candidates for management positions. J. Appl. Psychol. 59 511–512. 10.1037/h0037323 [ CrossRef ] [ Google Scholar ]
• Roth P. L., Purvis K. L., Bobko P. (2012). A meta-analysis of gender group differences for measures of job performance in field studies. J. Manag. 38 719–739. 10.1177/0149206310374774 [ CrossRef ] [ Google Scholar ]
• Rudman L. A. (1998). Self-promotion as a risk factor for women: the costs and benefits of counterstereotypical impression management. J. Pers. Soc. Psychol. 74 629–645. 10.1037/0022-3514.74.3.629 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rudman L. A., Kilianski S. E. (2000). Implicit and explicit attitudes toward female authority. Pers. Soc. Psychol. Bull. 26 1315–1328. 10.1177/0146167200263001 [ CrossRef ] [ Google Scholar ]
• Rudman L. A., Phelan J. E. (2008). Backlash effects for disconfirming gender stereotypes in organizations. Res. Organ. Behav. 28 61–79. 10.1016/j.riob.2008.04.003 [ CrossRef ] [ Google Scholar ]
• Rudman L. A., Moss-Racusin C. A., Phelan J. E., Nauts S. (2012). Status incongruity and backlash effects: defending the gender hierarchy motivates prejudice against female leaders. J. Exp. Soc. Psychol. 48 165–179. 10.1016/j.jesp.2011.10.008 [ CrossRef ] [ Google Scholar ]
• Ruggiero K. M., Taylor D. M. (1995). Coping with discrimination: how disadvantaged group members perceive the discrimination that confronts them. J. Pers. Soc. Psychol. 68 826–838. 10.1037/0022-3514.68.5.826 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Russell B. L., Trigg K. Y. (2004). Tolerance of sexual harassment: an examination of gender differences, ambivalent sexism, social dominance, and gender roles. Sex Roles 50 565–573. 10.1023/B:SERS.0000023075.32252.fd [ CrossRef ] [ Google Scholar ]
• Rynes S., Rosen B. (1995). A field survey of factors affecting the adoption and perceived success of diversity training. Pers. Psychol. 48 247–270. 10.1111/j.1744-6570.1995.tb01756.x [ CrossRef ] [ Google Scholar ]
• Salvaggio A. N., Streich M., Hopper J. E. (2009). Ambivalent sexism and applicant evaluations: effects on ambiguous applicants. Sex Roles 61 621–633. 10.1007/s11199-009-9640-6 [ CrossRef ] [ Google Scholar ]
• Sanchez J. I., De La Torre P. (1996). A second look at the relationship between rating and behavioral accuracy in performance appraisal. J. Appl. Psychol. 81 3–10. 10.1037/0021-9010.81.1.3 [ CrossRef ] [ Google Scholar ]
• Schein E. H. (2010). Organizational Culture and Leadership , Vol. 2 New York, NY: Jossey-Bass [ Google Scholar ]
• Schmader T., Johns M., Forbes C. (2008). An integrated process model of stereotype threat effects on performance. Psychol. Rev. 115 336–356. 10.1037/0033-295X.115.2.336 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Schmitt M. T., Branscombe N. R., Kobrynowicz D., Owen S. (2002). Perceiving discrimination against one’s gender group has different implications for well-being in women and men. Pers. Soc. Psychol. Bull. 28 197–210. 10.1177/0146167202282006 [ CrossRef ] [ Google Scholar ]
• Schmitt M. T., Branscombe N. R., Postmes T., Garcia A. (2014). The consequences of perceived discrimination for psychological well-being: a meta-analytic review. Psychol. Bull. 140 921–948. 10.1037/a0035754 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Schneider B. (1975). Organizational climates: an essay. Pers. Psychol. 28 447–479. 10.1111/j.1744-6570.1975.tb01386.x [ CrossRef ] [ Google Scholar ]
• Schneider B. (1983). “The attraction–selection–attrition framework,” in Organizational Effectiveness: A Comparison of Multiple Models eds Cameron K. S., Whetten D. A. (New York, NY: Academic Press; ). [ Google Scholar ]
• Schneider B. (1987). The people make the place. Pers. Psychol. 40 437–453. 10.1111/j.1744-6570.1987.tb00609.x [ CrossRef ] [ Google Scholar ]
• Schneider B., Ehrhart M. G., Macey W. H. (2011). “Organizational climate research: achievements and the road ahead,” in The Handbook of Organizational Culture and Climate 2nd Edn eds Ashkanasy N. M., Wilderom C. P. M., Peterson M. F. (Thousand Oaks, CA: Sage; ) 29–49. [ Google Scholar ]
• Schneider K. T., Swan S., Fitzgerald L. F. (1997). Job-related and psychological effects of sexual harassment in the workplace: empirical evidence from two organizations. J. Appl. Psychol. 82 401–415. 10.1037/0021-9010.82.3.401 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Schneyer K. L. (1998). Hooting: public and popular discourse about sex discrimination. Univ. Mich. J. Law Reform 31 551–636. [ Google Scholar ]
• Schwartz M. D., DeKeseredy W. S. (2000). Aggregation bias and woman abuse: variations by male peer support, region, language, and school type. J. Interpersh. Violence 15 555–565. 10.1177/088626000015006001 [ CrossRef ] [ Google Scholar ]
• Sheltzer J. M., Smith J. C. (2014). Elite male faculty in the life sciences employ fewer women. PNAS 111 10107–10112. 10.1073/pnas.1403334111 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smith P. C., Kendall L. M. (1963). Retranslation of expectations: an approach to the construction of unambiguous anchors for rating scales. J. Appl. Psychol. 47 149–155. 10.1037/h0047060 [ CrossRef ] [ Google Scholar ]
• Snyder K. A., Green A. I. (2008). Revisiting the glass escalator: the case of gender segregation in a female dominated occupation. Soc. Probl. 55 271–299. 10.1525/sp.2008.55.2.271 [ CrossRef ] [ Google Scholar ]
• Son Hing L. S. (2012). Responses to stigmatization: the moderating roles of primary and secondary appraisals. Du Bois Rev. 9 149–168. 10.10170/S1742058X11000592 [ CrossRef ] [ Google Scholar ]
• Son Hing L. S., Bobocel D. R., Zanna M. P. (2002). Meritocracy and opposition to affirmative action: making concessions in the face of discrimination. J. Pers. Soc. Psychol. 83 493–509. 10.1037/0022-3514.83.3.493 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Son Hing L. S., Bobocel D. R., Zanna M. P., Garcia D. M., Gee S. S., Orazietti K. (2011). The merit of meritocracy. J. Pers. Soc. Psychol. 101 433–450. 10.1037/a0024618 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Son Hing L. S., Chung-Yan G. A., Hamilton L. K., Zanna M. P. (2008). A two-dimensional model that employs explicit and implicit attitudes to characterize prejudice. J. Pers. Soc. Psychol. 94 971–987. 10.1037/0022-3514.94.6.971 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Son Hing L. S., Zanna M. P. (2010). “Individual differences,” in The Sage Handbook of Prejudice, Stereotyping and Discrimination eds Dovidio J. F., Hewstone M., Glick P., Esses V. (London: SAGE Publications Ltd.) 163–179. [ Google Scholar ]
• Spencer S. J., Steele C. M., Quinn D. M. (1999). Stereotype threat and women’s math performance. J. Exp. Soc. Psychol. 35 4–28. 10.1006/jesp.1998.1373 [ CrossRef ] [ Google Scholar ]
• Spreitzer G. M., McCall M. W., Mahoney J. D. (1997). Early identification of international executive potential. J. Appl. Psychol. 82 6–29. 10.1037/0021-9010.82.1.6 [ CrossRef ] [ Google Scholar ]
• Stangor C., Lynch L., Duan C., Glass B. (1992). Categorization of individuals on the basis of multiple social features. J. Pers. Soc. Psychol. 62 207–218. 10.1037/0022-3514.62.2.207 [ CrossRef ] [ Google Scholar ]
• Stangor C., Swim J. K., Sechrist G. B., DeCoster J., Van Allen K. L., Ottenbreit A. (2003). Ask, answer, and announce: three stages in perceiving and responding to discrimination. Eur. Rev. Soc. Psychol. 14 277–311. 10.1080/10463280340000090 [ CrossRef ] [ Google Scholar ]
• Steinpreis R. E., Anders K. A., Ritzke D. (1999). The impact of gender on the review of the curricula vitae of job applicants and tenure candidates: a national empirical study. Sex Roles 41 509–528. 10.1023/A:1018839203698 [ CrossRef ] [ Google Scholar ]
• Stone P., Lovejoy M. (2004). Fast-track women and the “choice” to stay home. Ann. Am. Acad. Polit. Soc. Sci. 596 62–83. 10.1177/0002716204268552 [ CrossRef ] [ Google Scholar ]
• Stroh L. K., Brett J. M., Reilly A. H. (1992). All the right stuff: a comparison of female and male managers’ career progression. J. Appl. Psychol. 77 251–260. 10.1037/0021-9010.77.3.251 [ CrossRef ] [ Google Scholar ]
• Swidler A. (1986). Culture in action: symbols and strategies. Am. Sociol. Rev. 51 273–286. 10.2307/2095521 [ CrossRef ] [ Google Scholar ]
• Thomas-Hunt M. C., Phillips K. W. (2004). When what you know is not enough: expertise and gender dynamics in task groups. Pers. Soc. Psychol. Bull. 30 1585–1598. 10.1177/0146167204271186 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tosi H. L., Einbender S. W. (1985). The effects of the type and amount of information in sex discrimination research: a meta-analysis. Acad. Manag. J. 28 712–723. 10.2307/256127 [ CrossRef ] [ Google Scholar ]
• Triana M. D. C., García M. F. (2009). Valuing diversity: a group-value approach to understanding the importance of organizational efforts to support diversity. J. Organ. Behav. 30 941–962. 10.1002/job.598 [ CrossRef ] [ Google Scholar ]
• Triana M. D. C., García M. F., Colella A. (2010). Managing diversity: how organizational efforts to support diversity moderate the effects of perceived racial discrimination on affective commitment. Pers. Psychol. 63 817–843. 10.1111/j.1744-6570.2010.01189.x [ CrossRef ] [ Google Scholar ]
• Trice H. M., Beyer J. M. (1993). The Cultures of Work Organizations. Englewood Cliffs, NJ: Prentice-Hall. [ Google Scholar ]
• Tsui A. S., O’Reilly C. A. (1989). Beyond simple demographic effects: the importance of relational demography in superior-subordinate dyads. Acad. Manag. J. 32 402–423. 10.2307/256368 [ CrossRef ] [ Google Scholar ]
• U.S. Census Bureau. (2007). Statistical Abstract of the United States: 2007. Washington, DC. Available at: http://www.census.gov/prod/www/statistical_abstract.html [ Google Scholar ]
• U.S. Government Accountability Office. (2003). Women’s Earnings: Work Patterns Partially Explain Difference Between Men’s and Women’s Earnings (GAO-04-35). Available at: http://www.gao.gov [ Google Scholar ]
• van Knippenberg D., De Dreu C. K., Homan A. C. (2004). Work group diversity and group performance: an integrative model and research agenda. J. Appl. Psychol. 89 1008–1022. 10.1037/0021-9010.89.6.1008 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• van Zomeren M., Postmes T., Spears R. (2008). Toward an integrative social identity model of collective action: a qualitative research synthesis of three socio-psychological perspectives. Psychol. Bull. 134 505–535. 10.1037/0033-2909.134.4.504 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Velez et al. v. Novartis Pharmaceuticals Crop et al. (2010). No. 04 Civ. 9194 (S.D. N.Y., May 19, 2010). [ Google Scholar ]
• Vescio T. K., Gervais S. J., Snyder M., Hoover A. (2005). Power and the creation of patronizing environments: the stereotype-based behaviors of the powerful and their effects on female performance in masculine domains. J. Pers. Soc. Psychol. 88 658–672. 10.1037/0022-3514.88.4.658 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Vorauer J. D., Kumhyr S. M. (2001). Is this about you or me? Self-versus other-directed judgments and feelings in response to intergroup interaction. Pers. Soc. Psychol. Bull. 27 706–719. 10.1177/0146167201276006 [ CrossRef ] [ Google Scholar ]
• Wal-Mart Stores Inc. v. Dukes. (2004/2011). 222 F.R.D. 137 (N.D. Cal. 2001) aff’d 509 F.3d. 1168 (9C 2007) aff’d 603 F.3d 571 (9C 2010) rev’d 564 U.S. ___ (2011), Docket No. 10–277. [ Google Scholar ]
• Welle B., Heilman M. E. (2005). “Formal and informal discrimination against women at work: the role of gender stereotypes,” in Research in Social Issues in Management eds Steiner D., Gilliland S. W., Skarlicki D. (Westport, CT: Information Age Publishers; ) 23–40. [ Google Scholar ]
• Westall R. (2015). Restaurant Dress Codes Open to Sexual Discrimination Complaints. CBC. Available at: http://www.cbc.ca/news/canada/restaurant-dress-codes-open-to-sexual-discrimination-complaints-1.3012522 [accessed March 31, 2015] [ Google Scholar ]
• Williams C. L. (1992). The glass escalator: hidden advantages for men in the “female” professions. Soc. Probl. 39 253–267. 10.2307/3096961 [ CrossRef ] [ Google Scholar ]
• Williams J. C. (2003). Beyond the glass ceiling: the maternal wall as a barrier to gender equality. T. Jefferson L. Rev. 26 1–14. [ Google Scholar ]
• Willness C. R., Steel P., Lee K. (2007). A meta-analysis of the antecedents and consequences of workplace sexual harassment. Pers. Psychol. 60 127–162. 10.1111/j.1744-6570.2007.00067.x [ CrossRef ] [ Google Scholar ]
• Word C. O., Zanna M. P., Cooper J. (1974). The nonverbal mediation of self-fulfilling prophecies in interracial interaction. J. Exp. Soc. Psychol. 10 109–120. 10.1016/0022-1031(74)90059-6 [ CrossRef ] [ Google Scholar ]
• Wright P., Ferris S. P., Hiller J. S., Kroll M. (1995). Competitiveness through management of diversity: effects on stock price valuation. Acad. Manag. J. 38 272–287. 10.2307/256736 [ CrossRef ] [ Google Scholar ]
• Wright P. M., McMahan G. C., McWilliams A. (1994). Human resources and sustained competitive advantage: a resource-based perspective. Int. J. Hum. Resour. Manag. 5 301–326. 10.1080/09585199400000020 [ CrossRef ] [ Google Scholar ]
• Wright S. C. (2001). “Strategic collective action: social psychology and social change,” in Blackwell Handbook of Social Psychology: Intergroup Processes eds Brown R., Gaertner S. (Oxford: Blackwell Publishing; ) 409–430. 10.1002/9780470693421.ch20 [ CrossRef ] [ Google Scholar ]
• Wright S. C., Lubensky M. E. (2009). “The struggle for social equality: collective action versus prejudice reduction,” in Intergroup Misunderstandings: Impact of Divergent Social Realities eds Demoulin S., Leyens J. P., Dovidio J. F. (New York, NY: Psychology Press; ) 291–310. [ Google Scholar ]

Introduction: The Case for Discrimination Research

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• Rosita Fibbi 4 ,
• Arnfinn H. Midtbøen 5 &
• Patrick Simon 6  

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Increasing migration-related diversity in Europe has fostered dramatic changes since the 1950s, among them the rise of striking ethno-racial inequalities in employment, housing, health, and a range of other social domains. These ethno-racial disadvantages can be understood as evidence of widespread discrimination; however, scholarly debates reflect striking differences in the conceptualization and measurement of discrimination in the social sciences. Indeed, what discrimination is, as well as how and why it operates, are differently understood and studied by the various scholarships and scientific fields. It is the ambition of this book to summarize how we frame, study, theorize, and aim at combatting ethno-racial discrimination in Europe.

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European societies are more ethnically diverse than ever. The increasing migration-related diversity has fostered dramatic changes since the 1950s, among them the rise of striking ethno-racial inequalities in employment, housing, health, and a range of other social domains. The sources of these enduring inequalities have been a subject of controversy for decades. To some scholars, ethno-racial gaps in such outcomes are seen as transitional bumps in the road toward integration, while others view structural racism, ethnic hostility, and subtle forms of outgroup-bias as fundamental causes of persistent ethno-racial inequalities. These ethno-racial disadvantages can be understood as evidence of widespread discrimination; however, scholarly debates reflect striking differences in the conceptualization and measurement of discrimination in the social sciences.

What discrimination is, as well as how and why it operates, are differently understood and studied by the various scholarships and scientific fields. A large body of research has been undertaken over the previous three decades, using a variety of methods – qualitative, quantitative, and experimental. These research efforts have improved our knowledge of the dynamics of discrimination in Europe and beyond. It is the ambition of this book to summarize how we frame, study, theorize, and aim at combatting ethno-racial discrimination in Europe.

1.1 Post-War Immigration and the Ethno-racial Diversity Turn

Even though ethnic and racial diversity has existed to some extent in Europe (through the slave trade, transnational merchants, and colonial troops), the scope of migration-related diversity reached an unprecedented level in the period following World War II. This period coincides with broader processes of decolonization and the beginning of mass migration from non-European countries, be it from former colonies to the former metropoles (from the Caribbean or India and Pakistan to the UK; South-East Asia, North Africa or Sub-Saharan Africa to France) or in the context of labor migration without prior colonial ties (from Turkey to Germany or the Netherlands; Morocco to Belgium or the Netherlands, etc.).

The ethnic and racial diversity in large demographic figures began in the 1960s (Van Mol and de Valk 2016 ). At this time, most labor migrants were coming from other European countries, but figures of non-European migration were beginning to rise: in 1975, 8% of the population in France and the UK had a migration background, half of which originated from a non-European country. By contrast, in 2014, 9.2% of the population of the EU28 had a migration background from outside of Europe (either foreign born or native-born from foreign-born parent(s)), and this share reached almost 16% in Sweden; 14% in the Netherlands, France, and the UK; and between 10 and 13% in Germany, Belgium, and Austria. The intensification of migration, especially from Asia and Africa, has heightened the visibility of ethno-racial diversity in large European metropolises. Almost 50% of inhabitants in Amsterdam and Rotterdam have a “nonwestern allochthon ” background (2014), 40% of Londoners are black or ethnic minorities (2011), while 30% of Berliners (2013) and 43% of Parisians (metropolitan area; 2009) have a migration background. The major facts of this demographic evolution are not only that diversity has reached a point of “super-diversity” (see Vertovec 2007 ; Crul 2016 ) in size and origins, but also that descendants of immigrants (i.e., the second generation) today make up a significant demographic group in most European countries, with the exception of Southern Europe where immigration first boomed in the 2000s.

The coming of age of the second generation has challenged the capacity of different models of integration to fulfill promises of equality, while the socio-cultural cohesion of European societies is changing and has to be revised to include ethnic and racial diversity. Native-born descendants of immigrants are socialized in the country of their parents’ migration and, in most European countries, share the full citizenship of the country where they live and, consequently, the rights attached to it. However, an increasing number of studies show that even the second generation faces disadvantages in education, employment, and housing that cannot be explained by their lack of skills or social capital (Heath and Cheung 2007 ). The transmission of penalties from one generation to the other – and in some cases an even higher level of penalty for the second generation than for the first – cannot be explained solely by the deficiencies in human, social, and cultural capital, as could have been the case for low-skilled labor migrants arriving in the 1960s and 1970s. Indeed, the persistence of ethno-racial disadvantages among citizens who do not differ from others except for their ethnic background, their skin color, or their religious beliefs is a testament to the fact that equality for all is an ambition not yet achieved.

Citizenship status may represent a basis for differential treatment. Undoubtedly, citizenship status is generally considered a legitimate basis for differential treatment, which is therefore not acknowledged as discrimination. Indeed, in many European countries, the divide between nationals and European Union (EU) citizens lost its bearing with the extension of social rights to EU citizens (Koopmans et al. 2012 ). Yet, in other countries, and for non-EU citizens, foreign citizenship status creates barriers to access to social subsidies, health care, specific professions, and pensions or exposure to differential treatment in criminal justice. In most countries, voting rights are conditional to citizenship, and the movement to expand the polity to non-citizens is uneven, at least for elections of representatives at the national parliaments. Notably, in countries with restrictive access to naturalization, citizenship status may provide an effective basis for unequal treatment (Hainmueller and Hangartner 2013 ). The issue of discrimination among nationals, therefore, should not overshadow the enduring citizenship-based inequalities.

The gap between ethnic diversity among the population and scarcity of the representation of this diversity in the economic, political, and cultural elites demonstrate that there are obstacles to minorities entering these positions. This picture varies across countries and social domains. The UK, Belgium, or the Netherlands display a higher proportion of elected politicians with a migration background than France or Germany (Alba and Foner 2015 ). Some would argue that it is only a matter of time before newcomers will take their rank in the queue and access the close ring of power in one or two generations. Others conclude that there is a glass ceiling for ethno-racial minorities, which will prove as efficient as that for women to prevent them from making their way to the top. The exception that proves the rule can be found in sports, where athletes with minority backgrounds are often well represented in high-level competitions. The question is how to narrow the gap in other domains of social life, and what this gap tells us about the structures of inequalities in European societies.

1.2 Talking About Discrimination in Europe

Discrimination is as old as human society. However, the use of the concept in academic research and policy debates in Europe is fairly recent. In the case of differential treatment of ethnic and racial minorities, the concept was typically related to blatant forms of racism and antisemitism, while the more subtle forms of stigmatization, subordination, and exclusion for a long time did not receive much attention as forms of “everyday racism” (Essed 1991 ). The turn from explicit racism to more subtle forms of selection and preference based on ethnicity and race paved the way to current research on discrimination. In European societies, where formal equality is a fundamental principle protected by law, discrimination is rarely observed directly. Contrary to overt racism, which is explicit and easily identified, discrimination is typically a hidden part of decisions, selection processes, and choices that are not explicitly based on ethnic or racial characteristics, even though they produce unfair biases. Discrimination does not have to be intentional and it is often not even a conscious part of human action and interaction. While it is clear that discrimination exists, this form of differential treatment is hard to make visible. The major task of research in the field is thus to provide evidence of the processes and magnitude of discrimination. Beyond the variety of approaches in the different disciplines, however, discrimination researchers tend to agree on the starting point: stereotypes and prejudices are nurturing negative perceptions, more or less explicit, of individuals or groups through processes of ethnicization or racialization, which in turn create biases in decision-making processes and serve as barriers to opportunities for these individuals or groups.

Although the concepts of inequality, discrimination, and racism are sometimes used interchangeably, the concept of discrimination entails specificities in terms of social processes, power relations, and legal frameworks that have opened new perspectives to understand ethnic and racial inequalities. The genealogy of the concept and its diffusion in scientific publications still has to be studied thoroughly, and we searched in major journals to identify broad historical sequences across national contexts. Until the 1980s, the use of the concept of discrimination was not widespread in the media, public opinion, science, or policies. In scientific publications, the dissemination of the concept was already well advanced in the US at the beginning of the twentieth century in the aftermath of the abolition of slavery to describe interracial relations. In Europe, there is a sharp distinction between the UK and continental Europe in this regard. The development of studies referring explicitly to discrimination in the UK has a clear link to the post-colonial migration after World War II and the foundation of ethnic and racial studies in the 1960s. However, the references to discrimination remained quite limited in the scientific literature until the 1990s – even in specialized journals such as Ethnic and Racial Studies , New Community and its follower Journal for Ethnic and Migration Studies , and more recently Ethnicities  – when the number of articles containing the term discrimination in their title or keywords increased significantly. In French-speaking journals, references to discrimination were restricted to a small number of feminist journals in the 1970s and became popular in the 1990s and 2000s in mainstream social science journals. The same held true in Germany, with a slight delay in the middle of the 2000s. Since the 2000s, the scientific publications on discrimination have reached new peaks in most European countries.

The year 2000 stands as a turning point in the development of research and public interest in discrimination in continental Europe. This date coincides with the legal recognition of discrimination by the parliament of the EU through a directive “implementing the principle of equal treatment between persons irrespective of racial or ethnic origin,” more commonly called the “Race Equality Directive.” This directive put ethnic and racial discrimination on the political agenda of EU countries. This political decision contributed to changing the legal framework of EU countries, which incorporated non-discrimination as a major reference and transposed most of the terms of the Race Equality Directive into their national legislation. The implementation of the directive was also a milestone in the advent of the awareness of discrimination in Europe. In order to think in terms of discrimination, there should be a principle of equal treatment applied to everyone, regardless of their ethnicity or race. This principle of equal treatment is not new, but it has remained quite formal for a long time. The Race Equality Directive represented a turning point toward a more effective and proactive approach to achieve equality and accrued sensitivity to counter discrimination wherever it takes place.

The first step to mobilize against discrimination is to launch awareness-raising campaigns to create a new consciousness of the existence of ethno-racial disadvantages. The denial of discrimination is indeed a paradoxical consequence of the extension of formal equality in post-war democratic regimes. Since racism is morally condemned and legally prohibited, it is expected that discrimination should not occur and, thus, that racism is incidental. Incidentally, an opinion survey conducted in 2000 for the European Union Monitoring Center on Racism and Xenophobia (which was replaced in 2003 by the Fundamental Rights Agency [FRA]), showed that only 31% of respondents in the EU15 at the time agreed that discrimination should be outlawed. However, the second Eurobarometer explicitly dedicated to studying discrimination in 2007 found that ethnic discrimination was perceived as the most widespread (very or fairly) type of discrimination by 64% of EU citizens (European Commission 2007 ). Almost 10 years later, in 2015, the answers were similar for ethnic discrimination but had increased for all other grounds except gender. Yet, there are large discrepancies between countries, with the Netherlands, Sweden, and France showing the highest levels of consciousness of ethnic discrimination (84%, 84%, and 82%, respectively), whereas awareness is much lower in Poland (31%) and Latvia (32%). In Western Europe, Germany (60%) and Austria (58%) stand out with relatively lower marks (European Commission 2015 ).

These Eurobarometer surveys provide useful information about the knowledge of discrimination and the attitudes of Europeans toward policies against it. However, they focus on the representation of different types of discrimination rather than the personal experience of minority members. To gather statistics on the experience of discrimination is difficult for two reasons: (1) minorities are poorly represented in surveys with relatively small samples in the general population and (2) questions about experiences of discrimination are rarely asked in non-specific surveys. Thanks to the growing interest in discrimination, more surveys are providing direct and indirect variables that are useful in studying the personal experiences of ethno-racial disadvantage.

The European Social Survey, for example, has introduced a question on perceived group discrimination (which is not exactly a personal self-reported experience of discrimination, see Chap. 4 ). In 2007 and 2015, the FRA conducted a specialized survey on discrimination in the 28 EU countries, the Minorities and Discrimination (EU-MIDIS) survey, to fill the gap in the knowledge of the experience of discrimination of ethnic and racial minorities. The information collected is wide ranging; however, only two minority groups were surveyed in each EU country, and the survey is not representative of the population.

Of course, European-wide surveys are not the main statistical sources on discrimination. Administrative statistics, censuses, and social surveys at the national and local levels in numerous countries bring new knowledge of discrimination, either with direct measures when this is the main topic of data collection or more indirectly when they provide information on gaps in employment or education faced by disadvantaged groups. The key point is to be able to identify the relevant population category in relation to discrimination, as we know that ethno-racial groups do not experience discrimination to the same extent. Analyses of immigrants or the second generation as a whole might miss the significant differences between – broadly speaking – European and non-European origins. Or, to put it in a different way, between white and non-white or “visible” minorities. Countries where groups with a European background make up most of the migration-related diversity typically show low levels of discrimination, while countries with high proportions of groups with non-European backgrounds, especially Africans (North and Sub-Saharan), Caribbean people, and South Asians, record dramatic levels of discrimination.

1.3 Who Is Discriminated Against? The Problem with Statistics on Ethnicity and Race

Collecting data on discrimination raises the problem of the identification of minority groups. Migration-related diversity has been designed from the beginning of mass migration based on place of birth of the individuals (foreign born) or their citizenship (foreigners). In countries where citizenship acquisition is limited, citizenship or nationality draws the boundary between “us” and “the others” over generations. This is not the case in countries with more open citizenship regimes where native-born children of immigrants acquire by law the nationality of their country of residence and thus cannot be identified by these variables. If most European countries collect data on foreigners and immigrants, a limited number identify the second generation (i.e., the children of immigrants born in the country of immigration). The question is whether the categories of immigrants and the second generation really reflect the population groups exposed to ethno-racial discrimination. As the grounds of discrimination make clear, nationality or country of birth is not the only characteristic generating biases and disadvantages: ethnicity, race, or color are directly involved. However, if it seems straightforward to define country of birth and citizenship, collecting data on ethnicity, race, or color is complex and, in Europe, highly sensitive.

Indeed, the controversial point is defining population groups by using the same characteristics by which they are discriminated against. This raises ethical, political, legal, and methodological issues. Ethical because the choice to re-use the very categories that convey stereotypes and prejudices at the heart of discrimination entails significant consequences. Political because European countries have adopted a color-blind strategy since 1945, meaning that their political philosophies consider that racial terminologies are producing racism by themselves and should be strictly avoided (depending on the countries, ethnicities receive the same blame). Legal because most European countries interpret the provisions of the European directive on data protection and their transposition in national laws as a legal prohibition. Methodological because there is no standardized format to collect personal information on ethnicity or race and there are several methodological pitfalls commented in the scientific literature. Data on ethnicity per se are collected in censuses to describe national minorities in Eastern Europe, the UK, and Ireland, which are the only Western European countries to produce statistics by ethno-racial categories (Simon 2012 ). The information is collected by self-identification either with an open question about one’s ethnicity or by ticking a box (or several in the case of multiple choices) in a list of categories. None of these questions explicitly mention race: for example, the categories in the UK census refer to “White,” “black British,” or “Asian British” among other items, but the question itself is called the “ethnic group question.”

In the rest of Europe, place of birth and nationality of the parents would be used as proxies for ethnicity in a limited number of countries: Scandinavia, the Netherlands, and Belgium to name a few. Data on second generations can be found in France, Germany, and Switzerland among others in specialized surveys with limitations in size and scope. Moreover, the succession of generations since the arrival of the first migrants will fade groups into invisibility by the third generation. This process is already well advanced in the oldest immigration countries, such as France, Germany, Switzerland, and the Netherlands. Asking questions about the grandparents and the previous generations is not an option since it would require hard decisions to classify those with mixed ancestry (how many ancestors are needed to belong to one category?), not to mention the problems in memory to retrieve all valuable information about the grandparents. This is one of the reasons why traditional immigration countries (USA, Canada, Australia) collect data on ethnicity through self-identification questions.

The discrepancies between official categories and those exposed to discrimination have fostered debates between state members and International Human Rights Organizations – such as the UN Committee for the Elimination of Racial Discrimination (CERD), European Commission against Racism and Intolerance (ECRI) at the Council of Europe, and the EU FRA – which claim that more data are needed on racism and discrimination categorized by ethnicity. The same applies to academia and antiracist NGOs where debates host advocates and opponents to “ethnic statistics.” There is no easy solution, but the accuracy of data for the measurement of discrimination is a strategic issue for both research and policies.

1.4 Discrimination and Integration: Commonalities and Contradictions

How does research on discrimination relate to the broader field of research on immigrant assimilation or integration? On one hand, assimilation/integration and discrimination are closely related both in theory and in empirical studies. Discrimination hinders full participation in society, and the persistence of ethnic penalties across generations contradicts long-term assimilation prospects. On the other hand, both assimilation and integration theory tend to assume that the role of discrimination in shaping access to opportunities will decrease over time. Assimilation is often defined as “the decline of ethnic distinction and its corollary cultural and social difference” (Alba and Nee 2003 , 11), a definition that bears an expectation that migrants and their descendants will over time cease to be viewed as different from the “mainstream population,” reach parity in socioeconomic outcomes, and gradually become “one of us.” In the canonical definition, integration departs from assimilation by considering incorporation as a two-way process. Migrants and ethnic minorities are expected to become full members of a society by adopting core values, norms, and basic cultural codes (e.g., language) from mainstream society, while mainstream society is transformed in return by the participation of migrants and ethnic minorities (Alba et al. 2012 ). The main idea is that convergence rather than differentiation should occur to reach social cohesion, and mastering the cultural codes of mainstream society will alleviate the barriers to resource access, such as education, employment, housing, and rights.

Of course, studies of assimilation and integration do not necessarily ignore that migrants and ethnic minorities face penalties in the course of the process of acculturation and incorporation into mainstream society. In the landmark book, Assimilation in American Life , Milton Gordon clearly spelled out that the elimination of prejudice and discrimination is a key parameter for assimilation to occur; or to use his own terms, that “attitude receptional” and “behavioral receptional” dimensions of assimilation are crucial to complete the process (Gordon 1964 , 81). Yet, ethnic penalties are believed to be mainly determined by human capital and class differences and therefore progressively offset as education level rises, elevating the newcomers to conditions of the natives and reducing the social distance between groups. Stressing the importance of generational progress, assimilation theory thus tends to consider discrimination as merely a short-run phenomenon.

The main blind spots in assimilation and integration theories revolve around two issues: the specific inequalities related to the ethnicization or racialization of non-white minorities and the balance between the responsibilities of the structures of mainstream society and the agencies of migrants and ethnic minorities in the process of incorporation. Along these two dimensions, discrimination research offers a different perspective than what is regularly employed in studies of assimilation and integration.

Discrimination research tends to identify the unfavorable and unfair treatment of individuals or groups based on categorical characteristics and often shows these unfair treatments lie in the activation of stereotypes and prejudices by gatekeepers and the lack of neutrality in processes of selection. In this perspective, what has to be transformed and adapted to change the situation are the structures – the institutions, procedures, bureaucratic routines, etc. – of mainstream society, opening it up to ethnic and racial diversity to enable migrants and ethnic minorities to participate on equal footing with other individuals, independent of their identities. By contrast, in studies of assimilation and integration, explanations of disadvantages are often linked to the lack of human capital and social networks among migrants and ethnic minorities, suggesting that they have to transform themselves to be able to take full part in society. To simplify matters, studies of assimilation and integration often explain persistent disadvantages by pointing to characteristics of migrants and ethnic minorities, while discrimination research explains disadvantages by characteristics of the social and political system.

Both assimilation and integration theories have gradually opened up for including processes of ethnicization and racialization and the consequences of such processes on assimilation prospects. Most prominently, segmented assimilation theory (Portes and Rumbaut 2001 ; Portes and Zhou 1993 ) shifts the focus away from migrants’ adaptation efforts and to the forms of interaction between minority groups – and prominently the second and later generations – and the receiving society. In this variant of assimilation theory, societies are viewed as structurally stratified by class, gender, and race, which powerfully influence the resources and opportunities available to immigrants and their descendants and contribute to shaping alternative paths of incorporation. According to segmented assimilation theory, children of immigrants may end up “ascending into the ranks of a prosperous middle class or join in large numbers the ranks of a racialized, permanently impoverished population at the bottom of society” (Portes et al. 2005 , 1004), the latter outcome echoing worries over persistent ethnic and racial disadvantage. Another possible outcome is upward bicultural mobility (selective acculturation) of the children of poorly educated parents, protected by strong community ties.

The major question arising from these related fields of research – the literature on assimilation and integration, on the one hand, and the literature on discrimination, on the other – is whether the gradual diversification of Europe will result in “mainstream expansion,” in which migrants and their descendants over time will ascend the ladders into the middle and upper classes of the societies they live in, or whether we are witnessing the formation of a permanent underclass along ethnic and racial lines. This book will not provide the ultimate answer to this question. However, by introducing the main concepts, theories, and methods in the field of discrimination, as well as pointing out key research findings, policies that are enacted to combat discrimination, and avenues for future research, we hope to provide the reader with an overview of the field.

1.5 The Content of the Book

The literature on discrimination is flourishing, and it involves a wide range of concepts, theories, methods, and findings. Chapter 2 provides the key concepts in the field. The chapter distinguishes between direct and indirect discrimination as legal and sociological concepts, between systemic and institutional discrimination, and between discrimination as intentional actions, subtle biases, and what might be referred to as the cumulative effects of past discrimination on the present. Chapter 3 reviews the main theoretical explanations of discrimination from a cross-disciplinary perspective. Mirroring the historical development of the field, it presents and discusses theories seeking the cause of prejudice and discrimination at the individual, organizational, and structural levels.

Of course, our knowledge of discrimination depends on the methods of measurement, since the phenomenon is mainly visible through its quantification. Hence, Chapter 4 offers an overview of the strengths and weaknesses of available methods of measurement, including statistical analysis of administrative data, surveys among potential victims and perpetrators, qualitative in-depth studies, legal cases, and experimental approaches to the study of discrimination (including survey experiments, lab experiments, and field experiments).

Importantly, discrimination does not occur similarly in all domains of social life, and it takes different forms according to the domain in question (e.g., the labor market, education, housing, health services, and public services). Chapter 5 taps into the large body of empirical work that can be grouped under the heading “discrimination research” in order to provide some key findings, while simultaneously highlighting a distinction between systems of differentiation and systems of equality.

What happens when discrimination occurs? Chapter 6 addresses the consequences of unfair treatment for targeted individuals and groups, as well as their reaction to it. These individual and collective responses to discrimination are seconded by policies designed to tackle discrimination. However, antidiscrimination policies vary greatly across countries, and Chapter 7 provides an overview of the different types of policies against discrimination in Europe and beyond, both public policies and schemes implemented by organizations. The chapter also reflects on some of the key political and societal debates about the implementation and the future of these policies. Chapter 8 concludes on the future of discrimination research in Europe, stressing the main challenges ahead for a burgeoning scientific field.

Alba, R., & Foner, N. (2015). Strangers no more: Immigration and the challenges of integration in North America and Western Europe . Princeton: Princeton University Press.

Book   Google Scholar  

Alba, R., & Nee, V. (2003). Remaking the American mainstream: Assimilation and contemporary immigration . Cambridge: Harvard University Press.

Alba, R., Reitz, J. G., & Simon, P. (2012). National Conceptions of assimilation, integration, and cohesion. In M. Crul & J. H. Mollenkopf (Eds.), The changing face of world cities: Young adult children of immigrants in Europe and the United States (pp. 44–61). New York: Russel Sage.

Google Scholar  

Crul, M. (2016). Super-diversity vs. assimilation: How complex diversity in majority–minority cities challenges the assumptions of assimilation. Journal of Ethnic and Migration Studies, 42 (1), 54–68. https://doi.org/10.1080/1369183X.2015.1061425 .

Article   Google Scholar  

Essed, P. (1991). Understanding everyday racism: An interdisciplinary theory . Newbury Park: Sage.

European Commission. (2007). Discrimination in the European Union (Special Eurobarometer, Vol. 263). Brussels: European Commission.

European Commission. (2015). Discrimination in the EU in 2015 (Special Eurobarometer, Vol. 437). Brussels: European Commission.

Gordon, M. (1964). Assimilation in American life: The role of race, religion, and National Origins . New York: Oxford University Press.

Hainmueller, J., & Hangartner, D. (2013). Who gets a swiss passport? A natural experiment in immigrant discrimination. American Political Science Review, 107 (01), 159–187. https://doi.org/10.1017/S0003055412000494 .

Heath, A. F., & Cheung, S. Y. (Eds.). (2007). Unequal chances: Ethnic minorities in Western labour markets . Oxford: British Academy/Oxford University Press.

Koopmans, R., Michalowski, I., & Waibel, S. (2012). Citizenship rights for immigrants. National political processes and cross-national convergence in Western Europe, 1980–2008. American Journal of Sociology, 117 (4), 1202–2045. https://doi.org/10.1086/662707 .

Portes, A., & Rumbaut, R. (Eds.). (2001). Legacies: The story of the immigrant second generation . Los Angeles: University of California Press.

Portes, A., & Zhou, M. (1993). The new second generation: Segmented assimilation and its variants. The Annals of the American Academy of Political and Social Science, 530 , 74–96. https://doi.org/10.1177/0002716293530001006 .

Portes, A., Fernández-Kelly, P., & Haller, W. (2005). Segmented assimilation on the ground: The new second generation in early adulthood. Ethnic and Racial Studies, 28 (6), 1000–1040. https://doi.org/10.1080/01419870500224117 .

Simon, P. (2012). Collecting ethnic statistics in Europe: A review. Ethnic and Racial Studies, 35 (8), 1366–1391. https://doi.org/10.1080/01419870.2011.607507 .

Van Mol, C., & de Valk, H. (2016). Migration and immigrants in Europe: A historical and demographic perspective. In B. Garcés-Mascareñas & R. Penninx (Eds.), Integration processes and policies in Europe (IMISCOE Research Series). Cham: Springer.

Vertovec, S. (2007). Super-diversity and its implications. Ethnic and Racial Studies, 30 (6), 1024–1054. https://doi.org/10.1080/01419870701599465 .

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Fibbi, R., Midtbøen, A.H., Simon, P. (2021). Introduction: The Case for Discrimination Research. In: Migration and Discrimination. IMISCOE Research Series. Springer, Cham. https://doi.org/10.1007/978-3-030-67281-2_1

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