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Instrumentalism, Parsimony, and the Akaike Framework

Published online by Cambridge University Press:  01 January 2022

Elliott Sober*
Affiliation:
University of Wisconsin and London School of Economics and Political Science
*
Send requests for reprints to the author, Department of Philosophy, University of Wisconsin, Madison, WI 53706; ersober@facstaff.wisc.edu.

Abstract

Akaike's framework for thinking about model selection in terms of the goal of predictive accuracy and his criterion for model selection have important philosophical implications. Scientists often test models whose truth values they already know, and they often decline to reject models that they know full well are false. Instrumentalism helps explain this pervasive feature of scientific practice, and Akaike's framework helps provide instrumentalism with the epistemology it needs. Akaike's criterion for model selection also throws light on the role of parsimony considerations in hypothesis evaluation. I explain the basic ideas behind Akaike's framework and criterion; several biological examples, including the use of maximum likelihood methods in phylogenetic inference, are considered.

Type
Research Article
Copyright
Copyright © The Philosophy of Science Association

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