How causal knowledge affects classification: A generative theory of categorization

Bob Rehder, Shinwoo Kim

Research output: Contribution to journalArticlepeer-review

Abstract

Several theories have been proposed regarding how causal relations among features of objects affect how those objects are classified. The assumptions of these theories were tested in 3 experiments that manipulated the causal knowledge associated with novel categories. There were 3 results. The 1st was a multiple cause effect in which a feature's importance increases with its number of causes. The 2nd was a coherence effect in which good category members are those whose features jointly corroborate the category's causal knowledge. These 2 effects can be accounted for by assuming that good category members are those likely to be generated by a category's causal laws. The 3rd result was a primary cause effect, in which primary causes are more important to category membership. This effect can also be explained by a generative account with an additional assumption: that categories often are perceived to have hidden generative causes.

Original languageEnglish (US)
Pages (from-to)659-683
Number of pages25
JournalJournal of Experimental Psychology: Learning Memory and Cognition
Volume32
Issue number4
DOIs
StatePublished - Jul 2006

Keywords

  • Categorization
  • Causal knowledge
  • Causal model theory
  • Causal status hypothesis
  • Classification

ASJC Scopus subject areas

  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Linguistics and Language

Fingerprint Dive into the research topics of 'How causal knowledge affects classification: A generative theory of categorization'. Together they form a unique fingerprint.

Cite this