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An Objective Justification of Bayesianism II: The Consequences of Minimizing Inaccuracy

Published online by Cambridge University Press:  01 January 2022

Hannes Leitgeb  and
Richard Pettigrew
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Abstract

In this article and its prequel, we derive Bayesianism from the following norm: Accuracy—an agent ought to minimize the inaccuracy of her partial beliefs. In the prequel, we make the norm mathematically precise; in this article, we derive its consequences. We show that the two core tenets of Bayesianism follow from Accuracy, while the characteristic claim of Objective Bayesianism follows from Accuracy together with an extra assumption. Finally, we show that Jeffrey Conditionalization violates Accuracy unless Rigidity is assumed, and we describe the alternative updating rule that Accuracy mandates in the absence of Rigidity.

Type
Research Article
Information
Philosophy of Science , Volume 77 , Issue 2 , April 2010 , pp. 236 - 272
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

‡

We would like to thank F. Arntzenius, L. Bayón, R. Bradley, F. Dietrich, K. Easwaran, D. Edgington, B. Fitelson (and his Berkeley reading group), A. Hájek, L. Horsten, F. Huber, J. Joyce, W. Myrvold, S. Okasha, G. Schurz, T. Seidenfeld, B. Skyrms, C. Wagner, R. Williams, J. Williamson, and B. van Fraassen for their comments on earlier versions of this article. Hannes Leitgeb would like to thank the Leverhulme Trust and the Alexander von Humboldt Foundation for their generous support of this work. Richard Pettigrew would like to thank the British Academy with whom he was a postdoctoral fellow during work on this article.

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