One of the main goals of Bayesian epistemology is to justify the rational norms credence functions ought to obey. Accuracy arguments attempt to justify these norms from the assumption that the source of value for credences relevant to their epistemic status is their accuracy. This assumption and some standard decision-theoretic principles are used to argue for norms like Probabilism, the thesis that an agent's credence function is rational only if it obeys the probability axioms. We introduce an example that shows that the accuracy arguments for Probabilism given by Joyce (1998, 2009) and Pettigrew (2016) fail, and that Probabilism in fact turns out to be false given Pettigrew's way of conceiving of the goal of having accurate credences. Finally, we use our discussion of Pettigrew's framework to draw an important general lesson about normative theorizing that relies on the positing of ideal agents.
