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Comparing Probabilistic Measures of Explanatory Power

Published online by Cambridge University Press:  01 January 2022

Abstract

Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the strength of a potential explanation. These candidate measures of “explanatory power” arguably have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people's actual explanatory judgments. Here I present my own experimental work investigating this question. I argue that one measure in particular is an accurate descriptor of explanatory judgments. Then I briefly point to some implications of this result for the epistemology and the psychology of explanatory reasoning.

Type
Research Article
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

Thanks to David Danks, John Earman, David Glass, Edouard Machery, and Jan Sprenger for helpful conversation and criticism pertaining to this research. John Earman and Edouard Machery very graciously helped to finance this project; for that, I am especially grateful. Research for this article was also supported by a grant from the Wesley Salmon Fund, offered through the University of Pittsburgh.

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