Proceedings of the Annual Meeting of the Cognitive Science Society

We investigated category-based inference tasics, contrasting the predictions of structural alignment theory as applied to categorization with those of feature-overlap models of similarity. We provide evidence for the differential level of importance of causal information in category-based inference tasks, as predicted by the systematicity principle (Centner, 1983). Our basic paradigm consists of a task in which participants decide between inferences based on shared causal antecedents or shared attributes. Experiment I demonstrated a preference for the causal inference when the target animal shares one attribute with one of the base animals and one causal antecedent with the other base. In Experiment 2, we found that this preference holds even when the target animal shares greater attribute similarity with the noncausal base (i.e., the target shares two attributes with one base and one causal antecedent with the other). Experiment 2 also served to demonstrate that this result can indeed be attributed to the influence of causal structure, and not to surface stimulus properties, such as sentence length. Overall, the results agreed with the predictions of structural alignment theory and were inconsistent with a feature-overlap account.