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A Deductive-Nomological Model of Probabilistic Explanation

Published online by Cambridge University Press:  01 April 2022

Peter Railton*
Affiliation:
Princeton University

Abstract

It has been the dominant view that probabilistic explanations of particular facts must be inductive in character. I argue here that this view is mistaken, and that the aim of probabilistic explanation is not to demonstrate that the explanandum fact was nomically expectable, but to give an account of the chance mechanism(s) responsible for it. To this end, a deductive-nomological model of probabilistic explanation is developed and defended. Such a model has application only when the probabilities occurring in covering laws can be interpreted as measures of objective chance, expressing the strength of physical propensities. Unlike inductive models of probabilistic explanation, this deductive model stands in no need of troublesome requirements of maximal specificity or epistemic relativization.

Type
Research Article
Copyright
Copyright © Philosophy of Science Association 1978

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Footnotes

I would like to thank C. G. Hempel, Richard C. Jeffrey, and David Lewis for helpful criticisms of earlier drafts. I am especially indebted to David Lewis for the idea that a propensity interpretation of probability sits best with the account of probabilistic explanation given here. I have greatly benefited from discussions of related matters with Sam Scheffler and David Fair.

References

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