The effect of category learning on sensitivity to within-category correlations

Abstract

A salient property of many categories is that they are not just sets of independent features but consist of clusters of correlated features. Although there is much evidence that people are sensitive to between-categories correlations, the evidence about within-category correlations is mixed. Two experiments tested whether the disparities might be due to different learning and test tasks. Subjects learned about categories either by classifying items or by inferring missing features of items. Their knowledge of the correlations was measured with classification, prediction, typicality, and production tests. The inference learners, but not the classification learners, showed sensitivity to the correlations, although different tests were differentially sensitive. These results reconcile some earlier disparities and provide a more complete understanding of people's sensitivities to within-category correlations.