Labeling Bias and Categorical Induction: Generative Aspects of Category Information
Abstract
When a person is characterized categorically with a label (e.g., Linda is a feminist), people tend to think
that the attributes associated with that person are central and long lasting (S. Gelman & G. D. Heyman,
1999). This bias, which is related to category-based induction and stereotyping, has been thought to arise
because a category label (e.g., feminist) activates the dominant properties associated with the representation
of the category. This explanation implies that categorical information influences inferential
processes mainly by conjuring up main attributes or instances represented in the category. However, the
present experiments reveal that this attribute-based explanation of induction does not provide a complete
picture of inferential processes. The results from 3 experiments suggest that category information can
affect inferences of attributes that are not directly related to the category, suggesting that categories not
only activate likely attributes but also help integrate unlikely or even unrelated attributes.