Proceedings of the Annual Meeting of the Cognitive Science Society

Consider the following two (hypothetical) generic causal claims: “Attending an all-girls school improves girls’ math scores” and “attending an affluent all-girls school improves girls’ math scores.” These claims not only differ in what they suggest about how test scores are distributed across different types of schools (i.e., “the data”), but also have the potential to communicate something about the speakers’ values: namely, the prominence they accord to affluence in representing and making decisions about the social world. Here, we examine the relationship between the level of granularity with which a cause is described in a generic causal claim (e.g., all-girls school vs. affluent all-girls school) and the value of the information contained in the causal model that generates that claim. We argue that listeners who know any two of the following can make reliable inferences about the third: 1) the level of granularity at which a speaker makes a generic causal claim, 2) the speaker’s decision-theoretic values, and 3) the data available to the speaker. We present results of three experiments in the domain of social categories (N=853) that provide evidence in keeping with these predictions.