Abstract
What makes category labels different from feature labels in predictive inference? This study suggests that category labels tend to make inductive reasoning polarized and homogeneous. In two experiments, participants were shown two schematic pictures of insects side by side and predicted the value of a hidden feature of one insect on the basis of the other insect. Arbitrary verbal labels were shown above the two pictures, and the meanings of the labels were manipulated in the instructions. In one condition, the labels represented the category membership of the insects, and in the other conditions, the same labels represented attributes of the insects. When the labels represented category membership, participants’ responses became substantially polarized and homogeneous, indicating that the mere reference to category membership can modify reasoning processes.
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This research was supported by a College Faculty Research Enhancement Award, a Glasscock Center Faculty Fellow Award, and a Developmental Grant by the Mexican American and U.S. Latino Research Center (Texas A & M University), all given to the first author.
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Yamauchi, T., Yu, N.Y. Category labels versus feature labels: Category labels polarize inferential predictions. Memory & Cognition 36, 544–553 (2008). https://doi.org/10.3758/MC.36.3.544
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DOI: https://doi.org/10.3758/MC.36.3.544