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Causal Status as a Determinant of Feature Centrality
- Cognitive Psychology
, 2000
"... this article. We also thank Denise Hatton, Tisha Baldwin, Joshua Nathan, Helen Sullivan, and Julia Wenzlaff for collecting data. Some of the stimulus materials used in Experiments 1 and 2 are adapted from the stimulus materials used in Rehder and Hastie (1997) and we thank them for inspiring many of ..."
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Cited by 28 (2 self)
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this article. We also thank Denise Hatton, Tisha Baldwin, Joshua Nathan, Helen Sullivan, and Julia Wenzlaff for collecting data. Some of the stimulus materials used in Experiments 1 and 2 are adapted from the stimulus materials used in Rehder and Hastie (1997) and we thank them for inspiring many of the features and objects used in these studies. This project was supported by a National Science Foundation Grant (NSF-SBR 9515085) and a National Institute of Mental Health Grant (RO1 MH57737) given to Woo-kyoung Ahn, a National Science Foundation Graduate Fellowship to Nancy Kim, and a National Institute of Mental Health Postdoctoral Fellowship (MH10888-01A1) to Mary Lassaline
Why Are Different Features Central for Natural Kinds and Artifacts?: The Role of Causal Status in Determining Feature Centrality
, 1998
"... Ahn and Lassaline [Ahn, W., Lassaline, M.E., 1995. Causal structure in categorization. ..."
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Cited by 21 (1 self)
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Ahn and Lassaline [Ahn, W., Lassaline, M.E., 1995. Causal structure in categorization.
The Rules versus Similarity Distinction
- Behavioural and Brain Sciences
, 2005
"... To be published in Behavioral and Brain Sciences (in press) ..."
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Cited by 10 (1 self)
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To be published in Behavioral and Brain Sciences (in press)
On the Functional Origins of Essentialism
- Mind and Society
, 2001
"... This essay examines the proposal that psychological essentialism results from a history of natural selection acting on human representation and inference systems. It has been argued that the features that distinguish essentialist representational systems are especially well suited for representing n ..."
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Cited by 3 (0 self)
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This essay examines the proposal that psychological essentialism results from a history of natural selection acting on human representation and inference systems. It has been argued that the features that distinguish essentialist representational systems are especially well suited for representing natural kinds. If the evolved function of essentialism is to exploit the rich inductive potential of such kinds, then it must be subserved by cognitive mechanisms that carry out at least three distinct functions: identifying these kinds in the envi - ronment, constructing essentialized representations of them, and constraining inductive infer - ences about kinds. Moreover, there are different kinds of kinds, ranging from nonliving sub - stances to biological taxa to within-species kinds such as sex, and the causal processes that render these categories coherent for the purposes of inductive generalization vary. If the evolved function of essentialism is to support inductive generalization under ignorance of true causes, and if kinds of kinds vary in the implicit assumptions that support valid inductive inferences about them, then we expect different, functionally incompatible modes of essen - tialist thinking for different kinds. In particular, there should be differences in how biological and nonbiological substances, biological taxa, and biological and social role kinds are essen - tialized. The functional differences between these kinds of essentialism are discussed.
doi:10.3758/MC.37.6.715 Classification as diagnostic reasoning
"... An ongoing goal in the field of categorization has been to determine how objects ’ features provide evidence of membership in one category versus another. Well-known findings include that feature diagnosticity is a function of how often the feature appears in category members versus nonmembers, thei ..."
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Cited by 3 (2 self)
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An ongoing goal in the field of categorization has been to determine how objects ’ features provide evidence of membership in one category versus another. Well-known findings include that feature diagnosticity is a function of how often the feature appears in category members versus nonmembers, their perceptual salience, how features are used in support of inferences, and how observable features are related to other observable features. We tested how diagnosticity is affected by causal relations between observable and unobserved features. Consistent with our view of classification as diagnostic reasoning, we found that observable features are more diagnostic to the extent that they are caused by underlying features that define category membership, because the presence of the latter can be (causally) inferred from the former. Implications of these results for current views of conceptual structure and models of categorization are discussed. It is generally accepted that people’s concepts include not only the features and attributes of the entity being represented, but also the ways in which those features are related to one another. For example, we know that hormones can alter a person’s behavior, that chemical structure can affect a substance’s hardness, and that processor
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"... Two experiments examined the impact of causal relations between features on categorization by adults and 5-6-year-old children. Participants learned about artificial categories containing instances with two causally related features and two non-causal features. They then selected the most likely cat ..."
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Two experiments examined the impact of causal relations between features on categorization by adults and 5-6-year-old children. Participants learned about artificial categories containing instances with two causally related features and two non-causal 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 and centrality when links were probabilistic (Experiment 2). Children’s classification was based primarily on causal coherence in both cases. These results suggest that the generative model [Rehder, B. (2003). A causalmodel theory of conceptual representation and categorization. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 1141-1159] provides a good account of causal categorization in both children and adults. Children’s Causal Categorization 3 It is well established that causal knowledge plays an important role in adult categorization and

