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Understanding Science: Why Causes Are Not Enough

Published online by Cambridge University Press:  01 April 2022

Ruth Berger
Ruth Berger*
Affiliation:
Starr Litigation Services, inc
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Abstract

This paper is an empirical critique of causal accounts of scientific explanation. Drawing on explanations which rely on nonlinear dynamical modeling, I argue that the requirement of causal relevance is both too strong and too weak to be constitutive of scientific explanation. In addition, causal accounts obscure how the process of mathematical modeling produces explanatory information. I advance three arguments for the inadequacy of causal accounts. First, I argue that explanatorily relevant information is not always information about causes, even in cases where the explanandum has an identifiable causal history. Second, I argue that treating theoretical explanations as reductions from general causal laws does not accurately describe the types of “top-down” explanations typical of dynamical modeling. Finally, I argue that causal/mechanical accounts of explanation are intrinsically vulnerable to the irrelevance problem.

Type
Research Article
Information
Philosophy of Science , Volume 65 , Issue 2 , June 1998 , pp. 306 - 332
Copyright
Copyright © Philosophy of Science Association 1998

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Footnotes

†

Send reprint requests to the author, Starr Litigation Services, inc, 1201 Grand Avenue, West Des Moines, IA, 50265.

‡

I would like to thank Michael Friedman, Frederick Suppe, Noretta Koertge, James Townsend, and David McCarty for comments on earlier drafts of this paper. I would also like to thank William Kallfelz, Elinor Berger, and two anonymous reviewers for Philosophy of Science.

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