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
University of Bristol

Citations of this work

Accuracy-First Epistemology Without Additivity.Richard Pettigrew - 2022 - Philosophy of Science 89 (1):128-151.
Rational Aversion to Information.Sven Neth - forthcoming - British Journal for the Philosophy of Science.
Learning from experience and conditionalization.Peter Brössel - 2023 - Philosophical Studies 180 (9):2797-2823.
Bayesian Epistemology.William Talbott - 2006 - Stanford Encyclopedia of Philosophy.
Opaque Updates.Michael Cohen - 2020 - Journal of Philosophical Logic 50 (3):447-470.

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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 - New York: Oxford University Press.
Accuracy and the Laws of Credence.Richard Pettigrew - 2016 - New York, NY.: Oxford University Press UK.
The Foundations of Statistics.Leonard J. Savage - 1956 - Philosophy of Science 23 (2):166-166.

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