Hostname: page-component-745bb68f8f-g4j75 Total loading time: 0 Render date: 2025-01-25T06:52:48.879Z Has data issue: false hasContentIssue false
  • English
  • Français

A NEW EPISTEMIC UTILITY ARGUMENT FOR THE PRINCIPAL PRINCIPLE*

Published online by Cambridge University Press:  25 March 2013

Richard Pettigrew
Get access Rights & Permissions [Opens in a new window]

Abstract

Jim Joyce has presented an argument for Probabilism based on considerations of epistemic utility. In a recent paper, I adapted this argument to give an argument for Probablism and the Principal Principle based on similar considerations. Joyce's argument assumes that a credence in a true proposition is better the closer it is to maximal credence, whilst a credence in a false proposition is better the closer it is to minimal credence. By contrast, my argument in that paper assumed (roughly) that a credence in a proposition is better the closer it is to the objective chance of that proposition. In this paper, I present an epistemic utility argument for Probabilism and the Principal Principle that retains Joyce's assumption rather than the alternative I endorsed in the earlier paper. I argue that this results in a superior argument for these norms.

Type
Articles
Information
Episteme , Volume 10 , Issue 1 , March 2013 , pp. 19 - 35
Copyright
Copyright © Cambridge University Press 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

I would like to thank Rachael Briggs, Kenny Easwaran, Branden Fitelson, Alan Hájek, Katie Steele, Jonathan Weisberg, and other participants in the Fourth Formal Epistemology Festival held in Konstanz in June 2012. Their questions and comments improved this paper greatly.

References

REFERENCES

Banerjee, A., Meruga, S., Dhillon, I. S., and Ghosh, J. 2005. ‘Clustering with Bregman Divergences.’ Journal of Machine Learning Research, 6: 1705–49.Google Scholar
de Finetti, B. 1974. Theory of Probability, vol. 1. New York: Wiley.Google Scholar
Hall, N. 1994. ‘Correcting the Guide to Objective Chance.’ Mind, 103: 505–18.CrossRefGoogle Scholar
Hall, N. 2004. ‘Two Mistakes about Credence and Chance.’ Australasian Journal of Philosophy, 82(1): 93–111.Google Scholar
Hempel, C. G. 1962. ‘Deductive-Nomological vs Statistical Explanation.’ In Feigl, H. and Maxwell, G. (eds), Minnesota Studies in the Philosophy of Science, vol. 3, pp. 98–169. Minneapolis: University of MinnesotaPress.Google Scholar
Ismael, J. 2008. ‘Raid! Dissolving the Big, Bad Bug.’ Noûs, 42(2): 292–307.Google Scholar
Joyce, J. M. 1998. ‘A Nonpragmatic Vindication of Probabilism.’ Philosophy of Science, 65(4): 575–603.Google Scholar
Kaplan, M. 1995. ‘Believing the Improbable.’ Philosophical Studies, 77(1): 117–46.CrossRefGoogle Scholar
Leitgeb, H. and Pettigrew, R. 2010. ‘An Objective Justification of Bayesianism I: Measuring Inaccuracy.’ Philosophy of Science, 77:201–235.CrossRefGoogle Scholar
Lewis, D. 1980. ‘A Subjectivist's Guide to Objective Chance.’ In Jeffrey, R. C. (ed.), Studies in Inductive Logic and Probability, vol. 2. Berkeley, CA: University of California Press.Google Scholar
Lewis, D. 1994. ‘Humean Supervenience Debugged.’ Mind, 103: 473–90.Google Scholar
Pettigrew, R. 2012. ‘Accuracy, Chance, and the Principal Principle.’ Philosophical Review, 121(2): 241–75.Google Scholar
Predd, J., Seiringer, R., Lieb, E. H., Osherson, D., Poor, V., and Kulkarni, S. 2009. ‘Probabilistic Coherence and Proper Scoring Rules.’ IEEE Transactions on Information Theory, 55(10): 4786–92.CrossRefGoogle Scholar
Savage, L. J. 1971. ‘Elicitation of Personal Probabilities and Expectations.’ Journal of the American Statistical Association, 66(336): 783–801.Google Scholar
Selten, R. 1998. ‘Axiomatic Characterization of the Quadratic Scoring Rule.’ Experimental Economics, 1(1): 43–61.Google Scholar