Optimality explanations: a plea for an alternative approach

Biology and Philosophy 27 (5):685-703 (2012)
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Abstract

Recently philosophers of science have begun to pay more attention to the use of highly idealized mathematical models in scientific theorizing. An important example of this kind of highly idealized modeling is the widespread use of optimality models within evolutionary biology. One way to understand the explanations provided by these models is as a censored causal explanation: an explanation that omits certain causal factors in order to focus on a modular subset of the causal processes that led to the explanandum. In this paper, I first argue that the censored causal model approach fails to establish a permanent explanatory role for optimality models in biology and mischaracterizes the explanatory virtues of biological optimality modeling. In addition, I argue that many biological optimality explanations cannot be characterized as censored causal explanations. In response, I propose an alternative approach that analyzes optimality models’ reliance on synchronically representing a system’s constraints and tradeoffs as well as their employment of various kinds of idealization in order to provide equilibrium explanations.

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2012-05-21

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Collin Rice
Colorado State University

Citations of this work

Minimal Model Explanations.Robert W. Batterman & Collin C. Rice - 2014 - Philosophy of Science 81 (3):349-376.
Models Don’t Decompose That Way: A Holistic View of Idealized Models.Collin Rice - 2019 - British Journal for the Philosophy of Science 70 (1):179-208.
Explanation in Computational Neuroscience: Causal and Non-causal.M. Chirimuuta - 2018 - British Journal for the Philosophy of Science 69 (3):849-880.

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References found in this work

Depth: An Account of Scientific Explanation.Michael Strevens - 2008 - Cambridge: Harvard University Press.
Explanatory unification.Philip Kitcher - 1981 - Philosophy of Science 48 (4):507-531.
Causal explanation.David Lewis - 1986 - In Philosophical Papers, Volume II. New York, US: OUP Usa. pp. 214-240.

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