Causal status as a determinant of feature centrality

One of the major problems in categorization research is the lack of systema tic ways of constraining feature weights. We propose one method of operatio nalizing feature centrality, a causal status hypothesis which states that a cause feature is judged to be more central than its effect feature in cate gorization. In Experiment 1, participants learned a novel category with thr ee characteristic features that were causally related into a single causal chain and judged the likelihood that new objects belong to the category. Li kelihood ratings for items missing the most fundamental cause were lower th an those for items missing the intermediate cause, which in turn were lower than those for items missing the terminal effect. The causal status effect was also obtained in goodness-of-exemplar judgments (Experiment 2) and in free-sorting tasks (Experiment 3), but it was weaker in similarity judgment s than in categorization judgments (Experiment 4). Experiment 5 shows that the size of the causal status effect is moderated by plausibility of causal relations, and Experiment 6 shows that effect features can be useful in re trieving information about unknown causes. We discuss the scope of the caus al status effect and its implications for categorization research. (C) 2000 Academic Press.