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, 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.
Rehder
Bob
B
New York University, New York, New York, USA. bob.rehder@nyu.edu
Kim
Shinwoo
S
D000818:Animals; D001245:Association Learning; D015984:Causality; D002965:Classification / Q000379:methods*; D003937:Diagnosis, Differential; D006801:Humans; D015233:Models, Statistical; D011337:Probability Learning; D011340:Problem Solving
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