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Accuracy, conditionalization, and probabilism

Lewis, Peter J. and Fallis, Don (2019) Accuracy, conditionalization, and probabilism. [Preprint]

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Accuracy-based arguments for conditionalization and probabilism appear to have a significant advantage over their Dutch Book rivals. They rely only on the plausible epistemic norm that one should try to decrease the inaccuracy of one's beliefs. Furthermore, conditionalization and probabilism apparently follow from a wide range of measures of inaccuracy. However, we argue that there is an under-appreciated diachronic constraint on measures of inaccuracy which limits the measures from which one can prove conditionalization, and none of the remaining measures allow one to prove probabilism. That is, among the measures in the literature, there are some from which one can prove conditionalization, others from which one can prove probabilism, but none from which one can prove both. Hence at present, the accuracy-based approach cannot underwrite both conditionalization and probabilism.

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Item Type: Preprint
Lewis, Peter
Keywords: Accuracy, probabilism, conditionalization, epistemic utility, scoring rules
Subjects: General Issues > Decision Theory
Depositing User: Peter J. Lewis
Date Deposited: 24 Mar 2020 01:28
Last Modified: 24 Mar 2020 01:28
Item ID: 16137
Subjects: General Issues > Decision Theory
Date: 15 June 2019

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