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  1. Infinite Opinion Sets and Relative Accuracy.Ilho Park & Jaemin Jung - 2023 - Journal of Philosophy 120 (6):285-313.
    We can have credences in an infinite number of propositions—that is, our opinion set can be infinite. Accuracy-first epistemologists have devoted themselves to evaluating credal states with the help of the concept of ‘accuracy’. Unfortunately, under several innocuous assumptions, infinite opinion sets yield several undesirable results, some of which are even fatal, to accuracy-first epistemology. Moreover, accuracy-first epistemologists cannot circumvent these difficulties in any standard way. In this regard, we will suggest a non-standard approach, called a relativistic approach, to accuracy-first (...)
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  • Accuracy and infinity: a dilemma for subjective Bayesians.Mikayla Kelley & Sven Neth - 2023 - Synthese 201 (12):1-14.
    We argue that subjective Bayesians face a dilemma: they must offend against the spirit of their permissivism about rational credence or reject the principle that one should avoid accuracy dominance.
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  • Can Arbitrary Beliefs be Rational?Mattias Skipper - 2023 - Episteme 20 (2):377-392.
    When a belief has been influenced, in part or whole, by factors that, by the believer's own lights, do not bear on the truth of the believed proposition, we can say that the belief has been, in a sense, arbitrarily formed. Can such beliefs ever be rational? It might seem obvious that they can't. After all, belief, supposedly, “aims at the truth.” But many epistemologists have come to think that certain kinds of arbitrary beliefs can, indeed, be rational. In this (...)
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  • On the Best Accuracy Arguments for Probabilism.Michael Nielsen - 2022 - Philosophy of Science 89 (3):621-630.
    In a recent paper, Pettigrew reports a generalization of the celebrated accuracy-dominance theorem due to Predd et al., but Pettigrew’s proof is incorrect. I will explain the mistakes and provide a correct proof.
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  • Necessary and Sufficient Conditions for Domination Results for Proper Scoring Rules.Alexander R. Pruss - 2024 - Review of Symbolic Logic 17 (1):132-143.
    Scoring rules measure the deviation between a forecast, which assigns degrees of confidence to various events, and reality. Strictly proper scoring rules have the property that for any forecast, the mathematical expectation of the score of a forecast p by the lights of p is strictly better than the mathematical expectation of any other forecast q by the lights of p. Forecasts need not satisfy the axioms of the probability calculus, but Predd et al. [9] have shown that given a (...)
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  • Accuracy and Probabilism in Infinite Domains.Michael Nielsen - 2023 - Mind 132 (526):402-427.
    The best accuracy arguments for probabilism apply only to credence functions with finite domains, that is, credence functions that assign credence to at most finitely many propositions. This is a significant limitation. It reveals that the support for the accuracy-first program in epistemology is a lot weaker than it seems at first glance, and it means that accuracy arguments cannot yet accomplish everything that their competitors, the pragmatic (Dutch book) arguments, can. In this paper, I investigate the extent to which (...)
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  • Accuracy, probabilism and Bayesian update in infinite domains.Alexander R. Pruss - 2022 - Synthese 200 (6):1-29.
    Scoring rules measure the accuracy or epistemic utility of a credence assignment. A significant literature uses plausible conditions on scoring rules on finite sample spaces to argue for both probabilism—the doctrine that credences ought to satisfy the axioms of probabilism—and for the optimality of Bayesian update as a response to evidence. I prove a number of formal results regarding scoring rules on infinite sample spaces that impact the extension of these arguments to infinite sample spaces. A common condition in the (...)
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