Associative and similarity-based processes in categorization decisions

Hampton, J. A. (1997). Associative and similarity-based processes in categorization decisions. Memory & Cognition, 25(5), pp. 625-640.

[img]
Preview
PDF
Download (161kB) | Preview

Abstract

Two experiments were directed at distinguishing associative and similarity-based accounts of systematic differences in categorization time for different items in natural categories. Experiment 1 investigated the correlation of categorization time with three measures of instance centrality in a category. Production frequency (PF), rated typicality, and familiarity from category norms for British participants (Hampton & Gardiner, 1983) were used to predict mean categorization times for 531 words in 12 semantic categories. PF and typicality (but not familarity) were found to make significant and independent contributions to categorization time. Error rates were related only to typicality (apart from errors made to ambiguous or unknown items). Experiment 2 provided a further dissociation of PF and typicality. Manipulating the difficulty of the task through the relatedness of the false items interacted primarily with the effect of typicality on categorization time, whereas, under conditions of easy discrimination, prior exposure to the category exemplars affected only the contribution of PF to the decision time. The dissociation of typicality and PF measures is interpreted as providing evidence that speeded categorization involves both retrieval of associations indexed by PF and a similarity-based decision process indexed by typicality.

Item Type: Article
Uncontrolled Keywords: VERIFYING CATEGORY MEMBERSHIP, SEMANTIC MEMORY, WORD-FREQUENCY, VERIFICATION, TYPICALITY, REPRESENTATIONS, CONNECTIONISM, DETERMINANTS, FAMILIARITY, STATEMENTS
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Divisions: School of Social Sciences > Department of Psychology
URI: http://openaccess.city.ac.uk/id/eprint/991

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics