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Against Probabilistic Measures of Explanatory Quality

Published online by Cambridge University Press:  10 February 2022

Marc Lange
Marc Lange*
Affiliation:
Department of Philosophy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, US. Email: mlange@email.unc.edu
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Abstract

Several philosophers propose probabilistic measures of how well a potential scientific explanation would explain the given evidence. These measures could elaborate “best” in “inference to the best explanation”. This paper argues that none of these measures (and no other measure built exclusively from such probabilities) succeeds. The paper considers the various rival explanations that scientists proposed for the parallelogram of forces. Scientists regarded various features of these proposals as making them more or less “lovely” (in Lipton’s sense). None of these probabilistic measures of loveliness can reflect these features. The paper concludes by considering the kinds of probabilities that could reflect these features.

Type
Article
Information
Philosophy of Science , Volume 89 , Issue 2 , April 2022 , pp. 252 - 267
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the Philosophy of Science Association

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