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Against Probabilistic Measures of Explanatory Quality

Lange, Marc (2020) Against Probabilistic Measures of Explanatory Quality. [Preprint]

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Several philosophers propose probabilistic measures of how well a potential scientific explanation would explain. 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.

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Item Type: Preprint
Keywords: explanation, inference to the best explanation, loveliness,
Subjects: General Issues > Explanation
Depositing User: Prof. Marc Lange
Date Deposited: 09 Feb 2022 03:22
Last Modified: 09 Feb 2022 03:22
Item ID: 20205
Subjects: General Issues > Explanation
Date: August 2020

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