Conceptual atomists argue that most of our concepts are primitive. I take up three arguments that have been thought to support atomism and show that they are inconclusive. The evidence that allegedly backs atomism is equally compatible with a localist position on which concepts are structured representations with complex semantic content. I lay out such a localist position and argue that the appropriate position for a non-atomist to adopt is a pluralist view of conceptual structure. I show several ways in (...) which conceptual pluralism provides an advantage in satisfying the empirical and philosophical demands on a theory of conceptual structure and content. (shrink)

Traditionally, theories of concepts in psychology assume that concepts are a single, uniform kind of mental representation. But no single kind of representation can explain all of the empirical data for which concepts are responsible. I argue that the assumption that concepts are uniformly the same kind of mental structure is responsible for these theories’ shortcomings, and outline a pluralist theory of concepts that rejects this assumption. On pluralism, concepts should be thought of as being constituted by multiple representational kinds, (...) with the particular kind of concept used on an occasion being determined by the context. I argue that endorsing pluralism does not lead to eliminativism about concepts as an object of scientific interest. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities (...) have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities (...) have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

Topics in Cognitive Science, Volume 14, Issue 1, Page 31-44, January 2022.

The question of how people represent emotions is eminently important for a number of different domains of psychological research. The present study tested the assumption that emotion concepts are represented similar to theories in that they are comprised of a set of causally interrelated features. Using emotional scenarios and investigating the emotion concepts of anger, anxiety, and sadness it was found that people's representations of emotion concepts essentially involved the representation of the causal relation of emotion features and that the (...) causal status of a feature determined the feature's centrality in the concept. Moreover, people's representations of emotion concepts corresponded to basic assumptions of cognitive emotion theories, namely that cognitive appraisals cause other surface features of emotion, like expression and behaviour. By providing evidence for a theory-based representation, the present results show that the classical and the prototype approach are insufficient to model the representation of emotion concepts. (shrink)

Categories, as mental structures, are more than simply sums of property frequencies. A number of recent studies have supported the view that the properties of categories may be organised along functional lines and possibly dependency structures more generally. The study presented here investigates whether earlier findings reflect something unique in the English language/North American culture or whether the functional structuring of categories is a more universal phenomenon. A population of English-speaking Americans was compared to a population of Cantonese-speaking Hong Kong (...) Chinese. The findings clearly support the view that functional influences on category centrality are universal (or at least common to Cantonese-speaking Hong Kong Chinese and English-speaking Americans), albeit with specific cross-cultural/cross-linguistic group differences in the particular properties that are considered central to categories. (shrink)

This paper defends the claim that pragmatic encroachment—the idea that knowledge is sensitive to the practical stakes of believing—can explain a distinctive kind of epistemic injustice: the injustice that occurs when prejudice causes someone to know less than they otherwise would. This encroachment injustice, as we call it, occurs when the threat of being met with prejudice raises the stakes for someone to rely on her belief when acting, by raising the level of evidential support required for knowledge. We explain (...) this notion of encroachment injustice, connect it to the empirical literature on implicit bias, and defend it against important objections. (shrink)

People feel they understand complex phenomena with far greater precision, coherence, and depth than they really do; they are subject to an illusion—an illusion of explanatory depth. The illusion is far stronger for explanatory knowledge than many other kinds of knowledge, such as that for facts, procedures or narratives. The illusion for explanatory knowledge is most robust where the environment supports real‐time explanations with visible mechanisms. We demonstrate the illusion of depth with explanatory knowledge in Studies 1–6. Then we show (...) differences in overconfidence about knowledge across different knowledge domains in Studies 7–10. Finally, we explore the mechanisms behind the initial confidence and behind overconfidence in Studies 11 and 12, and discuss the implications of our findings for the roles of intuitive theories in concepts and cognition. (shrink)

This paper details the content and structure of the folk concept of life, and discusses its relevance for scientific research on life. In four empirical studies, we investigate which features of life are considered salient, universal, central, and necessary. Functionings, such as nutrition and reproduction, but not material composition, turn out to be salient features commonly associated with living beings (Study 1). By contrast, being made of cells is considered a universal feature of living species (Study 2), a central aspect (...) of life (Study 3), and our best candidate for being necessary for life (Study 4). These results are best explained by the hypothesis that people take life to be a natural kind subject to scientific scrutiny. (shrink)

Some of philosophy's most central concepts, including art, friendship, and happiness, have been argued to be dual character concepts. Their main characteristic is that they encode not only a descriptive dimension but also an independent normative dimension for categorization. This article introduces the class of dual character concepts and discusses various accounts of their content and structure. A specific focus will be placed on their relation to two other classes of concepts, thick concepts and natural kind concepts. The study of (...) dual character concepts not only demonstrates that a wide range of concepts is inherently normative, but it also reveals new possibilities for investigating gender biases, generics, and social roles. (shrink)

This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new formalisms that allow cycles are introduced and evaluated. Dynamic Bayesian networks represent cycles by unfolding them over time. Chain graphs augment CGMs by allowing the presence of undirected links (...) that model feedback relations between variables. Unfolded chain graphs are chain graphs that unfold over time. An existing model of causal cycles is also evaluated. Four experiments in which subjects reason about categories with cyclically related features provided evidence against DBNs and alpha centrality and for the two types of chain graphs. Chain graphs—a mechanism for representing the equilibrium distribution of a dynamic system—may thus be good candidates for modeling how people reason causally with complex systems. Applications of chain graphs to areas of cognition other than category-based judgments are discussed. (shrink)

A theory of categorization is presented in which knowledge of causal relationships between category features is represented in terms of asymmetric and probabilistic causal mechanisms. According to causal‐model theory, objects are classified as category members to the extent they are likely to have been generated or produced by those mechanisms. The empirical results confirmed that participants rated exemplars good category members to the extent their features manifested the expectations that causal knowledge induces, such as correlations between feature pairs that are (...) directly connected by causal relationships. These expectations also included sensitivity to higher‐order feature interactions that emerge from the asymmetries inherent in causal relationships. Quantitative fits of causal‐model theory were superior to those obtained with extensions to traditional similarity‐based models that represent causal knowledge either as higher‐order relational features or “prior exemplars” stored in memory. (shrink)

A central question in cognitive research concerns how new properties are generalized to categories. This article introduces a model of how generalizations involve a process of causal inference in which people estimate the likely presence of the new property in individual category exemplars and then the prevalence of the property among all category members. Evidence in favor of this causal‐based generalization (CBG) view included effects of an existing feature’s base rate (Experiment 1), the direction of the causal relations (Experiments 2 (...) and 4), the number of those relations (Experiment 3), and the distribution of features among category members (Experiments 4 and 5). The results provided no support for an alternative view that generalizations are promoted by the centrality of the to‐be‐generalized feature. However, there was evidence that a minority of participants based their judgments on simpler associative reasoning processes. (shrink)

Nominal concepts represent things as tokens of types. Recent research suggests that we represent principled connections between the type of thing something is (e.g., DOG) and some of its properties (k‐properties; e.g., having four legs for dogs) but not other properties (t‐properties; e.g., being brown for dogs). Principled connections differ from logical, statistical, and causal connections. Principled connections license (i) the expectation that tokens of the type will generally possess their k‐properties, (ii) formal explanations (i.e., explanation of the presence of (...) k‐properties in tokens of a type by reference to the type of thing it is), and (iii) normative expectations concerning the presence of k‐properties in tokens of the type. The present paper investigates the hypothesis that representing principled connections requires representing properties as aspects of being the relevant kind of thing (Aspect Hypothesis). Experiment 1 provides a direct test of the Aspect Hypothesis. Experiments 2 and 3 provide indirect tests of the Aspect Hypothesis. All three experiments provide support for the Aspect Hypothesis. Experiment 4 investigates a prediction of the Aspect Hypothesis concerning the manner in which formal explanations are licensed by principled connections. Finally, Experiment 5 investigates a prediction of the Aspect Hypothesis concerning the nature of the normative expectations licensed by principled connections. Together these results provide strong evidence for the idea that representing principled connections involves representing a property as being an aspect of being a given kind of thing. The results also help clarify the manner in which formal explanation differs from other modes of explanation. Finally, the results of the experiments are used to motivate a proposal concerning the formal structure of the conceptual representations implicated by principled connections. This structure provides a domain‐general way of structuring our concepts and embodies the perspective we take when we think and talk of things as being instances of a kind. (shrink)

Generic sentences (e.g., bare plural sentences such as “dogs have four legs” and “mosquitoes carry malaria”) are used to talk about kinds of things. Three experiments investigated the conceptual foundations of generics as well as claims within the formal semantic approaches to generics concerning the roles of prevalence, cue validity and normalcy in licensing generics. Two classes of generic sentences that pose challenges to both the conceptually based and formal semantic approaches to generics were investigated. Striking property generics (e.g. “sharks (...) bite swimmers”) are true even though only a tiny minority of instances have the property and thus pose obvious problems for quantificational approaches, and they also do not seem to characterize kinds in terms of the principled or statistical connections investigated in previous research ( Prasada and Dillingham, 2006 ; Prasada and Dillingham, 2009). The second class — minority characteristic generics (e.g. “ducks lay eggs”) — also poses serious problems for quantificational accounts, and appears to involve principled connections even though fewer than half of its instances have the relevant property. The experiments revealed three principal discoveries: first, striking generics involve neither principled nor statistical connections. Instead, they involve a causal connection between a kind and a property. Second, minority characteristic generics exhibit the characteristics of principled connections, which suggests that principled connections license the expectation that most instances will have the property, but do not require it. Finally, the experiments also provided evidence that prevalence and the acceptability of generics may be dissociated and provided data that are problematic for normalcy approaches to generics, and for the idea that cue validity licenses low prevalence generics. As such, the studies provided evidence in favor of a conceptually based approach to the semantics of generics ( Leslie, 2007 ; Leslie, 2008; see also Carlson, 2009). (shrink)

The meaning that expressions take on particular occasions often depends on the context in ways which seem to transcend its direct effect on context-sensitive parameters. ‘Truth-conditional pragmatics’ is the project of trying to model such semantic flexibility within a compositional truth-conditional framework. Most proposals proceed by radically ‘freeing up’ the compositional operations of language. I argue, however, that the resulting theories are too unconstrained, and predict flexibility in cases where it is not observed. These accounts fall into this position because (...) they rarely, if ever, take advantage of the rich information made available by lexical items. I hold, instead, that lexical items encode both extension and non-extension determining information. Under certain conditions, the non-extension determining information of an expression e can enter into the compositional processes that determine the meaning of more complex expressions which contain e. This paper presents and motivates a set of type-driven compositional operations that can access non-extension determining information and introduce bits of it into the meaning of complex expressions. The resulting multidimensional semantics has the tools to deal with key cases of semantic flexibility in appropriately constrained ways, making it a promising framework to pursue the project of truth-conditional pragmatics. (shrink)

Pietraszewski provides a compelling case that representations of certain interaction-types are the “cognitive primitives” that allow all tokens of group-in-conflict to be represented within the mind. Here, I argue that the folk concept GROUP encodes shared intentions and goals as more central than these interaction-types, and that providing a computational theory of social groups will be more difficult than Pietraszewski envisages.

I argue that in addressing worries about the validity and reliability of implicit measures of social cognition, theorists should draw on research concerning “entitativity perception.” In brief, an aggregate of people is perceived as highly “entitative” when its members exhibit a certain sort of unity. For example, think of the difference between the aggregate of people waiting in line at a bank versus a tight-knit group of friends: The latter seems more “groupy” than the former. I start by arguing that (...) entitativity perception modulates the activation of implicit biases and stereotypes. I then argue that recognizing this modulatory role will help researchers to address concerns surrounding the validity and reliability of implicit measures. (shrink)

In two recent papers, Rose and Nichols present evidence in favor of the view that humans represent category essences in terms of a telos, such as honey-making, and not in terms of scientific essences, such as bee DNA. In this paper, I challenge their interpretation of the evidence, and show that it is directly predicted by the main theory they seek to undermine. I argue that their results can be explained as instances of diagnostic reasoning about scientific essences.

Recent theoretical and empirical work suggests that explanation and categorization are intimately related. This paper explores the hypothesis that explanations can help structure conceptual representations, and thereby influence the relative importance of features in categorization decisions. In particular, features may be differentially important depending on the role they play in explaining other features or aspects of category membership. Two experiments manipulate whether a feature is explained mechanistically, by appeal to proximate causes, or functionally, by appeal to a function or goal. (...) Explanation type has a significant impact on the relative importance of features in subsequent categorization judgments, with functional explanations reversing previously documented effects of [”]causal status’. The findings suggest that a feature’s explanatory importance can impact categorization, and that explanatory relationships, in addition to causal relationships, are critical to understanding conceptual representation. (shrink)

Five experiments provide evidence for a class of ‘dual character concepts.’ Dual character concepts characterize their members in terms of both (a) a set of concrete features and (b) the abstract values that these features serve to realize. As such, these concepts provide two bases for evaluating category members and two different criteria for category membership. Experiment 1 provides support for the notion that dual character concepts have two bases for evaluation. Experiments 2-4 explore the claim that dual character concepts (...) have two different criteria for category membership. The results show that when an object possesses the appropriate concrete features, but does not fulfill the appropriate abstract value, it is judged to be a category member in one sense but not in another. Finally, Experiment 5 uses the theory developed here to construct artificial dual character concepts and examines whether participants react to these artificial concepts in the same way as naturally occurring dual character concepts. The present studies serve to define the nature of dual character concepts and distinguish them from other types of concepts (e.g., natural kind concepts), which share some, but not all of the properties of dual character concepts. More broadly, these phenomena suggest a normative dimension in everyday conceptual representation. (shrink)

The rise of appeals to intuitive theories in many areas of cognitive science must cope with a powerful fact. People understand the workings of the world around them in far less detail than they think. This illusion of knowledge depth has been uncovered in a series of recent studies and is caused by several distinctive properties of explanatory understanding not found in other forms of knowledge. Other experimental work has shown that people do have skeletal frameworks of expectations that constrain (...) richer ad hoc theory construction on the fly. These frameworks are supplemented by an ability to evaluate and rely on the division of cognitive labour in one's culture, an ability shown to be present even in young children. (shrink)

Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status, and relational centrality. Adult classification was driven primarily by coherence when causal links were deterministic (...) (Experiment 1) but showed additional influences of causal status when links were probabilistic (Experiment 2). Children’s classification was based primarily on causal coherence in both cases. There was no effect of relational centrality in either age group. These results suggest that the generative model (Rehder, 2003a) provides a good account of causal categorization in children as well as adults. (shrink)

Two experiments examined the impact of causal relations between features on categorization in 5‐ to 6‐year‐old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status, and relational centrality. Adult classification was driven primarily by coherence when causal links were deterministic (...) (Experiment 1) but showed additional influences of causal status when links were probabilistic (Experiment 2). Children’s classification was based primarily on causal coherence in both cases. There was no effect of relational centrality in either age group. These results suggest that the generative model (Rehder, 2003a) provides a good account of causal categorization in children as well as adults. (shrink)

A feature is central to a concept to the extent that other features depend on it. Four studies tested the hypothesis that people will project a feature from a base concept to a target concept to the extent that they believe the feature is central to the two concepts. This centrality hypothesis implies that feature projection is guided by a principle that aims to maximize the structural commonality between base and target concepts. Participants were told that a category has two (...) or three novel features. One feature was the most central in that more properties depended on it. The extent to which the target shared the feature's dependencies was manipulated by varying the similarity of category pairs. Participants' ratings of the likelihood that each feature would hold in the target category support the centrality hypothesis with both natural kind and artifact categories and with both well-specified and vague dependency structures. (shrink)

How are biases encoded in our representations of social categories? Philosophical and empirical discussions of implicit bias overwhelmingly focus on salient or statistical associations between target features and representations of social categories. These are the sorts of associations probed by the Implicit Association Test and various priming tasks. In this paper, we argue that these discussions systematically overlook an alternative way in which biases are encoded, that is, in the dependency networks that are part of our representations of social categories. (...) Dependency networks encode information about how features in a conceptual representation depend on each other. This information determines the degree of centrality of a feature for a conceptual representation. Importantly, centrally encoded biases systematically disassociate from those encoded in salient-statistical associations. Furthermore, the degree of centrality of a feature determines its cross-contextual stability: in general, the more central a feature is for a concept, the more likely it is to survive into a wide array of cognitive tasks involving that concept. Accordingly, implicit biases that are encoded in the central features of concepts are predicted to be more resilient across different tasks and contexts. As a result, the distinction between centrally encoded and salient-statistical biases has important theoretical and practical implications. (shrink)

Over the past few decades, cognitive science has identified several forms of reasoning that make essential use of conceptual knowledge. Despite significant theoretical and empirical progress, there is still no unified framework for understanding how concepts are used in reasoning. This paper argues that the theory of conceptual spaces is capable of filling this gap. Our strategy is to demonstrate how various inference mechanisms which clearly rely on conceptual information—including similarity, typicality, and diagnosticity-based reasoning—can be modeled using principles derived from (...) conceptual spaces. Our first topic analyzes the role of expectations in inductive reasoning and their relation to the structure of our concepts. We examine the relationship between using generic expressions in natural language and common-sense reasoning as a second topic. We propose that the strength of a generic can be described by distances between properties and prototypes in conceptual spaces. Our third topic is category-based induction. We demonstrate that the theory of conceptual spaces can serve as a comprehensive model for this type of reasoning. The final topic is analogy. We review some proposals in this area, present a taxonomy of analogical relations, and show how to model them in terms of distances in conceptual spaces. We also briefly discuss the implications of the model for reasoning with concepts in artificial systems. (shrink)

Novice designers produced a sequence of sketches while inventing a logo for a novel brand of soft drink. The sketches were scored for the presence of specific objects, their local features and global composition. Self‐assessment scores for each sketch and art critics' scores for the end products were collected. It was investigated whether the design evolves in an essentially random fashion or according to an overall heuristic. The results indicated a macrostructure in the evolution of the design, characterized by two (...) stages. For the majority of participants, the first stage is marked by the introduction and modification of novel objects and their local and global aspects; the second stage is characterized by changes in their global composition. The minority that showed the better designs has a different strategy, in which most global changes were made in the beginning. Although participants did not consciously apply these strategies, their self‐assessment scores reflect the stages of the process. (shrink)

Philosophers are often credited with particularly well-developed conceptual skills. The ‘expertise objection’ to experimental philosophy builds on this assumption to challenge inferences from findings about laypeople to conclusions about philosophers. We draw on psycholinguistics to develop and assess this objection. We examine whether philosophers are less or differently susceptible than laypersons to cognitive biases that affect how people understand verbal case descriptions and judge the cases described. We examine two possible sources of difference: Philosophers could be better at deploying concepts, (...) and this could make them less susceptible to comprehension biases (‘linguistic expertise objection’). Alternatively, exposure to different patterns of linguistic usage could render philosophers vulnerable to a fundamental comprehension bias, the linguistic salience bias, at different points (‘linguistic usage objection’). Together, these objections mount a novel ‘master argument’ against experimental philosophy. To develop and empirically assess this argument, we employ corpus analysis and distributional semantic analysis and elicit plausibility ratings from academic philosophers and psychology undergraduates. Our findings suggest philosophers are better at deploying concepts than laypeople but are susceptible to the linguistic salience bias to a similar extent and at similar points. We identify methodological consequences for experimental philosophy and for philosophical thought experiments. (shrink)

Many philosophical thought experiments and arguments involve unusual cases. We present empirical reasons to doubt the reliability of intuitive judgments and conclusions about such cases. Inferences and intuitions prompted by verbal case descriptions are influenced by routine comprehension processes which invoke stereotypes. We build on psycholinguistic findings to determine conditions under which the stereotype associated with the most salient sense of a word predictably supports inappropriate inferences from descriptions of unusual (stereotype-divergent) cases. We conduct an experiment that combines plausibility ratings (...) with pupillometry to document this “salience bias.” We find that under certain conditions, competent speakers automatically make stereotypical inferences they know to be inappropriate. (shrink)

Discussions in social psychology overlook an important way in which biases can be encoded in conceptual representations. Most accounts of implicit bias focus on ‘mere associations’ between features and representations of social groups. While some have argued that some implicit biases must have a richer conceptual structure, they have said little about what this richer structure might be. To address this lacuna, we build on research in philosophy and cognitive science demonstrating that concepts represent dependency relations between features. These relations, (...) in turn, determine the centrality of a feature f for a concept C: roughly, the more features of C depend on f, the more central f is for C. In this paper, we argue that the dependency networks that link features can encode significant biases. To support this claim, we present a series of studies that show how a particular brilliance-gender bias is encoded in the dependency networks which are part of the concepts of female and male academics. We also argue that biases which are encoded in dependency networks have unique implications for social cognition. (shrink)

The concepts expressed by social role terms such as artist and scientist are unique in that they seem to allow two independent criteria for categorization, one of which is inherently normative. This study presents and tests an account of the content and structure of the normative dimension of these “dual character concepts.” Experiment 1 suggests that the normative dimension of a social role concept represents the commitment to fulfill the idealized basic function associated with the role. Background information can affect (...) which basic function is associated with each social role. However, Experiment 2 indicates that the normative dimension always represents the relevant commitment as an end in itself. We argue that social role concepts represent the commitments to basic functions because that information is crucial to predict the future social roles and role-dependent behavior of others. (shrink)