Comparing Probabilistic Measures of Explanatory Power

Philosophy of Science 78 (5):813-829 (2011)
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Abstract

Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the degree to which a hypothesis explains a given set of facts. These candidate measures of "explanatory power" are shown to 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 discuss some interesting implications of this result for both the epistemology and the psychology of explanatory reasoning.

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Jonah N. Schupbach
University of Utah

Citations of this work

Robustness Analysis as Explanatory Reasoning.Jonah N. Schupbach - 2018 - British Journal for the Philosophy of Science 69 (1):275-300.
The Logic of Explanatory Power.Jonah N. Schupbach & Jan Sprenger - 2011 - Philosophy of Science 78 (1):105-127.
Inference to the Best Explanation Made Incoherent.Nevin Climenhaga - 2017 - Journal of Philosophy 114 (5):251-273.

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References found in this work

Inference to the Best Explanation.Peter Lipton - 1991 - London and New York: Routledge/Taylor and Francis Group.
Inference to the Best Explanation.Peter Lipton - 1991 - London and New York: Routledge.
The Logic of Scientific Discovery.Karl Popper - 1959 - Studia Logica 9:262-265.
The Logic of Scientific Discovery.K. Popper - 1959 - British Journal for the Philosophy of Science 10 (37):55-57.
Précis of Inference to the Best Explanation, 2 nd Edition.Peter Lipton - 2007 - Philosophy and Phenomenological Research 74 (2):421-423.

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