Understanding (With) Toy Models

British Journal for the Philosophy of Science:axx005 (2016)
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Abstract

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models is that it is an unsettled question what the epistemic goal of toy modeling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this paper is to precisely articulate and to defend this claim. In particular, we will distinguish between autonomous and embedded toy models, and, then, argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied.

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Author Profiles

Stephan Hartmann
Ludwig Maximilians Universität, München
Alexander Reutlinger
Ludwig Maximilians Universität, München

Citations of this work

Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
Robustness and Idealizations in Agent-Based Models of Scientific Interaction.Daniel Frey & Dunja Šešelja - 2019 - British Journal for the Philosophy of Science 71 (4):1411-1437.
Idealizations and Understanding: Much Ado About Nothing?Emily Sullivan & Kareem Khalifa - 2019 - Australasian Journal of Philosophy 97 (4):673-689.

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References found in this work

How the laws of physics lie.Nancy Cartwright - 1983 - New York: Oxford University Press.
Models in Science (2nd edition).Roman Frigg & Stephan Hartmann - 2021 - The Stanford Encyclopedia of Philosophy.
Depth: An Account of Scientific Explanation.Michael Strevens - 2008 - Cambridge, Mass.: Harvard University Press.

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