Abstract

Two studies examined multiple category reasoning in property induction with cross-classified foods. Pilot tests identified foods that were more typical of a taxonomic category (e.g., "fruit"; termed 'taxonomic primary') or a script based category (e.g., "snack foods"; termed 'script primary'). They also confirmed that taxonomic categories were perceived as more coherent than script categories. In Experiment 1 participants completed an induction task in which information from multiple categories could be searched and combined to generate a property prediction about a target food. Multiple categories were more often consulted and used in prediction for script primary than for taxonomic primary foods. Experiment 2 replicated this finding across a range of property types but found that multiple category reasoning was reduced in the presence of a concurrent cognitive load. Property type affected which categories were consulted first and how information from multiple categories was weighted. The results show that multiple categories are more likely to be used for property predictions about cross-classified objects when an object is primarily associated with a category that has low coherence.

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