Two experiments examined the impact of causal relations between features on categorization by adults and 5-6-year-old children. Participants learned about artificial categories containing instances with two causally related features and two non-causal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status and relational centrality. Adult classification was driven primarily by coherence when causal links were deterministic (Experiment 1), but showed additional influences of causal status and centrality when links were probabilistic (Experiment 2). Children’s classification was based primarily on causal coherence in both cases. These results suggest that the generative model [Rehder, B. (2003). A causalmodel theory of conceptual representation and categorization. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 1141-1159] provides a good account of causal categorization in both children and adults. Children’s Causal Categorization 3 It is well established that causal knowledge plays an important role in adult categorization and

Design history function (i.e., what an artifact was made for) is a central aspect of artifact conceptualization. A generally accepted explanation is that design history is central because it is the root cause for many other artifact properties. In Exp. 1, an inference task allowed us to probe participants ‘ causal models, and then to use them when making predictions for Exp. 2. Design history was, in fact, part of what participants viewed as conceptually relevant. Predictions for Exp. 2 were derived using the currently most comprehensive theory about how causal knowledge affects categorization. Our results show that though participants used design history, functional outcome and physical structure to conceptualize artifacts, the effect of design history was independent from knowledge of physical structure and functional outcome. This result is inconsistent with a causal knowledge explanation of design history‘s conceptual centrality.

Conjunctive causes are causes that all need to be present for an effect to occur. They contrast with independent causes that by themselves can each bring about an effect. We extend existing “causal power ” representations of independent causes to include a representation of conjunctive causes. We then demonstrate how independent vs. conjunctive representations imply sharply different patterns of reasoning (e.g., explaining away effects for independent causes as compared to exoneration effects for conjunctive causes). An experiment testing how people reason with independent and conjunctive causes found that their inferences generally matched the model’s prediction, albeit with some important exceptions. Rather than operating in a vacuum, causes frequently interact with other factors to produce their effects. For example, the conjunction of two or more variables is often necessary for an outcome to occur. A spark may only produce fire if there is fuel to ignite, a virus may only cause disease if one’s immune system is suppressed, the motive to commit murder may result in death only if the means to carry out the crime are available. Sometimes, conjunctive causes take the form of enablers. For example, the presence of oxygen enables fire given spark and fuel. In contrast, disablers interact with existing causes by preventing normal outcomes. Although the eight ball’s path to the side pocket may appear inevitable, it may be interrupted by an earthquake, a falling ceiling tile, or a spilled beer. The last 20 years has seen a growing interest in the role of causal knowledge in numerous areas of cognition. Many studies have investigated how causal relations are learned from observed correlations (Cheng, 1997; Gopnik et al.,