what does the word theory mean in science

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Scientific Theory Definition and Examples

A scientific theory is a well-established explanation of some aspect of the natural world. Theories come from scientific data and multiple experiments. While it is not possible to prove a theory, a single contrary result using the scientific method can disprove it. In other words, a theory is testable and falsifiable.

Examples of Scientific Theories

There are many scientific theory in different disciplines:

• Astronomy : theory of stellar nucleosynthesis , theory of stellar evolution
• Biology : cell theory, theory of evolution, germ theory, dual inheritance theory
• Chemistry : atomic theory, Bronsted Lowry acid-base theory , kinetic molecular theory of gases , Lewis acid-base theory , molecular theory, valence bond theory
• Geology : climate change theory, plate tectonics theory
• Physics : Big Bang theory, perturbation theory, theory of relativity, quantum field theory

Criteria for a Theory

In order for an explanation of the natural world to be a theory, it meets certain criteria:

• A theory is falsifiable. At some point, a theory withstands testing and experimentation using the scientific method.
• A theory is supported by lots of independent evidence.
• A theory explains existing experimental results and predicts outcomes of new experiments at least as well as other theories.

Difference Between a Scientific Theory and Theory

Usually, a scientific theory is just called a theory. However, a theory in science means something different from the way most people use the word. For example, if frogs rain down from the sky, a person might observe the frogs and say, “I have a theory about why that happened.” While that theory might be an explanation, it is not based on multiple observations and experiments. It might not be testable and falsifiable. It’s not a scientific theory (although it could eventually become one).

Value of Disproven Theories

Even though some theories are incorrect, they often retain value.

For example, Arrhenius acid-base theory does not explain the behavior of chemicals lacking hydrogen that behave as acids. The Bronsted Lowry and Lewis theories do a better job of explaining this behavior. Yet, the Arrhenius theory predicts the behavior of most acids and is easier for people to understand.

Another example is the theory of Newtonian mechanics. The theory of relativity is much more inclusive than Newtonian mechanics, which breaks down in certain frames of reference or at speeds close to the speed of light . But, Newtonian mechanics is much simpler to understand and its equations apply to everyday behavior.

Difference Between a Scientific Theory and a Scientific Law

The scientific method leads to the formulation of both scientific theories and laws . Both theories and laws are falsifiable. Both theories and laws help with making predictions about the natural world. However, there is a key difference.

A theory explains why or how something works, while a law describes what happens without explaining it. Often, you see laws written in the form of equations or formulas.

Theories and laws are related, but theories never become laws or vice versa.

Theory vs Hypothesis

A hypothesis is a proposition that is tested via an experiment. A theory results from many, many tested hypotheses.

Theory vs Fact

Theories depend on facts, but the two words mean different things. A fact is an irrefutable piece of evidence or data. Facts never change. A theory, on the other hand, may be modified or disproven.

Difference Between a Theory and a Model

Both theories and models allow a scientist to form a hypothesis and make predictions about future outcomes. However, a theory both describes and explains, while a model only describes. For example, a model of the solar system shows the arrangement of planets and asteroids in a plane around the Sun, but it does not explain how or why they got into their positions.

• Frigg, Roman (2006). “ Scientific Representation and the Semantic View of Theories .”  Theoria . 55 (2): 183–206. 
• Halvorson, Hans (2012). “What Scientific Theories Could Not Be.”  Philosophy of Science . 79 (2): 183–206. doi: 10.1086/664745
• McComas, William F. (December 30, 2013).  The Language of Science Education: An Expanded Glossary of Key Terms and Concepts in Science Teaching and Learning . Springer Science & Business Media. ISBN 978-94-6209-497-0.
• National Academy of Sciences (US) (1999). Science and Creationism: A View from the National Academy of Sciences (2nd ed.). National Academies Press. doi: 10.17226/6024  ISBN 978-0-309-06406-4. 
• Suppe, Frederick (1998). “Understanding Scientific Theories: An Assessment of Developments, 1969–1998.”  Philosophy of Science . 67: S102–S115. doi: 10.1086/392812

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What Do We Mean by “Theory” in Science?

A theory is a carefully thought-out explanation for observations of the natural world that has been constructed using the scientific method, and which brings together many facts and hypotheses.

In a previous blog post, I talked about the definition of “fact” in a scientific context , and discussed how facts differ from hypotheses and theories. The latter two terms also are well worth looking at in more detail because they are used differently by scientists and the general public, which can cause confusion when scientists talk about their work.

With these definitions in mind, a simplified version of the scientific process would be as follows. A scientist makes an observation of a natural phenomenon. She then devises a hypothesis about the explanation of the phenomenon, and she designs an experiment and/or collects additional data to test the hypothesis. If the test falsifies the hypothesis (i.e., shows that it is incorrect), she will have to develop a new hypothesis and test that. If the hypothesis is corroborated (i.e., not falsified) by the test, the scientist will retain it. If it survives additional scrutiny, she may eventually try to incorporate it into a larger theory that helps to explain her observed phenomenon and relate it to other phenomena. 

That's all fairly abstract, so let's look at a concrete example involving some recent research I undertook with a group of collaborators. The theory of evolution states that the process of natural selection should work to optimize the function of an organism's parts if the changes increase the chances of the organism successfully producing offspring and the changes are heritable (i.e., can be passed down from generation to generation).

But what happens when there are multiple selective pressures at work? We might hypothesize that turtles that spend most of their time in water face a trade-off between having a strong shell and one that is streamlined (making them more efficient swimmers), whereas streamlining would be less important to turtles on land, allowing them to evolve stronger shells even if they aren’t very streamlined.

Our results corroborated our hypothesis that aquatic turtles are forced to make more of a trade-off between strength and streamlining than turtles that live on land. In general, the shell shapes of our aquatic turtles were more streamlined but weaker than those of our land turtles, and our mathematical model of natural selection indicated that selection for streamlining was acting more strongly on the aquatic species.

As with any idea in science, our results are open to further testing. For example, other researchers might develop a better model of natural selection that shows that our model was overly simplistic. Or they might collect data from more turtle species that shows that our results were based on a false pattern stemming from sampling too few species (we considered 47 species in our dataset, about 14% of living turtle species). For now, though, our results can be added as a piece of evidence that is consistent with the predictions of the large explanatory theory of evolution.

If you would like to learn more about this research, the scientific paper describing the work can be found in the Journal of Vertebrate Paleontology . You can see some of the turtle specimens that we used in this research in The Field Museum's exhibition Specimens: Unlocking the Secrets of Life , open through January 7, 2018.

I am a paleobiologist interested in three main topics: 1) understanding the broad implications of the paleobiology and paleoecology of extinct terrestrial vertebrates, particularly in relation to large scale problems such as the evolution of herbivory and the nature of the end-Permian mass extinction; 2) using quantitative methods to document and interpret morphological evolution in fossil and extant vertebrates; and 3) tropic network-based approaches to paleoecology. To address these problems, I integrate data from a variety of biological and geological disciplines including biostratigraphy, anatomy, phylogenetic systematics and comparative methods, functional morphology, geometric morphometrics, and paleoecology.

A list of my publications can be found here.

More information on some of my research projects and other topics can be found on the fossil non-mammalian synapsid page.

Most of my research in vertebrate paleobiology focuses on anomodont therapsids, an extinct clade of non-mammalian synapsids ("mammal-like reptiles") that was one of the most diverse and successful groups of Permian and Triassic herbivores. Much of my dissertation research concentrated on reconstructing a detailed morphology-based phylogeny for Permian members of the clade, as well as using this as a framework for studying anomodont biogeography, the evolution of the group's distinctive feeding system, and anomodont-based biostratigraphic schemes. My more recent research on the group includes: species-level taxonomy of taxa such as Dicynodon , Dicynodontoides , Diictodon , Oudenodon , and Tropidostoma ; development of a higher-level taxonomy for anomodonts; testing whether anomodonts show morphological changes consistent with the hypothesis that end-Permian terrestrial vertebrate extinctions were caused by a rapid decline in atmospheric oxygen levels; descriptions of new or poorly-known anomodonts from Antarctica, Tanzania, and South Africa; and examination of the implications of high growth rates in anomodonts. Fieldwork is an important part of my paleontological research, and recent field areas include the Parnaíba Basin of Brazil , the Karoo Basin of South Africa, the Ruhuhu Basin of Tanzania , and the Luangwa Basin of Zambia. My collaborators and I have made important discoveries in the course of these field projects, including the first remains of dinocephalian synapsids from Tanzania and a dinosaur relative that implies that the two main lineages of archosaurs (one including crocodiles and their relatives and the other including birds and dinosaurs) were diversifying in the early Middle Triassic, only a few million years after the end-Permian extinction. Finally, the experience I have gained while studying Permian and Triassic terrestrial vertebrates forms the foundation for work I am now involved in using models of food webs to investigate how different kinds of biotic and abiotic perturbations could have caused extinctions in ancient communities.

Geometric morphometrics is the basis of most of my quantitative research on evolutionary morphology, and I have been using this technique to address several biological and paleontological questions. For example, I conducted a simulation-based study of how tectonic deformation influences our ability to extract biologically-relevant shape information from fossil specimens, and the effectiveness of different retrodeformation techniques. I also used the method to address taxonomic questions in biostratigraphically-important anomodont taxa, and I served as a co-advisor for a Ph.D. student at the University of Bristol who used geometric morphometrics and finite element analysis to examine the functional significance of skull shape variation in fossil and extant crocodiles. Focusing on more biological questions, I am currently working on a large geometric morphometric study of plastron shape in extant emydine turtles. To date, I have compiled a data set of over 1600 specimens belonging to nine species, and I am using these data to address causes of variation at both the intra- and interspecific level. Some of the main goals of the work are to examine whether plastron morphology reflects a phylogeographic signal identified using molecular data in Emys marmorata , whether the "miniaturized" turtles Glyptemys muhlenbergii and Clemmys guttata have ontogenies that differ from those of their larger relatives, and how habitat preference, phylogeny, and shell kinesis affect shell morphology.

A collaborative project that began during my time as a postdoctoral researcher at the California Academy of Sciences involves using using models of trophic networks to examine how disturbances can spread through communities and cause extinctions. Our model is based on ecological principles, and some of the main data that we are using are a series of Permian and Triassic communities from the Karoo Basin of South Africa. Our research has already shown that the latest Permian Karoo community was susceptible to collapse brought on by primary producer disruption, and that the earliest Triassic Karoo community was very unstable. Presently we are investigating the mechanics that underlie this instability, and we're planning to investigate how the perturbation resistance of communities as changed over time. We've also experimented with ways to use the model to estimate the magnitude and type of disruptions needed to cause observed extinction levels during the end-Permian extinction event in the Karoo. Then there's the research project I've been working on almost my whole life .

Morphology and the stratigraphic occurrences of fossil organisms provide distinct, but complementary information about evolutionary history. Therefore, it is important to consider both sources of information when reconstructing the phylogenetic relationships of organisms with a fossil record, and I am interested how these data sources can be used together in this process. In my empirical work on anomodont phylogeny, I have consistently examined the fit of my morphology-based phylogenetic hypotheses to the fossil record because simulation studies suggest that phylogenies which fit the record well are more likely to be correct. More theoretically, I developed a character-based approach to measuring the fit of phylogenies to the fossil record. I also have shown that measurements of the fit of phylogenetic hypotheses to the fossil record can provide insight into when the direct inclusion of stratigraphic data in the tree reconstruction process results in more accurate hypotheses. Most recently, I co-advised two masters students at the University of Bristol who are examined how our ability to accurately reconstruct a clade's phylogeny changes over the course of the clade's history.

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Definition of theory

Did you know.

The Difference Between Hypothesis and Theory

A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

A hypothesis is usually tentative; it's an assumption or suggestion made strictly for the objective of being tested.

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, it is understood to be more likely to be true than a hypothesis is.

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch, with theory being the more common choice.

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

Two Related, Yet Distinct, Meanings of Theory

There are many shades of meaning to the word theory . Most of these are used without difficulty, and we understand, based on the context in which they are found, what the intended meaning is. For instance, when we speak of music theory we understand it to be in reference to the underlying principles of the composition of music, and not in reference to some speculation about those principles.

However, there are two senses of theory which are sometimes troublesome. These are the senses which are defined as “a plausible or scientifically acceptable general principle or body of principles offered to explain phenomena” and “an unproven assumption; conjecture.” The second of these is occasionally misapplied in cases where the former is meant, as when a particular scientific theory is derided as "just a theory," implying that it is no more than speculation or conjecture . One may certainly disagree with scientists regarding their theories, but it is an inaccurate interpretation of language to regard their use of the word as implying a tentative hypothesis; the scientific use of theory is quite different than the speculative use of the word.

• proposition
• supposition

hypothesis , theory , law mean a formula derived by inference from scientific data that explains a principle operating in nature.

hypothesis implies insufficient evidence to provide more than a tentative explanation.

theory implies a greater range of evidence and greater likelihood of truth.

law implies a statement of order and relation in nature that has been found to be invariable under the same conditions.

Examples of theory in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'theory.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Late Latin theoria , from Greek theōria , from theōrein

1592, in the meaning defined at sense 6

Phrases Containing theory

• atomic theory
• auteur theory
• big bang theory
• Bohr theory
• catastrophe theory
• cell theory
• chaos theory
• conspiracy theory
• critical race theory
• decision theory
• devil theory
• domino theory
• field theory
• Galois theory
• game theory
• gauge theory
• general theory of relativity
• germ theory
• grand unified theory
• graph theory
• group theory
• information theory
• kinetic theory
• knot theory
• number theory
• quantity theory
• quantum field theory
• quantum theory
• queer theory
• special theory of relativity
• steady state theory
• string theory
• theory of games
• theory of numbers
• trickle - down theory
• undulatory theory
• wave theory

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Cite this Entry

“Theory.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/theory. Accessed 17 May. 2024.

Kids Definition

Kids definition of theory.

from Latin theoria "a looking at or considering of facts, theory," from Greek theōria "theory, action of viewing, consideration," from theōrein "to look at, consider," — related to theater

Medical Definition

Medical definition of theory, more from merriam-webster on theory.

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Incorporate STEM journalism in your classroom

• Exercise type: Discussion
• Topic: Earth
• Category: Research & Design

How a scientific theory is born

• Download Student Worksheet

Directions for teachers:

Use the online Science News article “ How the Earth-shaking theory of plate tectonics was born ,” and the prompts below to have students explore scientific theories and determine the process behind creating theories. A version of the story, “Shaking up Earth,” appears in the January 16, 2021 issue of Science News . As a final exercise, have students discuss the definition of a scientific theory and compare it with hypotheses and scientific laws.

This story is the first installment in a series that celebrates Science News ’ upcoming 100th anniversary by highlighting some of the biggest advancements in science over the last century. For more on the story of plate tectonics, and to see the rest of series as it appears, visit Science News ’ Century of Science site at www.sciencenews.org/century .

Want to make it a virtual lesson? Post the online Science News article“ How the Earth-shaking theory of plate tectonics was born ,” to your learning management system. Pair up students and allow them to connect via virtual breakout rooms in a video conference, over the phone, in a shared document or using another chat system. Have each pair submit its answers to the second set of questions to you.

Thinking about theories

Discuss the following questions with a partner before reading the Science News article.

1. What does it mean to say that you have a theory about something? Think of a theory you’ve had about something outside of science.

Typically, when people say that they have theory, it means that they have an idea or philosophy. Student examples of theories will vary.

2. What is one scientific theory you have learned about this year in science? Explain what you remember about it.

Student answers will vary, but may include the general theory of relativity, evolution, etc.

3. How does the general use of the term theory differ from its use in a scientific context?    

Theories in science are explanations rooted in data. Having a theory outside of the scientific context may be based on observations or data, or the term may be used to state a logical idea.

The theory of plate tectonics

Read the online Science News article “How plate tectonics upended our understanding of Earth,” and answer the following questions individually before discussing them as a class.

1. What is the theory of plate tectonics? Over how many years was it developed?

The theory of plate tectonics states that the Earth’s surface is broken up into various pieces (plates) and describes how and why they are constantly in motion and how that motion is linked to features seen on Earth. The theory was developed over about 50 years.

2. Who helped develop the theory and what did they contribute to it? What types of scientists were they and where were they from?

Meteorologist Alfred Wegner proposed the idea of continental drift in 1912, and geologist Arthur Holmes added to that proposal years later with an explanation for how the continents might drift. These ideas were the precursors to the development of the theory of plate tectonics. From there, seismologists, geophysicists, mathematicians and physicists established the ideas, such as seafloor spreading, and found the data necessary to develop the theory. Notable scientists include Lynn Sykes, Harry Hess, Robert S. Dietz, Robert Parker, W. Jason Morgan and Dan McKenzie.  The researchers were from England and the United States.

3. Before the theory’s development, what were the conflicting lines of thought?

Wegner’s proposal sparked debates between mobilists, who supported the idea that the Earth’s surface was in motion, and fixists, who thought the Earth’s surface was static.

4. What did scientists need to resolve the conflict? Why did the conflict take so long to resolve?

In order to resolve the debate, scientists needed evidence. Wegner made his proposal in the early 1900s, but scientific evidence for why the continents move and how didn’t become available until after World War II, when technological advancements allowed scientists to study Earth’s surface and interior, and particularly the bottom of the oceans, in unprecedented detail.

5. How was evidence communicated to other members of the scientific community? Why was the communication important?

Evidence was communicated at conferences attended by scientists including geologists and geophysicists. By building on each other’s ideas and using each other’s data, the scientists were able to go beyond the idea of continental drift and come up with the unified theory of plate tectonics.

Defining a scientific theory

Discuss the following questions with a classmate.

1. Based on your answers to the questions above, how would you define a scientific theory?

A scientific theory is an explanation for how and why a natural phenomenon occurs based on evidence.

2. Think about a scientific hypothesis that you have written or look up an example of a hypothesis. How would you define a hypothesis? How is it different than a theory?

A hypothesis is a proposed explanation for a scientific question that hasn’t been validated with evidence. A theory relies on evidence to explain phenomena, whereas a hypothesis is proposed before the gathering of evidence. A hypothesis can become a theory once it is proven or disproven with supporting evidence.

Possible Extension

What is a scientific law that you have learned about in school? Explain how a scientific law is different than a scientific theory. For more information, watch this Ted-Ed video called “ What’s the difference between a scientific law and a theory? ” by educator Matt Anticole.

Student answers will vary, but could include Newton’s three laws of motion, Bernoulli’s principle, etc. A scientific law is different than a scientific theory in that it describes and predicts the relationships among variables, whereas a scientific theory describes how or why something happens.

Theory Definition in Science

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The definition of a theory in science is very different from the everyday usage of the word. In fact, it's usually called a "scientific theory" to clarify the distinction. In the context of science, a theory is a well-established explanation for scientific data . Theories typically cannot be proven, but they can become established if they are tested by several different scientific investigators. A theory can be disproven by a single contrary result.

Key Takeaways: Scientific Theory

• In science, a theory is an explanation of the natural world that has been repeatedly tested and verified using the scientific method.
• In common usage, the word "theory" means something very different. It could refer to a speculative guess.
• Scientific theories are testable and falsifiable. That is, it's possible a theory might be disproven.
• Examples of theories include the theory of relativity and the theory of evolution.

There are many different examples of scientific theories in different disciplines. Examples include:

• Physics : the big bang theory , atomic theory , theory of relativity, quantum field theory
• Biology : the theory of evolution, cell theory, dual inheritance theory
• Chemistry : the kinetic theory of gases, valence bond theory , Lewis theory, molecular orbital theory
• Geology : plate tectonics theory
• Climatology : climate change theory

Key Criteria for a Theory

There are certain criteria which must be fulfilled for a description to be a theory. A theory is not simply any description that can be used to make predictions!

A theory must do all of the following:

• It must be well-supported by many independent pieces of evidence.
• It must be falsifiable. In other words, it must be possible to test a theory at some point.
• It must be consistent with existing experimental results and able to predict outcomes at least as accurately as any existing theories.

Some theories may be adapted or changed over time to better explain and predict behavior. A good theory can be used to predict natural events that have not occurred yet or have yet to be observed.

Value of Disproven Theories

Over time, some theories have been shown to be incorrect. However, not all discarded theories are useless.

For example, we now know Newtonian mechanics is incorrect under conditions approaching the speed of light and in certain frames of reference. The theory of relativity was proposed to better explain mechanics. Yet, at ordinary speeds, Newtonian mechanics accurately explains and predicts real-world behavior. Its equations are much easier to work with, so Newtonian mechanics remains in use for general physics.

In chemistry, there are many different theories of acids and bases. They involve different explanations for how acids and bases work (e.g., hydrogen ion transfer, proton transfer, electron transfer). Some theories, which are known to be incorrect under certain conditions, remain useful in predicting chemical behavior and making calculations.

Theory vs. Law

Both scientific theories and scientific laws are the result of testing hypotheses via the scientific method . Both theories and laws may be used to make predictions about natural behavior. However, theories explain why something works, while laws simply describe behavior under given conditions. Theories do not change into laws; laws do not change into theories. Both laws and theories may be falsified but contrary evidence.

Theory vs. Hypothesis

A hypothesis is a proposition which requires testing. Theories are the result of many tested hypotheses.

Theory vs Fact

While theories are well-supported and may be true, they are not the same as facts. Facts are irrefutable, while a contrary result may disprove a theory.

Theory vs. Model

Models and theories share common elements, but a theory both describes and explains while a model simply describes. Both models and theory may be used to make predictions and develop hypotheses.

• Frigg, Roman (2006). " Scientific Representation and the Semantic View of Theories ." Theoria . 55 (2): 183–206. 
• Halvorson, Hans (2012). "What Scientific Theories Could Not Be." Philosophy of Science . 79 (2): 183–206. doi: 10.1086/664745
• McComas, William F. (December 30, 2013). The Language of Science Education: An Expanded Glossary of Key Terms and Concepts in Science Teaching and Learning . Springer Science & Business Media. ISBN 978-94-6209-497-0.
• National Academy of Sciences (US) (1999). Science and Creationism: A View from the National Academy of Sciences (2nd ed.). National Academies Press. doi: 10.17226/6024 ISBN 978-0-309-06406-4. 
• Suppe, Frederick (1998). "Understanding Scientific Theories: An Assessment of Developments, 1969–1998." Philosophy of Science . 67: S102–S115. doi: 10.1086/392812
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Theory n., plural: theories [ˈθɪɚ.i] Definition: a scientific explanation of a phenomenon based on a concurring set of scientific data from various independent studies

Table of Contents

Theory Definition

In science, a theory is a scientific explanation of a phenomenon. By scientific , it means it is an explanation or expectation based on a body of facts that have been repeatedly confirmed through methodical observations and experiments. For instance, in mathematics, a mathematical theory attempts to describe a particular class of constructs and includes axioms, theorems, examples, etc . In biology, a theory is a widely accepted explanation of a biological phenomenon based on sound evidence from rigorous empirical experiments and scientific observations. An example of a popular biological theory is Charles Darwin’s  Theory of Evolution by Natural Selection . This theory attempts to explain evolution where natural selection is one of the vital mechanisms that drive organisms to progressively change over successive generations.

Etymology: from Latin theōria, Greek theōría, meaning “a viewing” or “contemplating”. Compare: hypothesis

Watch this vid about scientific theory:

Theory vs. Hypothesis

The term theory is generally used to imply speculation or assumption that has not been fully verified or has relatively limited proof. However, in science, an unproven idea or mere theoretical speculation is regarded as a hypothesis rather than a scientific theory.

A scientific hypothesis is a tentative explanation for a phenomenon and is yet to be tested through a scientific and methodological experiment.  If it is confirmed by repetitive investigations and supports various independent studies, then, the hypothesis will likely be widely accepted by the scientific community, and through time — sans any scientific proof to debunk it — becomes a theory.

Theory vs. Law

Both scientific theories and laws are based on facts and are accepted by the scientific community as the truth. And both are used to make predictions of future events. However, while a scientific theory tells us why and how a phenomenon happens, a scientific law will tell us what to expect in a particular situation, especially through a mathematical equation . (MasterClass, 2020) Therefore, scientific theories and laws are essential in understanding things, particularly to grasp why they happen as they do and to reliably and factually predict results in a given situation or condition .

In biology, we have Mendel’s Laws that can be used as a basis for predicting the genotypes and the phenotypes of the offspring if it conforms to the Mendelian inheritance . Gregor Mendel formulated the Laws of heredity based on the patterns of trait variations, which he noticed when he conducted a series of breeding experiments on garden pea plants. Initially, his principles were not widely accepted until his works were rediscovered and reverified. Now, his principles on heredity are regarded as laws .

Although scientific theories and laws are accepted as scientific facts, they can be disproven when new evidence surfaces.

Mendel’s Laws, for instance, do not apply to some conditions, such as in the case of non-Mendelian inheritance . Codominance , incomplete dominance , and extranuclear inheritance are just some of the many examples of biological inheritance where Mendel’s Laws on heredity do not apply.

• MasterClass. (2020).  Theory vs. Law: Basics of the Scientific Method . MasterClass; MasterClass. https://www.masterclass.com/articles/theory-vs-law-basics-of-the-scientific-method#4-examples-of-scientific-theories

Last updated on July 24th, 2022

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Science and the scientific method: Definitions and examples

Here's a look at the foundation of doing science — the scientific method.

The scientific method

Hypothesis, theory and law, a brief history of science, additional resources, bibliography.

Science is a systematic and logical approach to discovering how things in the universe work. It is also the body of knowledge accumulated through the discoveries about all the things in the universe. 

The word "science" is derived from the Latin word "scientia," which means knowledge based on demonstrable and reproducible data, according to the Merriam-Webster dictionary . True to this definition, science aims for measurable results through testing and analysis, a process known as the scientific method. Science is based on fact, not opinion or preferences. The process of science is designed to challenge ideas through research. One important aspect of the scientific process is that it focuses only on the natural world, according to the University of California, Berkeley . Anything that is considered supernatural, or beyond physical reality, does not fit into the definition of science.

When conducting research, scientists use the scientific method to collect measurable, empirical evidence in an experiment related to a hypothesis (often in the form of an if/then statement) that is designed to support or contradict a scientific theory .

"As a field biologist, my favorite part of the scientific method is being in the field collecting the data," Jaime Tanner, a professor of biology at Marlboro College, told Live Science. "But what really makes that fun is knowing that you are trying to answer an interesting question. So the first step in identifying questions and generating possible answers (hypotheses) is also very important and is a creative process. Then once you collect the data you analyze it to see if your hypothesis is supported or not."

The steps of the scientific method go something like this, according to Highline College :

• Make an observation or observations.
• Form a hypothesis — a tentative description of what's been observed, and make predictions based on that hypothesis.
• Test the hypothesis and predictions in an experiment that can be reproduced.
• Analyze the data and draw conclusions; accept or reject the hypothesis or modify the hypothesis if necessary.
• Reproduce the experiment until there are no discrepancies between observations and theory. "Replication of methods and results is my favorite step in the scientific method," Moshe Pritsker, a former post-doctoral researcher at Harvard Medical School and CEO of JoVE, told Live Science. "The reproducibility of published experiments is the foundation of science. No reproducibility — no science."

Some key underpinnings to the scientific method:

• The hypothesis must be testable and falsifiable, according to North Carolina State University . Falsifiable means that there must be a possible negative answer to the hypothesis.
• Research must involve deductive reasoning and inductive reasoning . Deductive reasoning is the process of using true premises to reach a logical true conclusion while inductive reasoning uses observations to infer an explanation for those observations.
• An experiment should include a dependent variable (which does not change) and an independent variable (which does change), according to the University of California, Santa Barbara .
• An experiment should include an experimental group and a control group. The control group is what the experimental group is compared against, according to Britannica .

The process of generating and testing a hypothesis forms the backbone of the scientific method. When an idea has been confirmed over many experiments, it can be called a scientific theory. While a theory provides an explanation for a phenomenon, a scientific law provides a description of a phenomenon, according to The University of Waikato . One example would be the law of conservation of energy, which is the first law of thermodynamics that says that energy can neither be created nor destroyed. 

A law describes an observed phenomenon, but it doesn't explain why the phenomenon exists or what causes it. "In science, laws are a starting place," said Peter Coppinger, an associate professor of biology and biomedical engineering at the Rose-Hulman Institute of Technology. "From there, scientists can then ask the questions, 'Why and how?'"

Laws are generally considered to be without exception, though some laws have been modified over time after further testing found discrepancies. For instance, Newton's laws of motion describe everything we've observed in the macroscopic world, but they break down at the subatomic level.

This does not mean theories are not meaningful. For a hypothesis to become a theory, scientists must conduct rigorous testing, typically across multiple disciplines by separate groups of scientists. Saying something is "just a theory" confuses the scientific definition of "theory" with the layperson's definition. To most people a theory is a hunch. In science, a theory is the framework for observations and facts, Tanner told Live Science.

The earliest evidence of science can be found as far back as records exist. Early tablets contain numerals and information about the solar system , which were derived by using careful observation, prediction and testing of those predictions. Science became decidedly more "scientific" over time, however.

1200s: Robert Grosseteste developed the framework for the proper methods of modern scientific experimentation, according to the Stanford Encyclopedia of Philosophy. His works included the principle that an inquiry must be based on measurable evidence that is confirmed through testing.

1400s: Leonardo da Vinci began his notebooks in pursuit of evidence that the human body is microcosmic. The artist, scientist and mathematician also gathered information about optics and hydrodynamics.

1500s: Nicolaus Copernicus advanced the understanding of the solar system with his discovery of heliocentrism. This is a model in which Earth and the other planets revolve around the sun, which is the center of the solar system.

1600s: Johannes Kepler built upon those observations with his laws of planetary motion. Galileo Galilei improved on a new invention, the telescope, and used it to study the sun and planets. The 1600s also saw advancements in the study of physics as Isaac Newton developed his laws of motion.

1700s: Benjamin Franklin discovered that lightning is electrical. He also contributed to the study of oceanography and meteorology. The understanding of chemistry also evolved during this century as Antoine Lavoisier, dubbed the father of modern chemistry , developed the law of conservation of mass.

1800s: Milestones included Alessandro Volta's discoveries regarding electrochemical series, which led to the invention of the battery. John Dalton also introduced atomic theory, which stated that all matter is composed of atoms that combine to form molecules. The basis of modern study of genetics advanced as Gregor Mendel unveiled his laws of inheritance. Later in the century, Wilhelm Conrad Röntgen discovered X-rays , while George Ohm's law provided the basis for understanding how to harness electrical charges.

1900s: The discoveries of Albert Einstein , who is best known for his theory of relativity, dominated the beginning of the 20th century. Einstein's theory of relativity is actually two separate theories. His special theory of relativity, which he outlined in a 1905 paper, " The Electrodynamics of Moving Bodies ," concluded that time must change according to the speed of a moving object relative to the frame of reference of an observer. His second theory of general relativity, which he published as " The Foundation of the General Theory of Relativity ," advanced the idea that matter causes space to curve.

In 1952, Jonas Salk developed the polio vaccine , which reduced the incidence of polio in the United States by nearly 90%, according to Britannica . The following year, James D. Watson and Francis Crick discovered the structure of DNA , which is a double helix formed by base pairs attached to a sugar-phosphate backbone, according to the National Human Genome Research Institute .

2000s: The 21st century saw the first draft of the human genome completed, leading to a greater understanding of DNA. This advanced the study of genetics, its role in human biology and its use as a predictor of diseases and other disorders, according to the National Human Genome Research Institute .

• This video from City University of New York delves into the basics of what defines science.
• Learn about what makes science science in this book excerpt from Washington State University .
• This resource from the University of Michigan — Flint explains how to design your own scientific study.

Merriam-Webster Dictionary, Scientia. 2022. https://www.merriam-webster.com/dictionary/scientia

University of California, Berkeley, "Understanding Science: An Overview." 2022. ​​ https://undsci.berkeley.edu/article/0_0_0/intro_01  

Highline College, "Scientific method." July 12, 2015. https://people.highline.edu/iglozman/classes/astronotes/scimeth.htm  

North Carolina State University, "Science Scripts." https://projects.ncsu.edu/project/bio183de/Black/science/science_scripts.html  

University of California, Santa Barbara. "What is an Independent variable?" October 31,2017. http://scienceline.ucsb.edu/getkey.php?key=6045  

Encyclopedia Britannica, "Control group." May 14, 2020. https://www.britannica.com/science/control-group  

The University of Waikato, "Scientific Hypothesis, Theories and Laws." https://sci.waikato.ac.nz/evolution/Theories.shtml  

Stanford Encyclopedia of Philosophy, Robert Grosseteste. May 3, 2019. https://plato.stanford.edu/entries/grosseteste/  

Encyclopedia Britannica, "Jonas Salk." October 21, 2021. https://www.britannica.com/ biography /Jonas-Salk

National Human Genome Research Institute, "​Phosphate Backbone." https://www.genome.gov/genetics-glossary/Phosphate-Backbone  

National Human Genome Research Institute, "What is the Human Genome Project?" https://www.genome.gov/human-genome-project/What  

‌ Live Science contributor Ashley Hamer updated this article on Jan. 16, 2022.

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[ thee - uh -ree , theer -ee ]

Einstein's theory of relativity.

Synonyms: doctrine , law , principle

Synonyms: thesis , postulate , concept , notion , idea

number theory.

music theory.

conflicting theories of how children best learn to read.

the theory that there is life on other planets.

Synonyms: view , deduction , conclusion , judgment , opinion , thought

My theory is that he never stops to think words have consequences.

Synonyms: presumption , supposition , surmise , hypothesis

• a system of rules, procedures, and assumptions used to produce a result
• abstract knowledge or reasoning

I have a theory about that

• an ideal or hypothetical situation (esp in the phrase in theory )

the theory of relativity

• a nontechnical name for hypothesis

/ thē ′ ə-rē,thîr ′ ē /

• A set of statements or principles devised to explain a group of facts or phenomena. Most theories that are accepted by scientists have been repeatedly tested by experiments and can be used to make predictions about natural phenomena.
• See Note at hypothesis
• In science, an explanation or model that covers a substantial group of occurrences in nature and has been confirmed by a substantial number of experiments and observations. A theory is more general and better verified than a hypothesis . ( See Big Bang theory , evolution , and relativity .)

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Word history and origins.

Origin of theory 1

Idioms and Phrases

In theory, mapping the human genome may lead to thousands of cures.

Synonym Study

Example sentences.

“Our prosecutors have all too often inserted themselves into the political process based on the flimsiest of legal theories,” Barr went on.

Turn Wilson’s mathematical crank, and you get a related theory describing groups of those pieces — perhaps billiard ball molecules.

She also learns immediately that this theory is “not just incorrect but hateful, like saying that different races had different IQs” — and yet, “in my heart, I knew that Whorf was right,” that language does change the way you think.

It applies a different random error to each piece of information that’s encoded—which in theory makes it impossible to break without knowing the key.

Kindrachuk also works on ebola, and he says over the years many such theories have been put forth in scientific journals without provoking this kind of response.

But at the heart of this “Truther” conspiracy theory is the idea that “someone” wants to destroy Bill Cosby.

Is it sort of evidence of the Gladwellian 10,000 hours theory?

But a 2011 study of genetic evidence from 30 ethnic groups in India disproved this theory.

But, in theory, that started to change last week with the first meeting of SIX, the State Innovation Exchange.

So I was happy to see that the European theory of terroir was in action, promoting with pride the qualities of a specific region.

In the year of misery, of agony and suffering in general he had endured, he had settled upon one theory.

Dean Swift was indeed a misanthrope by theory, however he may have made exception to private life.

The other is the new theory: that the Bible is the work of many men whom God had inspired to speak or write the truth.

The evolution theory alleges that they were evolved, slowly, by natural processes out of previously existing matter.

And our surroundings at that particular moment were not the most favorable to coherent thought or plausible theory-building.

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Definitions and idiom definitions from Dictionary.com Unabridged, based on the Random House Unabridged Dictionary, © Random House, Inc. 2023

Idioms from The American Heritage® Idioms Dictionary copyright © 2002, 2001, 1995 by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company.

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13.7 Cosmos & Culture

Why is 'theory' such a confusing word.

Marcelo Gleiser

Theoretically speaking, there is widespread confusion about the word "theory." Right?

Many people interpret the word as iffy knowledge, based mostly on speculative thinking. It is used indiscriminately to indicate things we know — that is, based on solid empirical evidence — and things we aren't sure about. Not a good mix at all, especially when certain theories speak directly to people's religious and value-based sensitivities, such as the "theory of evolution" or "Big Bang theory." There is also the danger of falling for meaning traps set by groups with specific agendas.

Looking at the New Oxford American Dictionary (NOAD) listing for "theory" doesn't help:

• a supposition or a system of ideas intended to explain something, especially one based on general principles independent of the thing to be explained: Darwin's theory of evolution .
• A set of principles on which the practice of an activity is based: a theory of education .
• An idea used to account for a situation or justify a course of action: my theory would be that...

So, there is usage within a scientific context ("the theory of...") and in a subjective context ("my theory is...") — an obvious problem.

When used in the context of a phrase, as "in theory," it gets worse. According to NOAD, "used in describing what is supposed to happen or be possible, usually with the implication that it does not in fact happen." [My italics.] Clearly, in this context, "in theory" means something that is probably wrong.

No wonder there is confusion. It is confusing!

A first step in trying to clarify the meaning(s) of theory is to understand in which context the word is being used, and to keep different contexts separate. So, if a scientist is using the word theory, as in "theory of relativity," "theory of evolution," or "Big Bang theory," it should be understood as a statement within a scientific context. In this case, a theory is certainly NOT mere subjective speculation, or something that is probably wrong, but, quite the contrary, something that has been scrutinized by the scientific process of empirical validation and has, so far, passed the test of explaining the data.

Unfortunately, even within the scientific context the word is misused, which only adds to the confusion. For example, "superstring theory" refers to a speculative theory in high-energy physics where the fundamental building blocks of matter are not elementary particles but tiny vibrating tubes of energy. Given the lack of empirical support so far for the idea, "superstring hypothesis" would be a much more appropriate characterization. Scientists may know the status of the hypothesis, but most people won't. We should be more careful.

A scientific theory is an accumulated body of knowledge constructed to describe specific natural phenomena, such as the force of gravity or biodiversity, that has been vetted by the scientific community. It is the best that we can come up with to make sense of nature at a given time.

Mind you, as our understanding of natural phenomena change, theories can change as well. This doesn't necessarily mean that the old theories are wrong . It usually means that the old theories have a limited range of validity not covered by newly discovered phenomena. For example, Newton's theory of gravity works really well to send rocket ships to Neptune, but not to describe a black hole. New theories are born from the cracks in old ones.

Unfortunately, suspicion of certain scientific theories can come from confusing subjective speculation with objective description. A scientific theory is different from a scientific hypothesis. A scientific hypothesis is an idea not yet empirically tested and, hence, still not vetted by the scientific community. A theory is a hypothesis that has been tested and vetted.

Much popular confusion could be avoided if the word theory would be understood within the right context. The often-used trap of exploring the double meaning of the word theory to confuse or willfully misguide popular opinion should only catch those who don't know, or choose to neglect, what theory means within its scientific or subjective context.

Marcelo Gleiser is a theoretical physicist and cosmologist — and professor of natural philosophy, physics and astronomy at Dartmouth College. He is the co-founder of 13.7, a prolific author of papers and essays, and active promoter of science to the general public. His latest book is The Island of Knowledge: The Limits of Science and the Search for Meaning . You can keep up with Marcelo on Facebook and Twitter: @mgleiser .

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April 2, 2013

"Just a Theory": 7 Misused Science Words

From "significant" to "natural," here are seven scientific terms that can prove troublesome for the public and across research disciplines

By Tia Ghose & LiveScience

Hypothesis. Theory. Law. These scientific words get bandied about regularly, yet the general public usually gets their meaning wrong.

Now, one scientist is arguing that people should do away with these misunderstood words altogether and replace them with the word "model." But those aren't the only science words that cause trouble, and simply replacing the words with others will just lead to new, widely misunderstood terms, several other scientists said.

"A word like 'theory' is a technical scientific term," said Michael Fayer, a chemist at Stanford University. "The fact that many people understand its scientific meaning incorrectly does not mean we should stop using it. It means we need better scientific education ."

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From "theory" to "significant," here are seven scientific words that are often misused.

1. Hypothesis

The general public so widely misuses the words hypothesis , theory and law that scientists should stop using these terms, writes physicist Rhett Allain of Southeastern Louisiana University, in a blog post on Wired Science. [ Amazing Science: 25 Fun Facts ]

"I don't think at this point it's worth saving those words," Allain told LiveScience.

A hypothesis is a proposed explanation for something that can actually be tested. But "if you just ask anyone what a hypothesis is, they just immediately say 'educated guess,'" Allain said.

2. Just a theory?

Climate-change deniers and creationists have deployed the word "theory" to cast doubt on climate change and evolution.

"It's as though it weren't true because it's just a theory," Allain said.

 That's despite the fact that an overwhelming amount of evidence supports both human-caused climate change and Darwin's theory of evolution .

Part of the problem is that the word "theory" means something very different in lay language than it does in science: A scientific theory is an explanation of some aspect of the natural world that has been substantiated through repeated experiments or testing. But to the average Jane or Joe, a theory is just an idea that lives in someone's head, rather than an explanation rooted in experiment and testing.

However, theory isn't the only science phrase that causes trouble. Even Allain's preferred term to replace hypothesis, theory and law -- "model" -- has its troubles. The word not only refers to toy cars and runway walkers, but also means different things in different scientific fields. A climate model is very different from a mathematical model, for instance.

"Scientists in different fields use these terms differently from each other," John Hawks, an anthropologist at the University of Wisconsin-Madison, wrote in an email to LiveScience. "I don't think that 'model' improves matters. It has an appearance of solidity in physics right now mainly because of the Standard Model. By contrast, in genetics and evolution, 'models' are used very differently." (The Standard Model is the dominant theory governing particle physics.)

When people don't accept human-caused climate change, the media often describes those individuals as " climate skeptics ." But that may give them too much credit, Michael Mann, a climate scientist at Pennsylvania State University, wrote in an email.

"Simply denying mainstream science based on flimsy, invalid and too-often agenda-driven critiques of science is not skepticism at all. It is contrarianism ... or denial," Mann told LiveScience.

Instead, true skeptics are open to scientific evidence and are willing to evenly assess it.

"All scientists should be skeptics. True skepticism is, as [Carl] Sagan described it, the 'self-correcting machinery' of science," Mann said. 

5. Nature vs. nurture

The phrase " nature versus nurture " also gives scientists a headache, because it radically simplifies a very complicated process, said Dan Kruger, an evolutionary biologist at the University of Michigan.

"This is something that modern evolutionists cringe at," Kruger told LiveScience.

Genes may influence human beings, but so, too, do epigenetic changes . These modifications alter which genes get turned on, and are both heritable and easily influenced by the environment. The environment that shapes human behavior can be anything from the chemicals a fetus is exposed to in the womb to the block a person grew up on to the type of food they ate as a child, Kruger said. All these factors interact in a messy, unpredictable way.

6. Significant

Another word that sets scientists' teeth on edge is "significant."

"That's a huge weasel word. Does it mean statistically significant, or does it mean important?" said Michael O'Brien, the dean of the College of Arts and Science at the University of Missouri.

In statistics, something is significant if a difference is unlikely to be due to random chance. But that may not translate into a meaningful difference, in, say, headache symptoms or IQ.

"Natural" is another bugaboo for scientists. The term has become synonymous with being virtuous, healthy or good. But not everything artificial is unhealthy, and not everything that's natural is good for you .

"Uranium is natural, and if you inject enough of it, you're going to die," Kruger said.

Natural's sibling "organic" also has a problematic meaning, he said. While organic simply means "carbon-based" to scientists, the term is now used to describe pesticide-free peaches and high-end cotton sheets, as well.

Bad education

But though these words may be routinely misunderstood, the real problem, scientists say, is that people don't get rigorous science education in middle school and high school. As a result, the public doesn't understand how scientific explanations are formed , tested and accepted.

What's more, the human brain may not have evolved to intuitively understand key scientific concepts such as hypotheses or theories, Kruger said.

Most people tend to use mental shortcuts to make sense of the cacophony of information they're presented with every day.

One of those tendencies is to make a "binary distinction between something that is true in an absolute sense and something that's false or a lie," Kruger said. "With science, it's more of a continuum. We're continually building our understanding."

Top 10 Mysteries of the Mind

The Reality of Climate Change: 10 Myths Busted

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Copyright 2013 LiveScience, a TechMediaNetwork company. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.

Definitions of Fact, Theory, and Law in Scientific Work

Science uses specialized terms that have different meanings than everyday usage. These definitions correspond to the way scientists typically use these terms in the context of their work. Note, especially, that the meaning of “theory” in science is different than the meaning of “theory” in everyday conversation.

• Fact: In science, an observation that has been repeatedly confirmed and for all practical purposes is accepted as “true.” Truth in science, however, is never final and what is accepted as a fact today may be modified or even discarded tomorrow.
• Hypothesis: A tentative statement about the natural world leading to deductions that can be tested. If the deductions are verified, the hypothesis is provisionally corroborated. If the deductions are incorrect, the original hypothesis is proved false and must be abandoned or modified. Hypotheses can be used to build more complex inferences and explanations.
• Law: A descriptive generalization about how some aspect of the natural world behaves under stated circumstances.
• Theory: In science, a well-substantiated explanation of some aspect of the natural world that can incorporate facts, laws, inferences, and tested hypotheses.

The Role of Theory in Advancing 21st-Century Biology , National Academy of Sciences Teaching About Evolution and the Nature of Science , National Academy of Sciences

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Word Meaning

Word meaning has played a somewhat marginal role in early contemporary philosophy of language, which was primarily concerned with the structural features of sentence meaning and showed less interest in the nature of the word-level input to compositional processes. Nowadays, it is well-established that the study of word meaning is crucial to the inquiry into the fundamental properties of human language. This entry provides an overview of the way issues related to word meaning have been explored in analytic philosophy and a summary of relevant research on the subject in neighboring scientific domains. Though the main focus will be on philosophical problems, contributions from linguistics, psychology, neuroscience and artificial intelligence will also be considered, since research on word meaning is highly interdisciplinary.

1.1 The Notion of Word

1.2 theories of word meaning, 2.1 classical traditions, 2.2 historical-philological semantics, 3.1 early contemporary views, 3.2 grounding and lexical competence, 3.3 the externalist turn, 3.4 internalism, 3.5 contextualism, minimalism, and the lexicon, 4.1 structuralist semantics, 4.2 generativist semantics, 4.3 decompositional approaches, 4.4 relational approaches, 5.1 cognitive linguistics, 5.2 psycholinguistics, 5.3 neurolinguistics, other internet resources, related entries.

The notions of word and word meaning are problematic to pin down, and this is reflected in the difficulties one encounters in defining the basic terminology of lexical semantics. In part, this depends on the fact that the term ‘word’ itself is highly polysemous (see, e.g., Matthews 1991; Booij 2007; Lieber 2010). For example, in ordinary parlance ‘word’ is ambiguous between a type-level reading (as in “ Color and colour are spellings of the same word”), an occurrence-level reading (as in “there are thirteen words in the tongue-twister How much wood would a woodchuck chuck if a woodchuck could chuck wood? ”), and a token-level reading (as in “John erased the last two words on the blackboard”). Before proceeding further, let us then elucidate the notion of word in more detail ( Section 1.1 ), and lay out the key questions that will guide our discussion of word meaning in the rest of the entry ( Section 1.2 ).

We can distinguish two fundamental approaches to the notion of word. On one side, we have linguistic approaches, which characterize the notion of word by reflecting on its explanatory role in linguistic research (for a survey on explanation in linguistics, see Egré 2015). These approaches often end up splitting the notion of word into a number of more fine-grained and theoretically manageable notions, but still tend to regard ‘word’ as a term that zeroes in on a scientifically respectable concept (e.g., Di Sciullo & Williams 1987). For example, words are the primary locus of stress and tone assignment, the basic domain of morphological conditions on affixation, clitization, compounding, and the theme of phonological and morphological processes of assimilation, vowel shift, metathesis, and reduplication (Bromberger 2011).

On the other side, we have metaphysical approaches, which attempt to pin down the notion of word by inquiring into the metaphysical nature of words. These approaches typically deal with such questions as “what are words?”, “how should words be individuated?”, and “on what conditions two utterances count as utterances of the same word?”. For example, Kaplan (1990, 2011) has proposed to replace the orthodox type-token account of the relation between words and word tokens with a “common currency” view on which words relate to their tokens as continuants relate to stages in four-dimensionalist metaphysics (see the entries on types and tokens and identity over time ). Other contributions to this debate can be found, a.o., in McCulloch (1991), Cappelen (1999), Alward (2005), Hawthorne & Lepore (2011), Sainsbury & Tye (2012), Gasparri (2016), and Irmak (forthcoming).

For the purposes of this entry, we can rely on the following stipulation. Every natural language has a lexicon organized into lexical entries , which contain information about word types or lexemes . These are the smallest linguistic expressions that are conventionally associated with a non-compositional meaning and can be articulated in isolation to convey semantic content. Word types relate to word tokens and occurrences just like phonemes relate to phones in phonological theory. To understand the parallelism, think of the variations in the place of articulation of the phoneme /n/, which is pronounced as the voiced bilabial nasal [m] in “ten bags” and as the voiced velar nasal [ŋ] in “ten gates”. Just as phonemes are abstract representations of sets of phones (each defining one way the phoneme can be instantiated in speech), lexemes can be defined as abstract representations of sets of words (each defining one way the lexeme can be instantiated in sentences). Thus, ‘do’, ‘does’, ‘done’ and ‘doing’ are morphologically and graphically marked realizations of the same abstract word type do . To wrap everything into a single formula, we can say that the lexical entries listed in a lexicon set the parameters defining the instantiation potential of word types in sentences, utterances and inscriptions (cf. Murphy 2010). In what follows, unless otherwise indicated, our talk of “word meaning” should be understood as talk of “word type meaning” or “lexeme meaning”, in the sense we just illustrated.

As with general theories of meaning (see the entry on theories of meaning ), two kinds of theory of word meaning can be distinguished. The first kind, which we can label a semantic theory of word meaning, is a theory interested in clarifying what meaning-determining information is encoded by the words of a natural language. A framework establishing that the word ‘bachelor’ encodes the lexical concept adult unmarried male would be an example of a semantic theory of word meaning. The second kind, which we can label a foundational theory of word meaning, is a theory interested in elucidating the facts in virtue of which words come to have the semantic properties they have for their users. A framework investigating the dynamics of semantic change and social coordination in virtue of which the word ‘bachelor’ is assigned the function of expressing the lexical concept adult unmarried male would be an example of a foundational theory of word meaning. Likewise, it would be the job of a foundational theory of word meaning to determine whether words have the semantic properties they have in virtue of social conventions, or whether social conventions do not provide explanatory purchase on the facts that ground word meaning (see the entry on convention ).

Obviously, the endorsement of a given semantic theory is bound to place important constraints on the claims one might propose about the foundational attributes of word meaning, and vice versa . Semantic and foundational concerns are often interdependent, and it is difficult to find theories of word meaning which are either purely semantic or purely foundational. According to Ludlow (2014), for example, the fact that word meaning is systematically underdetermined (a semantic matter) can be explained in part by looking at the processes of linguistic negotiation whereby discourse partners converge on the assignment of shared meanings to the words of their language (a foundational matter). However, semantic and foundational theories remain in principle different and designed to answer partly non-overlapping sets of questions.

Our focus in this entry will be on semantic theories of word meaning, i.e., on theories that try to provide an answer to such questions as “what is the nature of word meaning?”, “what do we know when we know the meaning of a word?”, and “what (kind of) information must a speaker associate to the words of a language in order to be a competent user of its lexicon?”. However, we will engage in foundational considerations whenever necessary to clarify how a given framework addresses issues in the domain of a semantic theory of word meaning.

2. Historical Background

The study of word meaning became a mature academic enterprise in the 19 th century, with the birth of historical-philological semantics ( Section 2.2 ). Yet, matters related to word meaning had been the subject of much debate in earlier times. We can distinguish three major classical approaches to word meaning: speculative etymology, rhetoric, and classical lexicography (Meier-Oeser 2011; Geeraerts 2013). We describe them briefly in Section 2.1 .

The prototypical example of speculative etymology is perhaps the Cratylus (383a-d), where Plato presents his well-known naturalist thesis about word meaning. According to Plato, natural kind terms express the essence of the objects they denote and words are appropriate to their referents insofar as they implicitly describe the properties of their referents (see the entry on Plato’s Cratylus ). For example, the Greek word ‘ anthrôpos ’ can be broken down into anathrôn ha opôpe , which translates as “one who reflects on what he has seen”: the word used to denote humans reflects their being the only animal species which possesses the combination of vision and intelligence. For speculative etymology, there is a natural or non-arbitrary relation between words and their meaning, and the task of the theorist is to make this relation explicit through an analysis of the descriptive, often phonoiconic mechanisms underlying the genesis of words. More on speculative etymology in Malkiel (1993), Fumaroli (1999), and Del Bello (2007).

The primary aim of the rhetorical tradition was the study of figures of speech. Some of these concern sentence-level variables such as the linear order of the words occurring in a sentence (e.g., parallelism, climax, anastrophe); others are lexical in nature and depend on using words in a way not intended by their normal or literal meaning (e.g., metaphor, metonymy, synecdoche). Although originated for stylistic and literary purposes, the identification of regular patterns in the figurative use of words initiated by the rhetorical tradition provided a first organized framework to investigate the semantic flexibility of words, and laid the groundwork for further inquiry into our ability to use lexical expressions beyond the boundaries of their literal meaning. More on the rhetorical tradition in Kennedy (1994), Herrick (2004), and Toye (2013).

Finally, classical lexicography and the practice of writing dictionaries played an important role in systematizing the descriptive data on which later inquiry would rely to illuminate the relationship between words and their meaning. Putnam’s (1970) claim that it was the phenomenon of writing (and needing) dictionaries that gave rise to the idea of a semantic theory is probably an overstatement. But the inception of lexicography certainly had an impact on the development of modern theories of word meaning. The practice of separating dictionary entries via lemmatization and defining them through a combination of semantically simpler elements provided a stylistic and methodological paradigm for much subsequent research on lexical phenomena, such as decompositional theories of word meaning. More on classical lexicography in Béjoint (2000), Jackson (2002), and Hanks (2013).

Historical-philological semantics incorporated elements from all the above classical traditions and dominated the linguistic scene roughly from 1870 to 1930, with the work of scholars such as Michel Bréal, Hermann Paul, and Arsène Darmesteter (Gordon 1982). In particular, it absorbed from speculative etymology an interest in the conceptual mechanisms underlying the formation of word meaning, it acquired from rhetorical analysis a taxonomic toolkit for the classification of lexical phenomena, and it assimilated from lexicography and textual philology the empirical basis of descriptive data that subsequent theories of word meaning would have to account for (Geeraerts 2013).

On the methodological side, the key features of the approach to word meaning introduced by historical-philological semantics can be summarized as follows. First, it had a diachronic and pragmatic orientation. That is, it was primarily concerned with the historical evolution of word meaning rather than with word meaning statically understood, and attributed great importance to the contextual flexibility of word meaning. Witness Paul’s (1920 [1880]) distinction between usuelle Bedeutung and okkasionelle Bedeutung , or Bréal’s (1924 [1897]) account of polysemy as a byproduct of semantic change. Second, it looked at word meaning primarily as a psychological phenomenon. It assumed that the semantic properties of words should be defined in mentalistic terms (i.e., words signify “concepts” or “ideas” in a broad sense), and that the dynamics of sense modulation, extension, and contraction that underlie lexical change correspond to broader patterns of conceptual activity in the human mind. Interestingly, while the classical rhetorical tradition had conceived of tropes as marginal linguistic phenomena whose investigation, albeit important, was primarily motivated by stylistic concerns, for historical-philological semantics the psychological mechanisms underlying the production and the comprehension of figures of speech were part of the ordinary life of languages, and engines of the evolution of all aspects of lexical systems (Nerlich 1992).

The contribution made by historical-philological semantics to the study of word meaning had a long-lasting influence. First, with its emphasis on the principles of semantic change, historical-philological semantics was the first systematic framework to focus on the dynamic nature of word meaning, and established contextual flexibility as the primary explanandum for a theory of word meaning (Nerlich & Clarke 1996, 2007). This feature of historical-philological semantics is a clear precursor of the emphasis placed on context-sensitivity by many subsequent approaches to word meaning, both in philosophy (see Section 3 ) and in linguistics (see Section 4 ). Second, the psychologistic approach to word meaning fostered by historical philological-semantics added to the agenda of linguistic research the question of how word meaning relates to cognition at large. If word meaning is essentially a psychological phenomenon, what psychological categories should be used to characterize it? What is the dividing line separating the aspects of our mental life that constitute knowledge of word meaning from those that do not? As we shall see, this question will constitute a central concern for cognitive theories of word meaning (see Section 5 ).

3. Philosophy of Language

In this section we shall review some semantic and metasemantic theories in analytic philosophy that bear on how lexical meaning should be conceived and described. We shall follow a roughly chronological order. Some of these theories, such as Carnap’s theory of meaning postulates and Putnam’s theory of stereotypes, have a strong focus on lexical meaning, whereas others, such as Montague semantics, regard it as a side issue. However, such negative views form an equally integral part of the philosophical debate on word meaning.

By taking the connection of thoughts and truth as the basic issue of semantics and regarding sentences as “the proper means of expression for a thought” (Frege 1979a [1897]), Frege paved the way for the 20 th century priority of sentential meaning over lexical meaning: the semantic properties of subsentential expressions such as individual words were regarded as derivative, and identified with their contribution to sentential meaning. Sentential meaning was in turn identified with truth conditions, most explicitly in Wittgenstein’s Tractatus logico-philosophicus (1922). However, Frege never lost interest in the “building blocks of thoughts” (Frege 1979b [1914]), i.e., in the semantic properties of subsentential expressions. Indeed, his theory of sense and reference for names and predicates may be counted as the inaugural contribution to lexical semantics within the analytic tradition (see the entry on Gottlob Frege ). It should be noted that Frege did not attribute semantic properties to lexical units as such, but to what he regarded as a sentence’s logical constituents: e.g., not to the word ‘dog’ but to the predicate ‘is a dog’. In later work this distinction was obliterated and Frege’s semantic notions came to be applied to lexical units.

Possibly because of lack of clarity affecting the notion of sense, and surely because of Russell’s (1905) authoritative criticism of Fregean semantics, word meaning disappeared from the philosophical scene during the 1920s and 1930s. In Wittgenstein’s Tractatus the “real” lexical units, i.e., the constituents of a completely analyzed sentence, are just names, whose semantic properties are exhausted by their reference. In Tarski’s (1933) work on formal languages, which was taken as definitional of the very field of semantics for some time, lexical units are semantically categorized into different classes (individual constants, predicative constants, functional constants) depending on the logical type of their reference, i.e., according to whether they designate individuals in a domain of interpretation, classes of individuals (or of n -tuples of individuals), or functions defined over the domain. However, Tarski made no attempt nor felt any need to represent semantic differences among expressions belonging to the same logical type (e.g., between one-place predicates such as ‘dog’ and ‘run’, or between two-place predicates such as ‘love’ and ‘left of’). See the entry on Alfred Tarski .

Quine (1943) and Church (1951) rehabilitated Frege’s distinction of sense and reference. Non-designating words such as ‘Pegasus’ cannot be meaningless: it is precisely the meaning of ‘Pegasus’ that allows speakers to establish that the word lacks reference. Moreover, as Frege (1892) had argued, true factual identities such as “Morning Star = Evening Star” do not state synonymies; if they did, any competent speaker of the language would be aware of their truth. Along these lines, Carnap (1947) proposed a new formulation of the sense/reference dichotomy, which was translated into the distinction between intension and extension . The notion of intension was intended to be an explicatum of Frege’s “obscure” notion of sense: two expressions have the same intension if and only if they have the same extension in every possible world or, in Carnap’s terminology, in every state description (i.e., in every maximal consistent set of atomic sentences and negations of atomic sentences). Thus, ‘round’ and ‘spherical’ have the same intension (i.e., they express the same function from possible worlds to extensions) because they apply to the same objects in every possible world. Carnap later suggested that intensions could be regarded as the content of lexical semantic competence: to know the meaning of a word is to know its intension, “the general conditions which an object must fulfill in order to be denoted by [that] word” (Carnap 1955). However, such general conditions were not spelled out by Carnap (1947). Consequently, his system did not account, any more than Tarski’s, for semantic differences and relations among words belonging to the same semantic category: there were possible worlds in which the same individual a could be both a married man and a bachelor, as no constraints were placed on either word’s intension. One consequence, as Quine (1951) pointed out, was that Carnap’s system, which was supposed to single out analytic truths as true in every possible world, “Bachelors are unmarried”—intuitively, a paradigmatic analytic truth—turned out to be synthetic rather than analytic.

To remedy what he agreed was an unsatisfactory feature of his system, Carnap (1952) introduced meaning postulates , i.e., stipulations on the relations among the extensions of lexical items. For example, the meaning postulate

• (MP) \(\forall x (\mbox{bachelor}(x) \supset \mathord{\sim}\mbox{married} (x))\)

stipulates that any individual that is in the extension of ‘bachelor’ is not in the extension of ‘married’. Meaning postulates can be seen either as restrictions on possible worlds or as relativizing analyticity to possible worlds. On the former option we shall say that “If Paul is a bachelor then Paul is unmarried” holds in every admissible possible world, while on the latter we shall say that it holds in every possible world in which (MP) holds . Carnap regarded the two options as equivalent; nowadays, the former is usually preferred. Carnap (1952) also thought that meaning postulates expressed the semanticist’s “intentions” with respect to the meanings of the descriptive constants, which may or may not reflect linguistic usage; again, today postulates are usually understood as expressing semantic relations (synonymy, analytic entailment, etc.) among lexical items as currently used by competent speakers.

In the late 1960s and early 1970s, Montague (1974) and other philosophers and linguists (Kaplan, Kamp, Partee, and D. Lewis among others) set out to apply to the analysis of natural language the notions and techniques that had been introduced by Tarski and Carnap and further developed in Kripke’s possible worlds semantics (see the entry on Montague semantics ). Montague semantics can be represented as aiming to capture the inferential structure of a natural language: every inference that a competent speaker would regard as valid should be derivable in the theory. Some such inferences depend for their validity on syntactic structure and on the logical properties of logical words, like the inference from “Every man is mortal and Socrates is a man” to “Socrates is mortal”. Other inferences depend on properties of non-logical words that are usually regarded as semantic, like the inference from “Kim is pregnant” to “Kim is not a man”. In Montague semantics, such inferences are taken care of by supplementing the theory with suitable Carnapian meaning postulates. Yet, some followers of Montague regarded such additions as spurious: the aims of semantics, they said, should be distinguished from those of lexicography. The description of the meaning of non-logical words requires considerable world knowledge: for example, the inference from “Kim is pregnant” to “Kim is not a man” is based on a “biological” rather than on a “logical” generalization. Hence, we should not expect a semantic theory to furnish an account of how any two expressions belonging to the same syntactic category differ in meaning (Thomason 1974). From such a viewpoint, Montague semantics would not differ significantly from Tarskian semantics in its account of lexical meaning. But not all later work within Montague’s program shared such a skepticism about representing aspects of lexical meaning within a semantic theory, using either componential analysis (Dowty 1979) or meaning postulates (Chierchia & McConnell-Ginet 2000).

For those who believe that meaning postulates can exhaust lexical meaning, the issue arises of how to choose them, i.e., of how—and whether—to delimit the set of meaning-relevant truths with respect to the set of all true statements in which a given word occurs. As we just saw, Carnap himself thought that the choice could only be the expression of the semanticist’s intentions. However, we seem to share intuitions of analyticity , i.e., we seem to regard some, but not all sentences of a natural language as true by virtue of the meaning of the occurring words. Such intuitions are taken to reflect objective semantic properties of the language, that the semanticist should describe rather than impose at will. Quine (1951) did not challenge the existence of such intuitions, but he argued that they could not be cashed out in the form of a scientifically respectable criterion separating analytic truths (“Bachelors are unmarried”) from synthetic truths (“Aldo’s uncle is a bachelor”), whose truth does not depend on meaning alone. Though Quine’s arguments were often criticized (for recent criticisms, see Williamson 2007), and in spite of Chomsky’s constant endorsement of analyticity (see e.g. 2000: 47, 61–2), within philosophy the analytic/synthetic distinction was never fully vindicated (for an exception, see Russell 2008). Hence, it was widely believed that lexical meaning could not be adequately described by meaning postulates. Fodor and Lepore (1992) argued that this left semantics with two options: lexical meanings were either atomic (i.e., they could not be specified by descriptions involving other meanings) or they were holistic , i.e., only the set of all true sentences of the language could count as fixing them.

Neither alternative looked promising. Holism incurred in objections connected with the acquisition and the understanding of language: how could individual words be acquired by children, if grasping their meaning involved, somehow, semantic competence on the whole language? And how could individual sentences be understood if the information required to understand them exceeded the capacity of human working memory? (For an influential criticism of several varieties of holism, see Dummett 1991; for a review, Pagin 2006). Atomism, in turn, ran against strong intuitions of (at least some) relations among words being part of a language’s semantics: it is because of what ‘bachelor’ means that it doesn’t make sense to suppose we could discover that some bachelors are married. Fodor (1998) countered this objection by reinterpreting allegedly semantic relations as metaphysically necessary connections among extensions of words. However, sentences that are usually regarded as analytic, such as “Bachelors are unmarried”, are not easily seen as just metaphysically necessary truths like “Water is H 2 O”. If water is H 2 O, then its metaphysical essence consists in being H 2 O (whether we know it or not); but there is no such thing as a metaphysical essence that all bachelors share—an essence that could be hidden to us, even though we use the word ‘bachelor’ competently. On the contrary, on acquiring the word ‘bachelor’ we acquire the belief that bachelors are unmarried (Quine 1986); by contrast, many speakers that have ‘water’ in their lexical repertoire do not know that water is H 2 O. The difficulties of atomism and holism opened the way to vindications of molecularism (e.g., Perry 1994; Marconi 1997), the view on which only some relations among words matter for acquisition and understanding (see the entry on meaning holism ).

While mainstream formal semantics went with Carnap and Montague, supplementing the Tarskian apparatus with the possible worlds machinery and defining meanings as intensions, Davidson (1967, 1984) put forth an alternative suggestion. Tarski had shown how to provide a definition of the truth predicate for a (formal) language L : such a definition is materially adequate (i.e., it is a definition of truth , rather than of some other property of sentences of L ) if and only if it entails every biconditional of the form

• (T) S is true in L iff p ,

where S is a sentence of L and p is its translation into the metalanguage of L in which the definition is formulated. Thus, Tarski’s account of truth presupposes that the semantics of both L and its metalanguage is fixed (otherwise it would be undetermined whether S translates into p ). On Tarski’s view, each biconditional of form (T) counts as a “partial definition” of the truth predicate for sentences of L (see the entry on Tarski’s truth definitions ). By contrast, Davidson suggested that if one took the notion of truth for granted, then T-biconditionals could be read as collectively constituting a theory of meaning for L , i.e., as stating truth conditions for the sentences of L . For example,

• (W) “If the weather is bad then Sharon is sad” is true in English iff either the weather is not bad or Sharon is sad

states the truth conditions of the English sentence “If the weather is bad then Sharon is sad”. Of course, (W) is intelligible only if one understands the language in which it is phrased, including the predicate ‘true in English’. Davidson thought that the recursive machinery of Tarski’s definition of truth could be transferred to the suggested semantic reading, with extensions to take care of the forms of natural language composition that Tarski had neglected because they had no analogue in the formal languages he was dealing with. Unfortunately, few of such extensions were ever spelled out by Davidson or his followers. Moreover, it is difficult to see how, giving up possible worlds and intensions in favor of a purely extensional theory, the Davidsonian program could account for the semantics of propositional attitude ascriptions of the form “A believes (hopes, imagines, etc.) that p ”.

Construed as theorems of a semantic theory, T-biconditionals were often accused of being uninformative (Putnam 1975; Dummett 1976): to understand them, one has to already possess the information they are supposed to provide. This is particularly striking in the case of lexical axioms such as the following:

• (V1) Val( x , ‘man’) iff x is a man;
• (V2) Val(\(\langle x,y\rangle\), ‘knows’) iff x knows y .

(To be read, respectively, as “the predicate ‘man’ applies to x if and only if x is a man” and “the predicate ‘know’ applies to the pair \(\langle x, y\rangle\) if and only if x knows y ”). Here it is apparent that in order to understand (V1) one must know what ‘man’ means, which is just the information that (V1) is supposed to convey (as the theory, being purely extensional, identifies meaning with reference). Some Davidsonians, though admitting that statements such as (V1) and (V2) are in a sense “uninformative”, insist that what (V1) and (V2) state is no less “substantive” (Larson & Segal 1995). To prove their point, they appeal to non-homophonic versions of lexical axioms, i.e., to the axioms of a semantic theory for a language that does not coincide with the (meta)language in which the theory itself is phrased. Such would be, e.g.,

• (V3) Val ( x , ‘man’) si et seulement si x est un homme.

(V3), they argue, is clearly substantive, yet what it says is exactly what (V1) says, namely, that the word ‘man’ applies to a certain category of objects. Therefore, if (V3) is substantive, so is (V1). But this is beside the point. The issue is not whether (V1) expresses a proposition; it clearly does, and it is, in this sense, “substantive”. But what is relevant here is informative power: to one who understands the metalanguage of (V3), i.e., French, (V3) may communicate new information, whereas there is no circumstance in which (V1) would communicate new information to one who understands English.

In the mid-1970s, Dummett raised the issue of the proper place of lexical meaning in a semantic theory. If the job of a theory of meaning is to make the content of semantic competence explicit—so that one could acquire semantic competence in a language L by learning an adequate theory of meaning for L —then the theory ought to reflect a competent speaker’s knowledge of circumstances in which she would assert a sentence of L , such as “The horse is in the barn”, as distinct from circumstances in which she would assert “The cat is on the mat”. This, in turn, appears to require that the theory yields explicit information about the use of ‘horse’, ‘barn’, etc., or, in other words, that it includes information which goes beyond the logical type of lexical units. Dummett identified such information with a word’s Fregean sense. However, he did not specify the format in which word senses should be expressed in a semantic theory, except for words that could be defined (e.g., ‘aunt’ = “sister of a parent”): in such cases, the definiens specifies what a speaker must understand in order to understand the word (Dummett 1991). But of course, not all words are of this kind. For other words, the theory should specify what it is for a speaker to know them, though we are not told how exactly this should be done. Similarly, Grandy (1974) pointed out that by identifying the meaning of a word such as ‘wise’ as a function from possible worlds to the sets of wise people in those worlds, Montague semantics only specifies a formal structure and eludes the question of whether there is some possible description for the functions which are claimed to be the meanings of words. Lacking such descriptions, possible worlds semantics is not really a theory of meaning but a theory of logical form or logical validity. Again, aside from suggesting that “one would like the functions to be given in terms of computation procedures, in some sense”, Grandy had little to say about the form of lexical descriptions.

In a similar vein, Partee (1981) argued that Montague semantics, like every compositional or structural semantics, does not uniquely fix the intensional interpretation of words. The addition of meaning postulates does rule out some interpretations (e.g., interpretations on which the extension of ‘bachelor’ and the extension of ‘married’ may intersect in some possible world). However, it does not reduce them to the unique, “intended” or, in Montague’s words, “actual” interpretation (Montague 1974). Hence, standard model-theoretic semantics does not capture the whole content of a speaker’s semantic competence, but only its structural aspects. Fixing “the actual interpretation function” requires more than language-to-language connections as encoded by, e.g., meaning postulates: it requires some “language-to-world grounding ”. Arguments to the same effect were developed by Bonomi (1983) and Harnad (1990). In particular, Harnad had in mind the simulation of human semantic competence in artificial systems: he suggested that symbol grounding could be implemented, in part, by “feature detectors” picking out “invariant features of objects and event categories from their sensory projections” (for recent developments see, e.g., Steels & Hild 2012). Such a cognitively oriented conception of grounding differs from Partee’s Putnam-inspired view, on which the semantic grounding of lexical items depends on the speakers’ objective interactions with the external world in addition to their narrow psychological properties.

A resolutely cognitive approach characterizes Marconi’s (1997) account of lexical semantic competence. In his view, lexical competence has two aspects: an inferential aspect, underlying performances such as semantically based inference and the command of synonymy, hyponymy and other semantic relations; and a referential aspect, which is in charge of performances such as naming (e.g., calling a horse ‘horse’) and application (e.g., answering the question “Are there any spoons in the drawer?”). Language users typically possess both aspects of lexical competence, though in different degrees for different words: a zoologist’s inferential competence on ‘manatee’ is usually richer than a layman’s, though a layman who spent her life among manatees may be more competent, referentially, than a “bookish” scientist. However, the two aspects are independent of each another, and neuropsychological evidence appears to show that they can be dissociated: there are patients whose referential competence is impaired or lost while their inferential competence is intact, and vice versa (see Section 5.3 ). Being a theory of individual competence, Marconi’s account does not deal directly with lexical meanings in a public language: communication depends both on the uniformity of cognitive interactions with the external world and on communal norms concerning the use of language, together with speakers’ deferential attitude toward semantic authorities.

Since the early 1970s, views on lexical meaning were revolutionized by semantic externalism. Initially, externalism was limited to proper names and natural kind words such as ‘gold’ or ‘lemon’. In slightly different ways, both Kripke (1972) and Putnam (1970, 1975) argued that the reference of such words was not determined by any description that a competent speaker associated with the word; more generally, and contrary to what Frege may have thought, it was not determined by any cognitive content associated with it in a speaker’s mind (for arguments to that effect, see the entry on names ). Instead, reference is determined, at least in part, by objective (“causal”) relations between a speaker and the external world. For example, a speaker refers to Aristotle when she utters the sentence “Aristotle was a great warrior”—so that her assertion expresses a false proposition about Aristotle, not a true proposition about some great warrior she may “have in mind”—thanks to her connection with Aristotle himself. In this case, the connection is constituted by a historical chain of speakers going back to the initial users of the name ‘Aristotle’, or its Greek equivalent, in baptism-like circumstances. To belong to the chain, speakers (including present-day speakers) are not required to possess any precise knowledge of Aristotle’s life and deeds; they are, however, required to intend to use the name as it is used by the speakers they are picking up the name from, i.e., to refer to the individual those speakers intend to refer to.

In the case of most natural kind names, it may be argued, baptisms are hard to identify or even conjecture. In Putnam’s view, for such words reference is determined by speakers’ causal interaction with portions of matter or biological individuals in their environment: ‘water’, for example, refers to this liquid stuff, stuff that is normally found in our rivers, lakes, etc. The indexical component ( this liquid, our rivers) is crucial to reference determination: it wouldn’t do to identify the referent of ‘water’ by way of some description (“liquid, transparent, quenches thirst, boils at 100°C, etc.”), for something might fit the description yet fail to be water, as in Putnam’s (1973, 1975) famous Twin Earth thought experiment (see the entry on reference ). It might be remarked that, thanks to modern chemistry, we now possess a description that is sure to apply to water and only to water: “being H 2 O” (Millikan 2005). However, even if our chemistry were badly mistaken (as in principle it could turn out to be) and water were not, in fact, H 2 O, ‘water’ would still refer to whatever has the same nature as this liquid. Something belongs to the extension of ‘water’ if and only if it is the same substance as this liquid, which we identify—correctly, as we believe—as being H 2 O.

Let it be noted that in Putnam’s original proposal, reference determination is utterly independent of speakers’ cognition: ‘water’ on Twin Earth refers to XYZ (not to H 2 O) even though the difference between the two substances is cognitively inert, so that before chemistry was created nobody on either Earth or Twin Earth could have told them apart. However, the label ‘externalism’ has been occasionally used for weaker views: a semantic account may be regarded as externalist if it takes semantic content to depend in one way or another on relations a computational system bears to things outside itself (Rey 2005; Borg 2012), irrespective of whether such relations affect the system’s cognitive state. Weak externalism is hard to distinguish from forms of internalism on which a word’s reference is determined by information stored in a speaker’s cognitive system—information of which the speaker may or may not be aware (Evans 1982). Be that as it may, in what follows ‘externalism’ will be used to mean strong, or Putnamian, externalism.

Does externalism apply to other lexical categories besides proper names and natural kind words? Putnam (1975) extended it to artifactual words, claiming that ‘pencil’ would refer to pencils— those objects—even if they turned out not to fit the description by which we normally identify them (e.g., if they were discovered to be organisms, not artifacts). Schwartz (1978, 1980) pointed out, among many objections, that even in such a case we could make objects fitting the original description; we would then regard the pencil-like organisms as impostors, not as “genuine” pencils. Others sided with Putnam and the externalist account: for example, Kornblith (1980) pointed out that artifactual kinds from an ancient civilization could be re-baptized in total ignorance of their function. The new artifactual word would then refer to the kind those objects belong to independently of any beliefs about them, true or false. Against such externalist accounts, Thomasson (2007) argued that artifactual terms cannot refer to artifactual kinds independently of all beliefs and concepts about the nature of the kind, for the concept of the kind’s creator(s) is constitutive of the nature of the kind. Whether artifactual words are liable to an externalist account is still an open issue (for recent discussions see Marconi 2013; Bahr, Carrara & Jansen 2019; see also the entry on artifacts ), as is, more generally, the scope of application of externalist semantics.

There is another form of externalism that does apply to all or most words of a language: social externalism (Burge 1979), the view on which the meaning of a word as used by an individual speaker depends on the semantic standards of the linguistic community the speaker belongs to. In our community the word ‘arthritis’ refers to arthritis—an affliction of the joints—even when used by a speaker who believes that it can afflict the muscles as well and uses the word accordingly. If the community the speaker belongs to applied ‘arthritis’ to rheumatoids ailments in general, whether or not they afflict the joints, the same word form would not mean arthritis and would not refer to arthritis. Hence, a speaker’s mental contents, such as the meanings associated with the words she uses, depend on something external to her, namely the uses and the standards of use of the linguistic community she belongs to. Thus, social externalism eliminates the notion of idiolect: words only have the meanings conferred upon them by the linguistic community (“public” meanings); discounting radical incompetence, there is no such thing as individual semantic deviance, there are only false beliefs (for criticisms, see Bilgrami 1992, Marconi 1997; see also the entry on idiolects ).

Though both forms of externalism focus on reference, neither is a complete reduction of lexical meaning to reference. Both Putnam and Burge make it a necessary condition of semantic competence on a word that a speaker commands information that other semantic views would regard as part of the word’s sense. For example, if a speaker believes that manatees are a kind of household appliance, she would not count as competent on the word ‘manatee’, nor would she refer to manatees by using it (Putnam 1975; Burge 1993). Beyond that, it is not easy for externalists to provide a satisfactory account of lexical semantic competence, as they are committed to regarding speakers’ beliefs and abilities (e.g., recognitional abilities) as essentially irrelevant to reference determination, hence to meaning. Two main solutions have been proposed. Putnam (1970, 1975) suggested that a speaker’s semantic competence consists in her knowledge of stereotypes associated with words. A stereotype is an oversimplified theory of a word’s extension: the stereotype associated with ‘tiger’ describes tigers as cat-like, striped, carnivorous, fierce, living in the jungle, etc. Stereotypes are not meanings, as they do not determine reference in the right way: there are albino tigers and tigers that live in zoos. What the ‘tiger’-stereotype describes is (what the community takes to be) the typical tiger. Knowledge of stereotypes is necessary to be regarded as a competent speaker, and—one surmises—it can also be considered sufficient for the purposes of ordinary communication. Thus, Putnam’s account does provide some content for semantic competence, though it dissociates it from knowledge of meaning.

On an alternative view (Devitt 1983), competence on ‘tiger’ does not consist in entertaining propositional beliefs such as “tigers are striped”, but rather in being appropriately linked to a network of causal chains for ‘tiger’ involving other people’s abilities, groundings, and reference borrowings. In order to understand the English word ‘tiger’ and use it in a competent fashion, a subject must be able to combine ‘tiger’ appropriately with other words to form sentences, to have thoughts which those sentences express, and to ground these thoughts in tigers. Devitt’s account appears to make some room for a speaker’s ability to, e.g., recognize a tiger when she sees one; however, the respective weights of individual abilities (and beliefs) and objective grounding are not clearly specified. Suppose a speaker A belongs to a community C that is familiar with tigers; unfortunately, A has no knowledge of the typical appearance of a tiger and is unable to tell a tiger from a leopard. Should A be regarded as a competent user ‘tiger’ on account of her being “part of C ” and therefore linked to a network of causal chains for ‘tiger’?

Some philosophers (e.g., Loar 1981; McGinn 1982; Block 1986) objected to the reduction of lexical meaning to reference, or to non-psychological factors that are alleged to determine reference. In their view, there are two aspects of meaning (more generally, of content): the narrow aspect, that captures the intuition that ‘water’ has the same meaning in both Earthian and Twin-Earthian English, and the wide aspect, that captures the externalist intuition that ‘water’ picks out different substances in the two worlds. The wide notion is required to account for the difference in reference between English and Twin-English ‘water’; the narrow notion is needed, first and foremost, to account for the relation between a subject’s beliefs and her behavior. The idea is that how an object of reference is described (not just which object one refers to) can make a difference in determining behavior. Oedipus married Jocasta because he thought he was marrying the queen of Thebes, not his mother, though as a matter of fact Jocasta was his mother. This applies to words of all categories: someone may believe that water quenches thirst without believing that H 2 O does; Lois Lane believed that Superman was a superhero but she definitely did not believe the same of her colleague Clark Kent, so she behaved one way to the man she identified as Superman and another way to the man she identified as Clark Kent (though they were the same man). Theorists that countenance these two components of meaning and content usually identify the narrow aspect with the inferential or conceptual role of an expression e , i.e., with the aspect of e that contributes to determine the inferential relations between sentences containing an occurrence of e and other sentences. Crucially, the two aspects are independent: neither determines the other. The stress on the independence of the two factors also characterizes more recent versions of so-called “dual aspect” theories, such as Chalmers (1996, 2002).

While dual theorists agree with Putnam’s claim that some aspects of meaning are not “in the head”, others have opted for plain internalism. For example, Segal (2000) rejected the intuitions that are usually associated with the Twin-Earth cases by arguing that meaning (and content in general) “locally supervenes” on a subject’s intrinsic physical properties. But the most influential critic of externalism has undoubtedly been Chomsky (2000). First, he argued that much of the alleged support for externalism comes in fact from “intuitions” about words’ reference in this or that circumstance. But ‘reference’ (and the verb ‘refer’ as used by philosophers) is a technical term, not an ordinary word, hence we have no more intuitions about reference than we have about tensors or c-command. Second, if we look at how words such as ‘water’ are applied in ordinary circumstances, we find that speakers may call ‘water’ liquids that contain a smaller proportion of H 2 O than other liquids they do not call ‘water’ (e.g., tea): our use of ‘water’ does not appear to be governed by hypotheses about microstructure. According to Chomsky, it may well be that progress in the scientific study of the language faculty will allow us to understand in what respects one’s picture of the world is framed in terms of things selected and individuated by properties of the lexicon, or involves entities and relationships describable by the resources of the language faculty. Some semantic properties do appear to be integrated with other aspects of language. However, so-called “natural kind words” (which in fact have little to do with kinds in nature, Chomsky claims) may do little more than indicating “positions in belief systems”: studying them may be of some interest for “ethnoscience”, surely not for a science of language. Along similar lines, others have maintained that the genuine semantic properties of linguistic expressions should be regarded as part of syntax, and that they constrain but do not determine truth conditions (e.g., Pietroski 2005, 2010). Hence, the connection between meaning and truth conditions (and reference) may be significantly looser than assumed by many philosophers.

“Ordinary language” philosophers of the 1950s and 1960s regarded work in formal semantics as essentially irrelevant to issues of meaning in natural language. Following Austin and the later Wittgenstein, they identified meaning with use and were prone to consider the different patterns of use of individual expressions as originating different meanings of the word. Grice (1975) argued that such a proliferation of meanings could be avoided by distinguishing between what is asserted by a sentence (to be identified with its truth conditions) and what is communicated by it in a given context (or in every “normal” context). For example, consider the following exchange:

• A: Will Kim be hungry at 11am?
• B: Kim had breakfast.

Although B does not literally assert that Kim had breakfast on that particular day (see, however, Partee 1973), she does communicate as much. More precisely, A could infer the communicated content by noticing that the asserted sentence, taken literally (“Kim had breakfast at least once in her life”), would be less informative than required in the context: thus, it would violate one or more principles of conversation (“maxims”) whereas there is no reason to suppose that the speaker intended to opt out of conversational cooperation (see the entries on Paul Grice and pragmatics ). If the interlocutor assumes that the speaker intended him to infer the communicated content—i.e., that Kim had breakfast that morning , so presumably she would not be hungry at 11—cooperation is preserved. Such non-asserted content, called ‘implicature’, need not be an addition to the overtly asserted content: e.g., in irony asserted content is negated rather than expanded by the implicature (think of a speaker uttering “Paul is a fine friend” to implicate that Paul has wickedly betrayed her).

Grice’s theory of conversation and implicatures was interpreted by many (including Grice himself) as a convincing way of accounting for the variety of contextually specific communicative contents while preserving the uniqueness of a sentence’s “literal” meaning, which was identified with truth conditions and regarded as determined by syntax and the conventional meanings of the occurring words, as in formal semantics. The only semantic role context was allowed to play was in determining the content of indexical words (such as ‘I’, ‘now’, ‘here’, etc.) and the effect of context-sensitive structures (such as tense) on a sentence’s truth conditions. However, in about the same years Travis (1975) and Searle (1979, 1980) pointed out that the semantic relevance of context might be much more pervasive, if not universal: intuitively, the same sentence type could have very different truth conditions in different contexts, though no indexical expression or structure appeared to be involved. Take the sentence “There is milk in the fridge”: in the context of morning breakfast it will be considered true if there is a carton of milk in the fridge and false if there is a patch of milk on a tray in the fridge, whereas in the context of cleaning up the kitchen truth conditions are reversed. Examples can be multiplied indefinitely, as indefinitely many factors can turn out to be relevant to the truth or falsity of a sentence as uttered in a particular context. Such variety cannot be plausibly reduced to traditional polysemy such as the polysemy of ‘property’ (meaning quality or real estate), nor can it be described in terms of Gricean implicatures: implicatures are supposed not to affect a sentence’s truth conditions, whereas here it is precisely the sentence’s truth conditions that are seen as varying with context.

The traditionalist could object by challenging the contextualist’s intuitions about truth conditions. “There is milk in the fridge”, she could argue, is true if and only if there is a certain amount (a few molecules will do) of a certain organic substance in the relevant fridge (for versions of this objection, Cappelen & Lepore 2005). So the sentence is true both in the carton case and in the patch case; it would be false only if the fridge did not contain any amount of any kind of milk (whether cow milk or goat milk or elephant milk). The contextualist’s reply is that, in fact, neither the speaker nor the interpreter is aware of such alleged literal content (the point is challenged by Fodor 1983, Carston 2002); but “what is said” must be intuitively accessible to the conversational participants ( Availability Principle , Recanati 1989). If truth conditions are associated with what is said—as the traditionalist would agree they are—then in many cases a sentence’s literal content, if there is such a thing, does not determine a complete, evaluable proposition. For a genuine proposition to arise, a sentence type’s literal content (as determined by syntax and conventional word meaning) must be enriched or otherwise modified by primary pragmatic processes based on the speakers’ background knowledge relative to each particular context of use of the sentence. Such processes differ from Gricean implicature-generating processes in that they come into play at the sub-propositional level; moreover, they are not limited to saturation of indexicals but may include the replacement of a constituent with another. These tenets define contextualism (Recanati 1993; Bezuidenhout 2002; Carston 2002; relevance theory (Sperber & Wilson 1986) is in some respects a precursor of such views). Contextualists take different stands on nature of the semantic contribution made by words to sentences, though they typically agree that it is insufficient to fix truth conditions (Stojanovic 2008). See Del Pinal (2018) for an argument that radical contextualism (in particular, truth-conditional pragmatics) should instead commit to rich lexical items which, in certain conditions, do suffice to fix truth conditions.

Even if sentence types have no definite truth conditions, it does not follow that lexical types do not make definite or predictable contributions to the truth conditions of sentences (think of indexical words). It does follow, however, that conventional word meanings are not the final constituents of complete propositions (see Allot & Textor 2012). Does this imply that there are no such things as lexical meanings understood as features of a language? If so, how should we account for word acquisition and lexical competence in general? Recanati (2004) does not think that contextualism as such is committed to meaning eliminativism, the view on which words as types have no meaning; nevertheless, he regards it as defensible. Words could be said to have, rather than “meaning”, a semantic potential , defined as the collection of past uses of a word w on the basis of which similarities can be established between source situations (i.e., the circumstances in which a speaker has used w ) and target situations (i.e., candidate occasions of application of w ). It is natural to object that even admitting that long-term memory could encompass such an immense amount of information (think of the number of times ‘table’ or ‘woman’ are used by an average speaker in the course of her life), surely working memory could not review such information to make sense of new uses. On the other hand, if words were associated with “more abstract schemata corresponding to types of situations”, as Recanati suggests as a less radical alternative to meaning eliminativism, one wonders what the difference would be with respect to traditional accounts in terms of polysemy.

Other conceptions of “what is said” make more room for the semantic contribution of conventional word meanings. Bach (1994) agrees with contextualists that the linguistic meaning of words (plus syntax and after saturation) does not always determine complete, truth-evaluable propositions; however, he maintains that they do provide some minimal semantic information, a so-called ‘propositional radical’, that allows pragmatic processes to issue in one or more propositions. Bach identifies “what is said” with this minimal information. However, many have objected that minimal content is extremely hard to isolate (Recanati 2004; Stanley 2007). Suppose it is identified with the content that all the utterances of a sentence type share; unfortunately, no such content can be attributed to a sentence such as “Every bottle is in the fridge”, for there is no proposition that is stably asserted by every utterance of it (surely not the proposition that every bottle in the universe is in the fridge, which is never asserted). Stanley’s (2007) indexicalism rejects the notion of minimal proposition and any distinction between semantic content and communicated content: communicated content can be entirely captured by means of consciously accessible, linguistically controlled content (content that results from semantic value together with the provision of values to free variables in syntax, or semantic value together with the provision of arguments to functions from semantic types to propositions) together with general conversational norms. Accordingly, Stanley generalizes contextual saturation processes that are usually regarded as characteristic of indexicals, tense, and a few other structures; moreover, he requires that the relevant variables be linguistically encoded, either syntactically or lexically. It remains to be seen whether such solutions apply (in a non- ad hoc way) to all the examples of content modulation that have been presented in the literature.

Finally, minimalism (Borg 2004, 2012; Cappelen & Lepore 2005) is the view that appears (and intends) to be closest to the Frege-Montague tradition. The task of a semantic theory is said to be minimal in that it is supposed to account only for the literal meaning of sentences: context does not affect literal semantic content but “what the speaker says” as opposed to “what the sentence means” (Borg 2012). In this sense, semantics is not another name for the theory of meaning, because not all meaning-related properties are semantic properties (Borg 2004). Contrary to contextualism and Bach’s theory, minimalism holds that lexicon and syntax together determine complete truth-evaluable propositions. Indeed, this is definitional for lexical meaning: word meanings are the kind of things which, if one puts enough of them together in the right sort of way, then what one gets is propositional content (Borg 2012). Borg believes that, in order to be truth-evaluable, propositional contents must be “about the world”, and that this entails some form of semantic externalism. However, the identification of lexical meaning with reference makes it hard to account for semantic relations such as synonymy, analytic entailment or the difference between ambiguity and polysemy, and syntactically relevant properties: the difference between “John is easy to please” and “John is eager to please” cannot be explained by the fact that ‘easy’ means the property easy (see the entry on ambiguity ). To account for semantically based syntactic properties, words may come with “instructions” that are not, however, constitutive of a word’s meaning like meaning postulates (which Borg rejects), though awareness of them is part of a speaker’s competence. Once more, lexical semantic competence is divorced from grasp of word meaning. In conclusion, some information counts as lexical if it is either perceived as such in “firm, type-level lexical intuitions” or capable of affecting the word’s syntactic behavior. Borg concedes that even such an extended conception of lexical content will not capture, e.g., analytic entailments such as the relation between ‘bachelor’ and ‘unmarried’.

4. Linguistics

The emergence of modern linguistic theories of word meaning is usually placed at the transition from historical-philological semantics ( Section 2.2 ) to structuralist semantics, the linguistics movement started at the break of the 20 th century by Ferdinand de Saussure with his Cours de Linguistique Générale (1995 [1916]).

The advances introduced by the structuralist conception of word meaning are best appreciated by contrasting its basic assumptions with those of historical-philological semantics. Let us recall the three most important differences (Lepschy 1970; Matthews 2001).

• Anti-psychologism . Structuralist semantics views language as a symbolic system whose properties and internal dynamics can be analyzed without taking into account their implementation in the mind/brain of language users. Just as the rules of chess can be stated and analyzed without making reference to the mental properties of chess players, so a theory of word meaning can, and should, proceed simply by examining the formal role played by words within the system of the language.
• Anti-historicism . Since the primary explanandum of structuralist semantics is the role played by lexical expressions within structured linguistic systems, structuralist semantics privileges the synchronic description of word meaning. Diachronic accounts of word meaning are logically posterior to the analysis of the relational properties statically exemplified by words at different stages of the evolution of the language.
• Anti-localism . Because the semantic properties of words depend on the relations they entertain with other expressions in the same lexical system, word meanings cannot be studied in isolation. This is both an epistemological and a foundational claim, i.e., a claim about how matters related to word meaning should be addressed in the context of a semantic theory of word meaning, and a claim about the dynamics whereby the elements of a system of signs acquire the meaning they have for their users.

The account of lexical phenomena popularized by structuralism gave rise to a variety of descriptive approaches to word meaning. We can group them in three categories (Lipka 1992; Murphy 2003; Geeraerts 2006).

• Lexical Field Theory . Introduced by Trier (1931), it argues that word meaning should be studied by looking at the relations holding between words in the same lexical field. A lexical field is a set of semantically related words whose meanings are mutually interdependent and which together spell out the conceptual structure of a given domain of reality. Lexical Field Theory assumes that lexical fields are closed sets with no overlapping meanings or semantic gaps. Whenever a word undergoes a change in meaning (e.g., its range of application is extended or contracted), the whole arrangement of its lexical field is affected (Lehrer 1974).
• Componential Analysis . Developed in the second half of the 1950s by European and American linguists (e.g., Pattier, Coseriu, Bloomfield, Nida), this framework argues that word meaning can be described on the basis of a finite set of conceptual building blocks called semantic components or features . For example, ‘man’ can be analyzed as [+ male ], [+ mature ], ‘woman’ as [− male ], [+ mature ], ‘child’ as [+/− male ] [− mature ] (Leech 1974).
• Relational Semantics . Prominent in the work of linguists such as Lyons (1963), this approach shares with Lexical Field Theory the commitment to a style of analysis that privileges the description of lexical relations, but departs from it in two important respects. First, it postulates no direct correspondence between sets of related words and domains of reality, thereby dropping the assumption that the organization of lexical fields should be understood to reflect the organization of the non-linguistic world. Second, instead of deriving statements about the meaning relations entertained by a lexical item (e.g., synonymy, hyponymy) from an independent account of its meaning, for relational semantics word meanings are constituted by the set of semantic relations words participate in (Evens et al. 1980; Cruse 1986).

The componential current of structuralism was the first to produce an important innovation in theories of word meaning: Katzian semantics (Katz & Fodor 1963; Katz 1972, 1987). Katzian semantics combined componential analysis with a mentalistic conception of word meaning and developed a method for the description of lexical phenomena in the context of a formal grammar. The mentalistic component of Katzian semantics is twofold. First, word meanings are defined as aggregates of simpler conceptual features inherited from our general categorization abilities. Second, the proper subject matter of the theory is no longer identified with the “structure of the language” but, following Chomsky (1957, 1965), with speakers’ ability to competently interpret the words and sentences of their language. In Katzian semantics, word meanings are structured entities whose representations are called semantic markers . A semantic marker is a hierarchical tree with labeled nodes whose structure reproduces the structure of the represented meaning, and whose labels identify the word’s conceptual components. For example, the figure below illustrates the sense of ‘chase’ (simplified from Katz 1987).

Katz (1987) claimed that this approach was superior in both transparency and richness to the analysis of word meaning that could be provided via meaning postulates. For example, in Katzian semantics the validation of conditionals such as \(\forall x\forall y (\textrm{chase}(x, y) \to \textrm{follow}(x,y))\) could be reduced to a matter of inspection: one had simply to check whether the semantic marker of ‘follow’ was a subtree of the semantic marker of ‘chase’. Furthermore, the method incorporated syntagmatic relations in the representation of word meanings (witness the grammatical tags ‘NP’, ‘VP’ and ‘S’ attached to the conceptual components above). Katzian semantics was favorably received by the Generative Semantics movement (Fodor 1977; Newmeyer 1980) and boosted an interest in the formal representation of word meaning that would dominate the linguistic scene for decades to come (Harris 1993). Nonetheless, it was eventually abandoned. As subsequent commentators noted, Katzian semantics suffered from three important drawbacks. First, the theory did not provide any clear model of how the complex conceptual information represented by semantic markers contributed to the truth conditions of sentences (Lewis 1972). Second, some aspects of word meaning that could be easily represented with meaning postulates could not be expressed through semantic markers, such as the symmetry and the transitivity of predicates (e.g., \(\forall x\forall y (\textrm{sibling}(x, y) \to \textrm{sibling}(y, x))\) or \(\forall x\forall y\forall z (\textrm{louder}(x, y) \mathbin{\&} \textrm{louder}(y, z) \to \textrm{louder}(x, z))\); see Dowty 1979). Third, Katz’s arguments for the view that word meanings are intrinsically structured turned out to be vulnerable to objections from proponents of atomistic views of word meaning (see, most notably, Fodor & Lepore 1992).

After Katzian semantics, the landscape of linguistic theories of word meaning bifurcated. On one side, we find a group of theories advancing the decompositional agenda established by Katz. On the other side, we find a group of theories fostering the relational approach originated by Lexical Field Theory and relational semantics. Following Geeraerts (2010), we will briefly characterize the following ones.

The basic idea of the Natural Semantic Metalanguage approach (henceforth, NSM; Wierzbicka 1972, 1996; Goddard & Wierzbicka 2002) is that word meaning is best described through the combination of a small set of elementary conceptual particles, known as semantic primes . Semantic primes are primitive (i.e., not decomposable into further conceptual parts), innate (i.e., not learned), and universal (i.e., explicitly lexicalized in all natural languages, whether in the form of a word, a morpheme, a phraseme, and so forth). According to NSM, the meaning of any word in any natural language can be defined by appropriately combining these fundamental conceptual particles. Wierzbicka (1996) proposed a catalogue of about 60 semantic primes, designed to analyze word meanings within so-called reductive paraphrases. For example, the reductive paraphrase for ‘top’ is a part of something; this part is above all the other parts of this something . NSM has produced interesting applications in comparative linguistics (Peeters 2006), language teaching (Goddard & Wierzbicka 2007), and lexical typology (Goddard 2012). However, the approach has been criticized on various grounds. First, it has been argued that the method followed by NSM in the identification of semantic primes is insufficiently clear (e.g., Matthewson 2003). Second, some have observed that reductive paraphrases are too vague to be considered adequate representations of word meanings, since they fail to account for fine-grained differences between semantically neighboring words. For example, the reductive paraphrase provided by Wierzbicka for ‘sad’ (i.e., x feels something; sometimes a person thinks something like this: something bad happened; if i didn’t know that it happened i would say: i don’t want it to happen; i don’t say this now because i know: i can’t do anything; because of this, this person feels something bad; x feels something like this ) seems to apply equally well to ‘unhappy’, ‘distressed’, ‘frustrated’, ‘upset’, and ‘annoyed’ (e.g., Aitchison 2012). Third, there is no consensus on what items should ultimately feature in the list of semantic primes available to reductive paraphrases: the content of the list is debated and varies considerably between versions of NSM. Fourth, some purported semantic primes appear to fail to comply with the universality requirement and are not explicitly lexicalized in all known languages (Bohnemeyer 2003; Von Fintel & Matthewson 2008). See Goddard (1998) for some replies and Riemer (2006) for further objections.

For NSM, word meanings can be exhaustively represented with a metalanguage appealing exclusively to the combination of primitive linguistic particles. Conceptual Semantics (Jackendoff 1983, 1990, 2002) proposes a more open-ended approach. According to Conceptual Semantics, word meanings are essentially an interface phenomenon between a specialized body of linguistic knowledge (e.g., morphosyntactic knowledge) and core non-linguistic cognition. Word meanings are thus modeled as hybrid semantic representations combining linguistic features (e.g., syntactic tags) and conceptual elements grounded in perceptual knowledge and motor schemas. For example, here is the semantic representation of ‘drink’ according to Jackendoff.

Syntactic tags represent the grammatical properties of the word under analysis, while the items in subscript are picked from a core set of perceptually grounded primitives (e.g., event, state, thing, path, place, property, amount ) which are assumed to be innate, cross-modal and universal categories of the human mind. The decompositional machinery of Conceptual Semantics has a number of attractive features. Most notably, its representations take into account grammatical class and word-level syntax, which are plausibly an integral aspect of our knowledge of the meaning of words. However, some of its claims about the interplay between language and conceptual structure appear more problematic. To begin with, it has been observed that speakers tend to use causative predicates (e.g., ‘drink’) and the paraphrases expressing their decompositional structure (e.g., “cause a liquid to go into someone or something’s mouth”) in different and sometimes non-interchangeable ways (e.g., Wolff 2003), which raises concerns about the hypothesis that decompositional analyses à la Jackendoff may be regarded as faithful representations of word meanings. In addition, Conceptual Semantics is somewhat unclear as to what exact method should be followed in the identification of the motor-perceptual primitives that can feed descriptions of word meanings (Pulman 2005). Finally, the restriction placed by Conceptual Semantics on the type of conceptual material that can inform definitions of word meaning (low-level primitives grounded in perceptual knowledge and motor schemas) appears to affect the explanatory power of the framework. For example, how can one account for the difference in meaning between ‘jog’ and ‘run’ without ut taking into account higher-level, arguably non-perceptual knowledge about the social characteristics of jogging, which typically implies a certain leisure setting, the intention to contribute to physical wellbeing, and so on? See Taylor (1996), Deane (1996).

The neat dividing line drawn between word meanings and general world knowledge by Conceptual Semantics does not tell us much about the dynamic interaction of the two in language use. The Two-Level Semantics of Bierwisch (1983a,b) and Lang (Bierwisch & Lang 1989; Lang 1993) aims to provide such a dynamic account. Two-Level Semantics views word meaning as the result of the interaction between two systems: semantic form (SF) and conceptual structure (CS). SF is a formalized representation of the basic features of a word. It contains grammatical information that specifies, e.g., the admissible syntactic distribution of the word, plus a set of variables and semantic parameters whose value is determined by the interaction with CS. By contrast, CS consists of language-independent systems of knowledge (including general world knowledge) that mediate between language and the world (Lang & Maienborn 2011). According to Two-Level Semantics, for example, polysemous words can express variable meanings by virtue of having a stable underspecified SF which can be flexibly manipulated by CS. By way of example, consider the word ‘university’, which can be read as referring either to an institution (as in “the university selected John’s application”) or to a building (as in “the university is located on the North side of the river”). Simplifying a bit, Two-Level Semantics explains the dynamics governing the selection of these readings as follows.

• Because ‘university’ belongs to the category of words denoting objects primarily characterized by their purpose, the general lexical entry for ‘university’ is \(\lambda x [\textrm{purpose} [x w]]\).
• Based on our knowledge that the primary purpose of universities is to provide advanced education, the SF of ‘university’ is specified as \(\lambda x [\textrm{purpose} [x w] \mathbin{\&} \textit{advanced study and teaching} [w]]\).
• The alternative readings of ‘university’ are a function of the two ways CS can set the value of the variable x in its SF, such ways being \(\lambda x [\textrm{institution} [x] \mathbin{\&} \textrm{purpose} [x w]]\) and \(\lambda x [\textrm{building} [x] \mathbin{\&} \textrm{purpose} [x w]]\).

Two-Level Semantics shares Jackendoff’s and Wierzbicka’s commitment to a descriptive paradigm that anchors word meaning to a stable decompositional template, all the while avoiding the immediate complications arising from a restrictive characterization of the type of conceptual factors that can modulate such stable decompositional templates in contexts. But there are, once again, a few significant issues. A first problem is definitional accuracy: defining the SF of ‘university’ as \(\lambda x [\textrm{purpose} [x w] \mathbin{\&} \textit{advanced study and teaching} [w]]\) seems too loose to reflect the subtle differences in meaning among ‘university’ and related terms designating institutions for higher education, such as ‘college’ or ‘academy’. Furthermore, the apparatus of Two-Level Semantics relies heavily on lambda expressions, which, as some commentators have noted (e.g., Taylor 1994, 1995), appears ill-suited to represent the complex forms of world knowledge we often rely on to fix the meaning of highly polysemous words. See also Wunderlich (1991, 1993).

The Generative Lexicon theory (GL; Pustejovsky 1995) takes a different approach. Instead of explaining the contextual flexibility of word meaning by appealing to rich conceptual operations applied on semantically thin lexical entries, this approach postulates lexical entries rich in conceptual information and knowledge of worldly facts. According to classical GL, the informational resources encoded in the lexical entry for a typical word w consist of the following four levels.

• A lexical typing structure , specifying the semantic type of w within the type system of the language;
• An argument structure , representing the number and nature of the arguments supported by w ;
• An event structure , defining the event type denoted by w (e.g., state, process, transition);
• A qualia structure , specifying the predicative force of w .

In particular, qualia structure specifies the conceptual relations that speakers associate to the real-world referents of a word and impact on the way the word is used in the language (Pustejovsky 1998). For example, our knowledge that bread is something that is brought about through baking is considered a Quale of the word ‘bread’, and this knowledge is responsible for our understanding that, e.g., “fresh bread” means “bread which has been baked recently”. GL distinguishes four types of qualia:

• constitutive : the relation between an object x and its constituent parts;
• formal : the basic ontological category of x ;
• telic : the purpose and the function of x ;
• agentive : the factors involved in the origin of x .

Take together, these qualia form the “qualia structure” of a word. For example, the qualia structure of the noun ‘sandwich’ will feature information about the composition of sandwiches, their nature of physical artifacts, their being intended to be eaten, and our knowledge about the operations typically involved in the preparation of sandwiches. The notation is as follows.

sandwich ( x ) const = {bread, …} form = physobj( x ) tel = eat(P, g , x ) agent = artifact( x )

Qualia structure is the primary explanatory device by which GL accounts for polysemy. The sentence “Mary finished the sandwich” receives the default interpretation “Mary finished eating the sandwich” because the argument structure of ‘finish’ requires an action as direct object, and the qualia structure of ‘sandwich’ allows the generation of the appropriate sense via type coercion (Pustejovsky 2006). GL is an ongoing research program (Pustejovsky et al. 2012) that has led to significant applications in computational linguistics (e.g., Pustejovsky & Jezek 2008; Pustejovsky & Rumshisky 2008). But like the theories mentioned so far, it has been subject to criticisms. A first general criticism is that the decompositional assumptions underlying GL are unwarranted and should be replaced by an atomist view of word meaning (Fodor & Lepore 1998; see Pustejovsky 1998 for a reply). A second criticism is that GL’s focus on variations in word meaning which depend on sentential context and qualia structure is too narrow, since since contextual variations in word meaning often depend on more complex factors, such as the ability to keep track of coherence relations in a discourse (e.g., Asher & Lascarides 1995; Lascarides & Copestake 1998; Kehler 2002; Asher 2011). Finally, the empirical adequacy of the framework has been called into question. It has been argued that the formal apparatus of GL leads to incorrect predictions, that qualia structure sometimes overgenerates or undergenerates interpretations, and that the rich lexical entries postulated by GL are psychologically implausible (e.g., Jayez 2001; Blutner 2002).

To conclude this section, we will briefly mention some contemporary approaches to word meaning that, in different ways, pursue the theoretical agenda of the relational current of the structuralist paradigm. For pedagogical convenience, we can group them into two categories. On the one hand, we have network approaches, which formalize knowledge of word meaning within models where the lexicon is seen as a structured system of entries interconnected by sense relations such as synonymy, antonymy, and meronymy. On the other, we have statistical approaches, whose primary aim is to investigate the patterns of co-occurrence among words in linguistic corpora.

The main example of network approaches is perhaps Collins and Quillian’s (1969) hierarchical network model, in which words are represented as entries in a network of nodes, each comprising a set of conceptual features defining the conventional meaning of the word in question, and connected to other nodes in the network through semantic relations (more in Lehman 1992). Subsequent developments of the hierarchical network model include the Semantic Feature Model (Smith, Shoben & Rips 1974), the Spreading Activation Model (Collins & Loftus 1975; Bock & Levelt 1994), the WordNet database (Fellbaum 1998), as well as the connectionist models of Seidenberg & McClelland (1989), Hinton & Shallice (1991), and Plaut & Shallice (1993). More on this in the entry on connectionism .

Finally, statistical analysis investigates word meaning by examining through computational means the distribution of words in linguistic corpora. The main idea is to use quantitative data about the frequency of co-occurrence of sets of lexical items to identify their semantic properties and differentiate their different senses (for overviews, see Atkins & Zampolli 1994; Manning & Schütze 1999; Stubbs 2002; Sinclair 2004). Notice that while symbolic networks are models of the architecture of the lexicon that seek to be psychologically adequate (i.e., to reveal how knowledge of word meaning is stored and organized in the mind/brain of human speakers), statistical approaches to word meaning are not necessarily interested in psychological adequacy, and may have completely different goals, such as building a machine translation service able to mimic human performance (a goal that can obviously be achieved without reproducing the cognitive mechanisms underlying translation in humans). More on this in the entry on computational linguistics .

5. Cognitive Science

As we have seen, most theories of word meaning in linguistics face, at some point, the difficulties involved in drawing a plausible dividing line between word knowledge and world knowledge, and the various ways they attempt to meet this challenge display some recurrent features. For example, they assume that the lexicon, though richly interfaced with world knowledge and non-linguistic cognition, remains an autonomous representational system encoding a specialized body of linguistic knowledge. In this section, we survey a group of empirical approaches that adopt a different stance on word meaning. The focus is once again psychological, which means that the overall goal of these approaches is to provide a cognitively realistic account of the representational repertoire underlying knowledge of word meaning. Unlike the approaches surveyed in Section 4 , however, these theories tend to encourage a view on which the distinction between the semantic and pragmatic aspects of word meaning is highly unstable (or even impossible to draw), where lexical knowledge and knowledge of worldly facts are aspects of a continuum, and where the lexicon is permeated by our general inferential abilities (Evans 2010). Section 5.1 will briefly illustrate the central assumptions underlying the study of word meaning in cognitive linguistics. Section 5.2 will turn to the study of word meaning in psycholinguistics. Section 5.3 will conclude with some references to neurolinguistics.

At the beginning of the 1970s, Eleanor Rosch put forth a new theory of the mental representation of categories. Concepts such as furniture or bird , she claimed, are not represented just as sets of criterial features with clear-cut boundaries, so that an item can be conceived as falling or not falling under the concept based on whether or not it meets the relevant criteria. Rather, items within categories can be considered more or less representative of the category itself (Rosch 1975; Rosch & Mervis 1975; Mervis & Rosch 1981). Several experiments seemed to show that the application of concepts is no simple yes-or-no business: some items (the “good examples”) are more easily identified as falling under a concept than others (the “poor examples”). An automobile is perceived as a better example of vehicle than a rowboat, and much better than an elevator; a carrot is more readily identified as an example of the concept vegetable than a pumpkin. If the concepts speakers associate to category words (such as ‘vehicle’ and ‘vegetable’) were mere bundles of criterial features, these preferences would be inexplicable, since they rank items that meet the criteria equally well. It is thus plausible to assume that the concepts associated to category words are have a center-periphery architecture centered on the most representative examples of the category: a robin is perceived as a more “birdish” bird than an ostrich or, as people would say, closer to the prototype of a bird or to the prototypical bird (see the entry on concepts ).

Although nothing in Rosch’s experiments licensed the conclusion that prototypical rankings should be reified and treated as the content of concepts (what her experiments did support was merely that a theory of the mental representation of categories should be consistent with the existence of prototype effects ), the study of prototypes revolutionized the existing approaches to category concepts (Murphy 2002) and was a leading force behind the birth of cognitive linguistics. Prototypes were central to the development of the Radial Network Theory of Brugman (1988 [1981]) and Lakoff (Brugman & Lakoff 1988), which proposed to model the sense network of words by introducing in the architecture of word meanings the center-periphery relation at the heart of Rosch’s seminal work. According to Brugman, word meanings can typically be modeled as radial complexes where a dominant sense is related to less typical senses by means of semantic relations such as metaphor and metonymy. For example, the sense network of ‘fruit’ features product of plant growth at its center and a more abstract outcome at its periphery, and the two are connected by a metaphorical relation). On a similar note, the Conceptual Metaphor Theory of Lakoff & Johnson (1980; Lakoff 1987) and the Mental Spaces Approach of Fauconnier (1994; Fauconnier & Turner 1998) combined the assumption that word meanings typically have an internal structure arranging multiple related senses in a radial fashion, with the further claim that our use of words is governed by hard-wired mapping mechanisms that catalyze the integration of word meanings across conceptual domains. For example, it is in virtue of these mechanisms that the expressions “love is war”, “life is a journey”) are so widespread across cultures and sound so natural to our ears. On the proposed view, these associations are creative, perceptually grounded, systematic, cross-culturally uniform, and grounded on pre-linguistic patterns of conceptual activity which correlate with core elements of human embodied experience (see the entries on metaphor and embodied cognition ). More in Kövecses (2002), Gibbs (2008), and Dancygier & Sweetser (2014).

Another major innovation introduced by cognitive linguistics is the development of a resolutely “encyclopedic” approach to word meaning, best exemplified by Frame Semantics (Fillmore 1975, 1982) and by the Theory of Domains (Langacker 1987). Approximating a bit, an approach to word meaning can be defined “encyclopedic” insofar as it characterizes knowledge of worldly facts as the primary constitutive force of word meaning. While the Mental Spaces Approach and Conceptual Metaphor Theory regarded word meaning mainly as the product of associative patterns between concepts, Fillmore and Langacker turned their attention to the relation between word meaning and the body of encyclopedic knowledge possessed by typical speakers. Our ability to use and interpret the verb ‘buy’, for example, is closely intertwined with our background knowledge of the social nature of commercial transfer, which involves a seller, a buyer, goods, money, the relation between the money and the goods, and so forth. However, knowledge structures of this kind cannot be modeled as standard concept-like representations. Here is how Frame Semantics attempts to meet the challenge. First, words are construed as pairs of phonographic forms with highly schematic concepts which are internally organized as radial categories and function as access sites to encyclopedic knowledge. Second, an account of the representational organization of encyclopedic knowledge is provided. According to Fillmore, encyclopedic knowledge is represented in long-term memory in the form of frames , i.e., schematic conceptual scenarios that specify the prototypical features and functions of a denotatum, along with its interactions with the objects and the events typically associated with it. Frames provide thus a schematic representation of the elements and entities associated with a particular domain of experience and convey the information required to use and interpret the words employed to talk about it. For example, according to Fillmore & Atkins (1992) the use of the verb ‘bet’ is governed by the risk frame, which is as follows:

In the same vein as Frame Semantics (more on the parallels in Clausner & Croft 1999), Langacker’s Theory of Domains argues that our understanding of word meaning depends on our access to larger knowledge structures called domains . To illustrate the notion of a domain, consider the word ‘diameter’. The meaning of this word cannot be grasped independently of a prior understanding of the notion of a circle. According to Langacker, word meaning is precisely a matter of “profile-domain” organization: the profile corresponds to a substructural element designated within a relevant macrostructure, whereas the domain corresponds to the macrostructure providing the background information against which the profile can be interpreted (Taylor 2002). In the diameter/circle example, ‘diameter’ designates a profile in the circle domain. Similarly, expressions like ‘hot’, ‘cold’, and ‘warm’ designate properties in the temperature domain. Langacker argues that domains are typically structured into hierarchies that reflect meronymic relations and provide a basic conceptual ontology for language use. For example, the meaning of ‘elbow’ is understood with respect to the arm domain, while the meaning of ‘arm’ is situated within the body domain. Importantly, individual profiles typically inhere to different domains, and this is one of the factors responsible for the ubiquity of polysemy in natural language. For example, the profile associated to the word ‘love’ inheres both to the domains of embodied experience and to the abstract domains of social activities such as marriage ceremonies.

Developments of the approach to word meaning fostered by cognitive linguistics include Construction Grammar (Goldberg 1995), Embodied Construction Grammar (Bergen & Chang 2005), Invited Inferencing Theory (Traugott & Dasher 2001), and LCCM Theory (Evans 2009). The notion of a frame has become popular in cognitive psychology to model the dynamics of ad hoc categorization (e.g., Barsalou 1983, 1992, 1999; more in Section 5.2 ). General information about the study of word meaning in cognitive linguistics can be found in Talmy (2000a,b), Croft & Cruse (2004), and Evans & Green (2006).

In psycholinguistics, the study of word meaning is understood as the investigation of the mental lexicon , the cognitive system that underlies the capacity for conscious and unconscious lexical activity (Jarema & Libben 2007). Simply put, the mental lexicon is the long-term representational inventory storing the body of linguistic knowledge speakers are required to master in order to make competent use of the lexical elements of a language; as such, it can be equated with the lexical component of an individual’s language capacity. Research on the mental lexicon is concerned with a variety of problems (for surveys, see, e.g., Traxler & Gernsbacher 2006, Spivey, McRae & Joanisse 2012, Harley 2014), that center around the following tasks:

• Define the overall organization of the mental lexicon, specify its components and clarify the role played by such components in lexical production and comprehension;
• Determine the internal makeup of single components and the way the information they store is brought to bear on lexical performance;
• Describe the interface mechanisms connecting the mental lexicon to other domains in the human cognitive architecture (e.g., declarative memory);
• Illustrate the learning processes responsible for the acquisition and the development of lexical abilities.

From a functional point of view, the mental lexicon is usually understood as a system of lexical entries , each containing the information related to a word mastered by a speaker (Rapp 2001). A lexical entry for a word w is typically modeled as a complex representation made up of the following components (Levelt 1989, 2001):

• A semantic form , determining the semantic contribution made by w to the meaning of sentences containing w ;
• A grammatical form , assigning w to a grammatical category (noun, verb, adjective) and regulating the behavior of w in syntactic environments;
• A morphological form , representing the morphemic substructure of w and the morphological operations that can be applied on w ;
• A phonological form , specifying the set of phonological properties of w ;
• An orthographic form , specifying the graphic structure of w .

From this standpoint, a theory of word meaning translates into an account of the information stored in the semantic form of lexical entries. A crucial part of the task consists in determining exactly what kind of information is stored in lexical semantic forms as opposed to, e.g., bits of information that fall under the scope of episodic memory or general factual knowledge. Recall the example we made in Section 3.3 : how much of the information that a competent zoologist can associate to tigers is part of her knowledge of the meaning of the word ‘tiger’? Not surprisingly, even in psycholinguistics tracing a neat functional separation between word processing and general-purpose cognition has proven a problematic task. The general consensus among psycholinguists seems to be that lexical representations and conceptual representations are richly interfaced, though functionally distinct (e.g., Gleitman & Papafragou 2013). For example, in clinical research it is standard practice to distinguish between amodal deficits involving an inability to process information at both the conceptual and the lexical level, and modal deficits specifically restricted to one of the two spheres (Saffran & Schwartz 1994; Rapp & Goldrick 2006; Jefferies & Lambon Ralph 2006; more in more in Section 5.3 ). On the resulting view, lexical activity in humans is the output of the interaction between two functionally neighboring systems, one broadly in charge of the storage and processing of conceptual-encyclopedic knowledge, the other coinciding with the mental lexicon. The role of lexical entries is essentially to make these two systems communicate with one another through semantic forms (see Denes 2009). Contrary to the folk notion of a mental lexicon where words are associated to fully specified meanings or senses which are simply retrieved from the lexicon for the purpose of language processing, in these models lexical semantic forms are seen as highly schematic representations whose primary function is to supervise the recruitment of the extra-linguistic information required to interpret word occurrences in language use. In recent years, appeals to “ultra-thin” lexical entries have taken an eliminativist turn. It has been suggested that psycholinguistic accounts of the representational underpinnigs of lexical competence should dispose of the largely metaphorical notion of an “internal word store”, and there is no such thing as a mental lexicon in the human mind (e.g., Elman 2004, 2009; Dilkina, McClelland & Plaut 2010).

In addition to these approaches, in a number of prominent psychological accounts emerged over the last two decades, the study of word meaning is essentially considered a chapter of theories of the mental realization of concepts (see the entry on concepts ). Lexical units are seen either as ingredients of conceptual networks or as (auditory or visual) stimuli providing access to conceptual networks. A flow of neuroscientific results has shown that understanding of (certain categories of) words correlates with neural activations corresponding to the semantic content of the processed words. For example, it has been shown that listening to sentences that describe actions performed with the mouth, hand, or leg activates the visuomotor circuits which subserve execution and observation of such actions (Tettamanti et al. 2005); that reading words denoting specific actions of the tongue (‘lick’), fingers (‘pick’), and leg (‘kick’) differentially activate areas of the premotor cortex that are active when the corresponding movements are actually performed (Hauk et al. 2004); that reading odor-related words (‘jasmine’, ‘garlic’, ‘cinnamon’) differentially activates the primary olfactory cortex (Gonzales et al. 2006); and that color words (such as ‘red’) activate areas in the fusiform gyrus that have been associated with color perception (Chao et al. 1999, Simmons et al. 2007; for a survey of results on visual activations in language processing, see Martin 2007).

This body of research originated so-called simulationist (or enactivist ) accounts of conceptual competence, on which “understanding is imagination” and “imagining is a form of simulation” (Gallese & Lakoff 2005). In these accounts, conceptual (often called “semantic”) competence is seen as the ability to simulate or re-enact perceptual (including proprioceptive and introspective) experiences of the states of affairs that language describes, by manipulating memory traces of such experiences or fragments of them. In Barsalou’s theory of perceptual symbol systems (1999), language understanding (and cognition in general) is based on perceptual experience and memory of it. The central claim is that “sensory-motor systems represent not only perceived entities but also conceptualizations of them in their absence”. Perception generates mostly unconscious “neural representations in sensory-motor areas of the brain”, which represent schematic components of perceptual experience. Such perceptual symbols are not holistic copies of experiences but selections of information isolated by attention. Related perceptual symbols are integrated into a simulator that produces limitless simulations of a perceptual component, such as red or lift . Simulators are located in long-term memory and play the roles traditionally attributed to concepts: they generate inferences and can be combined recursively to implement productivity. A concept is not “a static amodal structure” as in traditional, computationally-oriented cognitive science, but “the ability to simulate a kind of thing perceptually”. Linguistic symbols (i.e., auditory or visual memories of words) get to be associated with simulators; perceptual recognition of a word activates the relevant simulator, which simulates a referent for the word; syntax provides instructions for building integrated perceptual simulations, which “constitute semantic interpretations”.

Though popular among researchers interested in the conceptual underpinnings of semantic competence, the simulationist paradigm faces important challenges. Three are worth mentioning. First, it appears that imulations do not always capture the intuitive truth conditions of sentences: listeners may enact the same simulation upon exposure to sentences that have different truth conditions (e.g., “The man stood on the corner” vs. “The man waited on the corner”; see Weiskopf 2010). Moreover, simulations may overconstrain truth conditions. For example, even though in the simulations listeners typically associate to the sentence “There are three pencils and four pens in Anna’s mug”, the pens and the pencils are in vertical position, the sentence would be true even if they were lying horizontally in the mug. Second, the framework does not sit well with pathological data. For example, no general impairment with auditory-related words is reported in patients with lesions in the auditory association cortex (e.g., auditory agnosia patients); analogously, patients with damage to the motor cortex seem to have no difficulties in linguistic performance, and specifically in inferential processing with motor-related words (for a survey of these results, see Calzavarini, to appear; for a defense of the embodied paradigm, Pulvermüller 2013). Finally, the theory has difficulties accounting for the meaning of abstract words (e.g., ‘beauty’, ‘pride’, ‘kindness’), which does not appear to hinge on sensory-motor simulation (see Dove 2016 for a discussion).

Beginning in the mid-1970s, neuropsychological research on cognitive deficits related to brain lesions has produced a considerable amount of findings related to the neural correlates of lexical semantic information and processing. More recently, the development of neuroimaging techniques such as PET, fMRI and ERP has provided further means to adjudicate hypotheses about lexical semantic processes in the brain (Vigneau et al. 2006). Here we do not intend to provide a complete overview of such results (for a survey, see Faust 2012). We shall just mention three topics of neurolinguistic research that appear to bear on issues in the study of word meaning: the partition of the lexicon into categories, the representation of common nouns vs. proper names, and the distinction between the inferential and the referential aspects of lexical competence.

Two preliminary considerations should be kept in mind. First, a distinction must be drawn between the neural realization of word forms, i.e., traces of acoustic, articulatory, graphic, and motor configurations (‘peripheral lexicons’), and the neural correlates of lexical meanings (‘concepts’). A patient can understand what is the object represented by a picture shown to her (and give evidence of her understanding, e.g., by miming the object’s function) while being unable to retrieve the relevant phonological form from her output lexicon (Warrington 1985; Shallice 1988). Second, there appears to be wide consensus about the irrelevance to brain processing of any distinction between strictly semantic and factual or encyclopedic information (e.g., Tulving 1972; Sartori et al. 1994). Whatever information is relevant to such processes as object recognition or confrontation naming is standardly characterized as ‘semantic’. This may be taken as a stipulation—it is just how neuroscientists use the word ‘semantic’—or as deriving from lack of evidence for any segregation between the domains of semantic and encyclopedic information (see Binder et al. 2009). Be that as it may, in present-day neuroscience there seems to be no room for a correlate of the analytic/synthetic distinction. Moreover, in the literature ‘semantic’ and ‘conceptual’ are often used synonymously; hence, no distinction is drawn between lexical semantic and conceptual knowledge. Finally, the focus of neuroscientific research on “semantics” is on information structures roughly corresponding to word-level meanings, not to sentence-level meanings: hence, so far neuroscientific research has had little to say about the compositional mechanisms that have been the focus (and, often, the entire content) of theories of meaning as pursued within formal semantics and philosophy of language.

Let us start with the partition of the semantic lexicon into categories. Neuropsychological research indicates that the ability to name objects or to answer simple questions involving such nouns can be selectively lost or preserved: subjects can perform much better in naming living entities than in naming artifacts, or in naming animate living entities than in naming fruits and vegetables (Shallice 1988). Different patterns of brain activation may correspond to such dissociations between performances: e.g., Damasio et al. (1996) found that retrieval of names of animals and of tools activate different regions in the left temporal lobe. However, the details of this partition have been interpreted in different ways. Warrington & McCarthy (1983) and Warrington & Shallice (1984) explained the living vs. artifactual dissociation by taking the category distinction to be an effect of the difference among features that are crucial in the identification of living entities and artifacts: while living entities are identified mainly on the basis of perceptual features, artifacts are identified by their function. A later theory (Caramazza & Shelton 1998) claimed that animate and inanimate objects are treated by different knowledge systems separated by evolutionary pressure: domains of features pertaining to the recognition of living things, human faces, and perhaps tools may have been singled out as recognition of such entities had survival value for humans. Finally, Devlin et al. (1998) proposed to view the partition as the consequence of a difference in how recognition-relevant features are connected with one another: in the case of artifactual kinds, an object is recognized thanks to a characteristic coupling of form and function, whereas no such coupling individuates kinds of living things (e.g., eyes go with seeing in many animal species). For non-neutral surveys, see Caramazza & Mahon (2006) and Shallice & Cooper (2011).

On the other hand, it is also known that “semantic” (i.e., conceptual) competence may be lost in its entirety (though often gradually). This is what typically happens in semantic dementia. Empirical evidence has motivated theories of the neural realization of conceptual competence that are meant to account for both modality-specific deficits and pathologies that involve impairment across all modalities. The former may involve a difficulty or impossibility to categorize a visually exhibited object which, however, can be correctly categorized in other modalities (e.g., if the object is touched) or verbally described on the basis of the object’s name (i.e., on the basis of the lexical item supposedly associated with the category). The original “hub and spokes” model of the brain representation of concepts (Rogers et al. 2004, Patterson et al. 2007) accounted for both sets of findings by postulating that the semantic network is composed of a series of “spokes”, i.e., cortical areas distributed across the brain processing modality-specific (visual, auditory, motor, as well as verbal) sources of information, and that the spokes are two-ways connected to a transmodal “hub”. While damage to the spokes accounts for modality-specific deficits, damage to the hub and its connections explains the overall impairment of semantic competence. On this model, the hub is supposed to be located in the anterior temporal lobe (ATL), since semantic dementia had been found to be associated with degeneration of the anterior ventral and polar regions of both temporal poles (Guo et al. 2013). According to more recent, “graded” versions of the model (Lambon Ralph et al. 2017), the contribution of the hub units may vary depending on different patterns of connectivity to the spokes, to account for evidence of graded variation of function across subregions of ATL. It should be noted that while many researchers converge on a distributed view of semantic representation and on the role of domain-specific parts of the neural network (depending on differential patterns of functional connectivity), not everybody agrees on the need to postulate a transmodal hub (see, e.g., Mahon & Caramazza 2011).

Let us now turn to common nouns and proper names. As we have seen, in the philosophy of language of the last decades, proper names (of people, landmarks, countries, etc.) have being regarded as semantically different from common nouns. Neuroscientific research on the processing of proper names and common nouns concurs, to some extent. To begin with, the retrieval of proper names is doubly dissociated from the retrieval of common nouns. Some patients proved competent with common nouns but unable to associate names to pictures of famous people, or buildings, or brands (Ellis, Young & Critchley 1989); in other cases, people’s names were specifically affected (McKenna & Warrington 1980). Other patients had the complementary deficit. The patient described in Semenza & Sgaramella (1993) could name no objects at all (with or without phonemic cues) but he was able to name 10 out of 10 familiar people, and 18 out of 22 famous people with a phonemic cue. Martins & Farrayota‘s (2007) patient ACB also presented impaired object naming but spared retrieval of proper names. Such findings suggest distinct neural pathways for the retrieval of proper names and common nouns (Semenza 2006). The study of lesions and neuroimaging research both initially converged in identifying the left temporal pole as playing a crucial role in the retrieval of proper names, from both visual stimuli (Damasio et al. 1996) and the presentation of speaker voices (Waldron et al. 2014) (though in at least one case damage to the left temporal pole was associated with selective sparing of proper names; see Martins & Farrajota 2007). In addition, recent research has found a role for the uncinate fasciculus (UF). In patients undergoing surgical removal of UF, retrieval of common nouns was recovered while retrieval of proper names remained impaired (Papagno et al. 2016). The present consensus appears to be that “the production of proper names recruits a network that involves at least the left anterior temporal lobe and the left orbitofrontal cortex connected together by the UF” (Brédart 2017).

Furthermore, a few neuropsychological studies have described patients whose competence on geographical names was preserved while names of people were lost: one patient had preserved country names, though he had lost virtually every other linguistic ability (McKenna & Warrington 1978; see Semenza 2006 for other cases of selective preservation of geographical names). Other behavioral experiments seem to show that country names are closer to common nouns than to other proper names such as people and landmark names in that the connectivity between the word and the conceptual system is likely to require diffuse multiple connections, as with common nouns (Hollis & Valentine 2001). If these results were confirmed, it would turn out that the linguistic category of proper names is not homogeneous in terms of neural processing. Studies have also demonstrated that the retrieval of proper names from memory is typically a more difficult cognitive task than the retrieval of common nouns. For example, it is harder to name faces (of famous people) than to name objects; moreover, it is easier to remember a person’s occupation than her or his name. Interestingly, the same difference does not materialize in definition naming, i.e., in tasks where names and common nouns are to be retrieved from definitions (Hanley 2011). Though several hypotheses about the source of this difference have been proposed (see Brédart 2017 for a survey), no consensus has been reached on how to explain this phenomenon.

Finally, a few words on the distinction between the inferential and the referential component of lexical competence. As we have seen in Section 3.2 , Marconi (1997) suggested that processing of lexical meaning might be distributed between two subsystems, an inferential and a referential one. Beginning with Warrington (1975), many patients had been described that were more or less severely impaired in referential tasks such as naming from vision (and other perceptual modalities as well), while their inferential competence was more or less intact. The complementary pattern (i.e., the preservation of referential abilities with loss of inferential competence) is definitely less common. Still, a number of cases have been reported, beginning with a stroke patient of Heilman et al. (1976), who, while unable to perform any task requiring inferential processing, performed well in referential naming tasks with visually presented objects (he could name 23 of 25 common objects). In subsequent years, further cases were described. For example, in a study of 61 patients with lesions affecting linguistic abilities, Kemmerer et al. (2012) found 14 cases in which referential abilities were better preserved than inferential abilities. More recently, Pandey & Heilman (2014), while describing one more case of preserved (referential) naming from vision with severely impaired (inferential) naming from definition, hypothesized that “these two naming tasks may, at least in part, be mediated by two independent neuronal networks”. Thus, while double dissociation between inferential processes and naming from vision is well attested, it is not equally clear that it involves referential processes in general. On the other hand, evidence from neuroimaging is, so far, limited and overall inconclusive. Some neuroimaging studies (e.g., Tomaszewski-Farias et al. 2005, Marconi et al. 2013), as well as TMS mapping experiments (Hamberger et al. 2001, Hamberger & Seidel 2009) did find different patterns of activation for inferential vs. referential performances. However, the results are not entirely consistent and are liable to different interpretations. For example, the selective activation of the anterior left temporal lobe in inferential performances may well reflect additional syntactic demands involved in definition naming, rather than be due to inferential processing as such (see Calzavarini 2017 for a discussion).

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A new campaign wants to redefine the word ‘nature’ to include humans – here’s why this linguistic argument matters

Professor of Applied Ecology, University of Reading

Disclosure statement

Tom Oliver has received research funding from BBSRC, NERC and Natural England for quantifying climate change impacts on biodiversity and developing climate adaptation plans for humans and other species. He was affiliated with Defra as a senior scientific fellow on their Systems Research Programme, with the Government Office for Science working on long-term risks to the UK, and spent four years with the European Environment Agency on their scientific committee. He sits on the Food Standards Agency science council and Office for Environmental Protection expert college. He is author of The Self Delusion: The Surprising Science of Our Connection To Each Other and the Natural World, published by Weidenfeld and Nicholson.

University of Reading provides funding as a member of The Conversation UK.

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What does the word nature mean to you? Does it conjure visions of wild places away from the hustle and bustle of people, or does it include humans too? The meaning of nature has changed since the word was first used back as early as the 15th century .

Now a new campaign, We Are Nature , aims to persuade dictionaries to include humans in their definitions of nature. This campaign, a collaboration between a group of lawyers and a design company, involves a petition and open letter , as well as a collection of alternative definitions supplied by various thinkers and authors (including me). Here’s my definition of nature:

The living world comprised as the total set of organisms and relationships between them. These organisms include bacteria, fungi, plants and animals (including humans). Some definitions may also include non-living entities as part of nature – such as mountains, waterfalls and cloud formations – in recognition of their important role underpinning the web of life.

Derived from the Latin natura , literally meaning “birth”, nature used to only refer to the innate qualities or essential disposition of something. But over time, it also began to describe something “other” or separate to humans. For example, the Oxford English Dictionary (OED) defines nature as :

The phenomena of the physical world collectively; esp. plants, animals, and other features and products of the Earth itself, as opposed to humans and human creations.

But how did we arrive at such a definition, which hinges on us being apart from, rather than a part of, the natural world? Since the 17th century, a rationalist world view prompted by philosophers such as René Descartes increasingly saw things from a mechanical perspective, comparing the workings of the universe to a great machine. Rather than any kind of divine spirit inhabiting the natural world, this perspective emphasised the split between the human mind and physical matter.

Anything non-human fell into the latter category and was likened to clockwork machinery. But that view has since been found to lead to animal cruelty , and many environmental bodies including the European Environment Agency suggest this disconnect is accelerating the decline of nature.

Is it OK to change words in a dictionary through lobbying? There are two lines of thought here. One might argue yes, if the scientific evidence suggests the distinction between nature and humans is illusory – something I have argued based on findings in biology, ecology and neuroscience.

A dictionary definition represents society’s framing of the natural world. This in turn influences our perception of our place within it – and the actions we take to protect nature. So, the words we use have real-world impacts: they frame how we think and determine how we feel and act. Linguist George Lakoff has argued that they ultimately structure our society.

My children are growing up in a world where humans feel disconnected with nature – indeed, the UK ranks among the most disconnected countries. Research shows this leads people to make fewer positive environmental changes to their behaviour , such as reducing their carbon footprint, recycling, or doing voluntary conservation work.

Conversely, when people feel they are enmeshed with nature, they are not only greener in their behaviour but they tend to be happier . So I absolutely want my kids to grow up feeling they are part of nature.

There are some words that I certainly recommend we use less. I dislike the term “natural capital”, referring to nature as an asset that can be commodified and sold . These words have a place with professional environmentalists and policy, but they can also create psychological distancing and make us care less for natural world.

One sustainability-focused communications agency found the best way to motivate people about protecting nature is through messages based on awe and wonder , rather than the economic value of nature. Scientific studies back this up.

Dangers of controlling language

But I’m torn. Another line of thought suggests it’s not OK to change the meaning of words through lobbying, and that dictionaries should reflect how words are being used – the OED takes this position .

Dystopian fiction, including George Orwell’s Nineteen Eighty-Four , highlights the dangers of a world where controlling the language allows control of the population. Dictionaries bowing to pressure from lobbying seems to set a dangerous precedent.

With regards to the meaning of nature, if a word is too broad, it may lose its usefulness in communication, just like a blunt knife is a poor tool for carving food. People wanting to articulate the natural world may simply use other words, such as “environment”. This word is derived from the French environs , explicitly describing something surrounding us.

Environment has already been replacing nature in our modern lexicon. This may reflect a subtle cognitive shift towards increasingly seeing human beings as distinct entities, separate from the natural world.

Nature v environment: tracking the use of these words

But the We Are Nature campaign is not just lobbying the OED based on a preferred use of language. The organisers have collated many historical uses of the word nature from 1850 to the present day, some of which include humans in the meaning, and presented the dictionary with this evidence. In April 2024, as a result, the OED removed the label “obsolete” from a secondary, wider definition of nature comprising “the whole natural world, including human beings”.

But to change the primary definition of nature from “as opposed to humans” to “including humans” will require more people to use the word in a way that reflects how humans are intertwined with the whole web of life.

The great thing is, by doing this, we rekindle the bonds of care towards the living world around us. And by dispelling the illusion of our separation from nature, we can also expect to live happier lives . Words matter – there is restoration and joy from talking about how we are nature.

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