Ideal counterpart theorizing and the accuracy argument for probabilism

Analysis 78 (2):207-216 (2018)

Clinton Castro
Florida International University
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 and Pettigrew 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.
Keywords Accuracy first epistemology  Arguments for probabilism  Bayesian epistemology
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DOI 10.1093/analys/anx107
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References found in this work BETA

Accuracy and the Laws of Credence.Richard Pettigrew - 2016 - Oxford University Press UK.
A Nonpragmatic Vindication of Probabilism.James Joyce - 1998 - Philosophy of Science 65 (4):575-603.
Accuracy and Coherence: Prospects for an Alethic Epistemology of Partial Belief.James Joyce - 2009 - In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of Belief. Synthese. pp. 263-297.
Epistemic Utility Theory and the Aim of Belief.Jennifer Rose Carr - 2017 - Philosophy and Phenomenological Research 95 (3):511-534.
The Foundations of Statistics.Leonard J. Savage - 1954 - Philosophy of Science 23 (2):166-166.

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