How good is an explanation?

David H. Glass

doi:10.1007/s11229-022-04025-x

How good is an explanation?

David H. Glass

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

70 Downloads (Pure)

Abstract

How good is an explanation and when is one explanation better than another? In this paper, I address these questions by exploring probabilistic measures of explanatory power in order to defend a particular Bayesian account of explanatory goodness. Critical to this discussion is a distinction between weak and strong measures of explanatory power due to Good (Br J Philos Sci 19:123–143, 1968). In particular, I argue that if one is interested in the overall goodness of an explanation, an appropriate balance needs to be struck between the weak explanatory power and the complexity of a hypothesis. In light of this, I provide a new defence of a strong measure proposed by Good by providing new derivations of it, comparing it with other measures and exploring its connection with information, confirmation and explanatory virtues. Furthermore, Good really presented a family of strong measures, whereas I draw on a complexity criterion that favours a specific measure and hence provides a more precise way to quantify explanatory goodness.

Original language	English
Article number	53
Pages (from-to)	1-26
Number of pages	27
Journal	Synthese
Volume	201
Issue number	2
Early online date	2 Feb 2023
DOIs	https://doi.org/10.1007/s11229-022-04025-x
Publication status	Published online - 2 Feb 2023

Bibliographical note

Funding Information:
I would like to thank participants at the conference on ‘Scientific Explanations, Competing and Conjunctive’ at the University of Utah in June 2019 for helpful discussions and Jonah Schupbach for very insightful comments on an earlier draft. I would also like to thank anonymous reviewers for their comments and suggestions. This publication was made possible through the support of a grant from the John Templeton Foundation (Grant No. 61115). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation.

Funding Information:
I would like to thank participants at the conference on ‘Scientific Explanations, Competing and Conjunctive’ at the University of Utah in June 2019 for helpful discussions and Jonah Schupbach for very insightful comments on an earlier draft. I would also like to thank anonymous reviewers for their comments and suggestions. This publication was made possible through the support of a grant from the John Templeton Foundation (Grant No. 61115). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation.

Publisher Copyright:
© 2023, The Author(s).

Funding

Funding Information: I would like to thank participants at the conference on ‘Scientific Explanations, Competing and Conjunctive’ at the University of Utah in June 2019 for helpful discussions and Jonah Schupbach for very insightful comments on an earlier draft. I would also like to thank anonymous reviewers for their comments and suggestions. This publication was made possible through the support of a grant from the John Templeton Foundation (Grant No. 61115). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. Funding Information: I would like to thank participants at the conference on ‘Scientific Explanations, Competing and Conjunctive’ at the University of Utah in June 2019 for helpful discussions and Jonah Schupbach for very insightful comments on an earlier draft. I would also like to thank anonymous reviewers for their comments and suggestions. This publication was made possible through the support of a grant from the John Templeton Foundation (Grant No. 61115). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. Publisher Copyright: © 2023, The Author(s).

Keywords

Original Research
Explanation
Explanatory goodness
Explanatory power
Bayesian
Information
Confirmation

Access to Document

10.1007/s11229-022-04025-x

11229_2022_Article_4025.pdfFinal published version, 431 KBLicence: CC BY

Cite this

@article{2b3be8dd05bc47e4a4219696bb587aad,

title = "How good is an explanation?",

abstract = "How good is an explanation and when is one explanation better than another? In this paper, I address these questions by exploring probabilistic measures of explanatory power in order to defend a particular Bayesian account of explanatory goodness. Critical to this discussion is a distinction between weak and strong measures of explanatory power due to Good (Br J Philos Sci 19:123–143, 1968). In particular, I argue that if one is interested in the overall goodness of an explanation, an appropriate balance needs to be struck between the weak explanatory power and the complexity of a hypothesis. In light of this, I provide a new defence of a strong measure proposed by Good by providing new derivations of it, comparing it with other measures and exploring its connection with information, confirmation and explanatory virtues. Furthermore, Good really presented a family of strong measures, whereas I draw on a complexity criterion that favours a specific measure and hence provides a more precise way to quantify explanatory goodness.",

keywords = "Original Research, Explanation, Explanatory goodness, Explanatory power, Bayesian, Information, Confirmation",

author = "Glass, \{David H.\}",

note = "Funding Information: I would like to thank participants at the conference on {\textquoteleft}Scientific Explanations, Competing and Conjunctive{\textquoteright} at the University of Utah in June 2019 for helpful discussions and Jonah Schupbach for very insightful comments on an earlier draft. I would also like to thank anonymous reviewers for their comments and suggestions. This publication was made possible through the support of a grant from the John Templeton Foundation (Grant No. 61115). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. Funding Information: I would like to thank participants at the conference on {\textquoteleft}Scientific Explanations, Competing and Conjunctive{\textquoteright} at the University of Utah in June 2019 for helpful discussions and Jonah Schupbach for very insightful comments on an earlier draft. I would also like to thank anonymous reviewers for their comments and suggestions. This publication was made possible through the support of a grant from the John Templeton Foundation (Grant No. 61115). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2023",

month = feb,

day = "2",

doi = "10.1007/s11229-022-04025-x",

language = "English",

volume = "201",

pages = "1--26",

journal = "Synthese",

issn = "0039-7857",