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Studies in the Logic of Explanatory Power

Schupbach, Jonah N. (2011) Studies in the Logic of Explanatory Power. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Human reasoning often involves explanation. In everyday affairs, people reason to hypotheses based on the explanatory power these hypotheses afford; I might, for example, surmise that my toddler has been playing in my office because I judge that this hypothesis delivers a good explanation of the disarranged state of the books on my shelves. But such explanatory reasoning also has relevance far beyond the commonplace. Indeed, explanatory reasoning plays an important role in such varied fields as the sciences, philosophy, theology, medicine, forensics, and law.This dissertation provides an extended study into the logic of explanatory reasoning via two general questions. First, I approach the question of what exactly we have in mind when we make judgments pertaining to the explanatory power that a hypothesis has over some evidence. This question is important to this study because these are the sorts of judgments that we constantly rely on when we use explanations to reason about the world. Ultimately, I introduce and defend an explication of the concept of explanatory power in the form of a probabilistic measure. This formal explication allows us to articulate precisely some of the various ways in which we might reason explanatorily.The second question this dissertation examines is whether explanatory reasoning constitutes an epistemically respectable means of gaining knowledge. I defend the following ideas: The probability theory can be used to describe the logic of explanatory reasoning, the normative standard to which such reasoning attains. Explanatory judgments, on the other hand, constitute heuristics that allow us to approximate reasoning in accordance with this logical standard while staying within our human bounds. The most well known model of explanatory reasoning, Inference to the Best Explanation, describes a cogent, nondeductive inference form. And reasoning by Inference to the Best Explanation approximates reasoning directly via the probability theory in the real world. Finally, I respond to some possible objections to my work, and then to some more general, classic criticisms of Inference to the Best Explanation. In the end, this dissertation puts forward a clearer articulation and novel defense of explanatory reasoning.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Schupbach, Jonah N.jns24@pitt.eduJNS24
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee CoChairMachery, Edouardmachery@pitt.eduMACHERY
Committee CoChairEarman, Johnjearman@pitt.eduJEARMAN
Committee MemberDanks,
Committee MemberNorton, Johnjdnorton@pitt.eduJDNORTON
Committee MemberHartmann,
Date: 30 September 2011
Date Type: Completion
Defense Date: 14 June 2011
Approval Date: 30 September 2011
Submission Date: 15 May 2011
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > History and Philosophy of Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: abduction; Bayesian explanationism; Bayesianism; bounded rationality; Carnap; epistemology; explanation; explanatory power; explanatory reasoning; explication; formal epistemology; formal methods; formal philosophy; heuristics; human reasoning; inductive logic; Inference to the Best Explanation; Peirce; probability theory
Other ID:, etd-05152011-215555
Date Deposited: 10 Nov 2011 19:44
Last Modified: 15 Nov 2016 13:43


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