What is conditionalization, and why should we do it?

Philosophical Studies 177 (11):3427-3463 (2020)
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Abstract

Conditionalization is one of the central norms of Bayesian epistemology. But there are a number of competing formulations, and a number of arguments that purport to establish it. In this paper, I explore which formulations of the norm are supported by which arguments. In their standard formulations, each of the arguments I consider here depends on the same assumption, which I call Deterministic Updating. I will investigate whether it is possible to amend these arguments so that they no longer depend on it. As I show, whether this is possible depends on the formulation of the norm under consideration.

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Richard Pettigrew
Bristol University

Citations of this work

Bayesian Epistemology.William Talbott - 2006 - Stanford Encyclopedia of Philosophy.
Best Laid Plans: Idealization and the Rationality–Accuracy Bridge.Brett Topey - forthcoming - British Journal for the Philosophy of Science.
Opaque Updates.Michael Cohen - 2021 - Journal of Philosophical Logic 50 (3):447-470.
Beyond linear conciliation.Ko-Hung Kuan - 2020 - Synthese 198 (12):11483-11504.

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References found in this work

The Foundations of Statistics.Leonard J. Savage - 1954 - Wiley Publications in Statistics.
Laws and Symmetry.Bas C. Van Fraassen - 1989 - Oxford, England: Oxford University Press.
Accuracy and the Laws of Credence.Richard Pettigrew - 2016 - Oxford University Press UK.
The Foundations of Statistics.Leonard J. Savage - 1956 - Philosophy of Science 23 (2):166-166.

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