 Tessler and Goodman’s model does a remarkable job of predicting the degree to which people endorse a given generic with great quantitative accuracy, and it extends a growing body of evidence in cognitive science that much of human cognition, including early cognitive development, involves or approximates to Bayesian inference (e.g., for a recent review, see Ullman and Tenenbaum 2020). While their model predicts that prior beliefs about the distribution of the prevalence of the property over comparable kinds mediates all endorsement/rejection of generics, they allow that these priors may be influenced by content-based factors. For example, “mosquitoes carry West Nile virus” is predicted to be accepted with a high degree of confidence by the model because the prevalence prior for carrying West Nile virus is almost entirely bunched up very close to zero, and correspondingly the prevalence posterior upon hearing the generic shifts modestly over to low but decidedly non-zero values. If people have a higher order prior expectation that strikingly dangerous properties are rare, such that the prevalence priors for such properties resemble that of carrying West Nile virus, then this would mean that people would be disposed to accept generics that predicate such properties, even though the referent prevalence is low.