In her wide-ranging book, Probabilistic Knowledge, Sarah Moss presents a unified account of probabilistic content in theories of belief, assertion, and knowledge. The first part (chaps. 1–2.3) begins by arguing for a particular way of incorporating credence into an extant picture of belief—that is, by analyzing credence as a relation between an agent and a probabilistic content. The second part (chaps. 2.4–4) moves on to language, with a focus on epistemic vocabulary, indicative conditionals, and logical connectives. The third (chaps. 5–10) turns to knowledge. Here, the central thesis is that all grades of Bayesian credence—traditionally considered as mere partial belief—can in fact constitute knowledge in many of its central epistemological roles. Additional chapters turn to applications, including action and decision (chap. 9) and the role of statistical evidence in the law (chap. 10).
In each case, the role played by individual possible worlds on standard theories—as well as some...
