Accuracy, conditionalization, and probabilism

Synthese 198 (5):4017-4033 (2019)
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Abstract

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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Author Profiles

Peter J. Lewis
Dartmouth College
Don Fallis
Northeastern University

Citations of this work

When the (Bayesian) ideal is not ideal.Danilo Fraga Dantas - 2023 - Logos and Episteme 15 (3):271-298.

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