title: What some effects might not be: the time to verify membership in "well-defined" categories.
abstract: Armstrong, Gleitman, and Gleitman (1983) reported shorter categorization times for members of well-defined categories judged more typical. They concluded that these effects could not originate in a graded, similarity-based category representation and consequently that the typicality effects obtained with natural categories might not be indicative of such a structure either. In this article, we re-examine this conclusion, focusing first on the performance obtained with well-defined categories of different sizes. Only the larger categories used showed variations in typicality ratings and produced typicality effects on categorization times. However, multiple regression analyses showed the effects on categorization times to be better explained by a measure of associative strength, called category dominance. The range of various predictor variables was equated in a follow-up experiment involving large, natural, and well-defined categories. Results obtained with well-defined categories showed pronounced dominance effects when typicality was controlled, but no reliable typicality effect when category dominance and instance familiarity were controlled. Results were opposite for natural categories. By showing that well-defined categories fail to produce unbiased typicality effects, our results bring added support to the hypothesis that the effects obtained with natural categories originate in a graded, similarity-based category structure.
authors.affiliation: Départment de psychologie, Université de Montréal, C.P. 6128, Succursale Centre-Ville, Montréal, Québec, Canada H3C 3J7. larochel@psy.umontreal.ca
authors.forename: S
authors.initials: S
authors.lastname: Larochelle
authors.forename: S
authors.initials: S
authors.lastname: Richard
authors.forename: I
authors.initials: I
authors.lastname: Soulières
mesh_terms: D003210:Concept Formation; D006801:Humans; D010153:Paired-Associate Learning; D011930:Reaction Time; D012660:Semantics