How Causal Knowledge Affects Classification: A Generative Theory of Categorization

Autor/inn/en	Rehder, Bob; Kim, ShinWoo
Titel	How Causal Knowledge Affects Classification: A Generative Theory of Categorization
Quelle	In: Journal of Experimental Psychology: Learning, Memory, and Cognition, 32 (2006) 4, S.659-683 (25 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0278-7393
Schlagwörter	Causal Models; Classification; Theories; Experimental Psychology + Suchen Sie Ihr Suchwort? Kausalanalyse; Classification system; Klassifikation; Klassifikationssystem; Theory; Theorie; Experimentelle Psychologie
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. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10