Classification as diagnostic reasoning.

Full Abstract

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.

Author information

Author/s: Rehder, Bob (B); Kim, Shinwoo (S);

Affiliation: New York University, New York, New York, USA. bob.rehder(-atsign-)nyu.edu

Journal and publication information

Publication Type: Journal Article

Journal: Memory & cognition (Mem Cognit), published in United States. (Language: eng)

Reference: 2009-Sep; vol 37 (issue 6) : pp 715-29

Dates: Created 2009/08/14; Completed 2009/10/19;

PMID: 19679853, status: MEDLINE (last retrieval date: 10/19/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

External Links for this article
(including full text providers, if available):

Click Electronic Full-text Provider Links to see options for finding the electronic full text links to this article. Note there may be a subscription or fee required for access to the full text. See our FAQ for information on finding FREE full text articles.

This article may also be located in paper journal collections available in many libraries. Use the Journal and Publication Information above to find the full article.