Why We Cannot Learn from Minimal Models

Erkenntnis 81 (3):433-455 (2016)
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Abstract

Philosophers of science have developed several accounts of how consideration of scientific models can prompt learning about real-world targets. In recent years, various authors advocated the thesis that consideration of so-called minimal models can prompt learning about such targets. In this paper, I draw on the philosophical literature on scientific modelling and on widely cited illustrations from economics and biology to argue that this thesis fails to withstand scrutiny. More specifically, I criticize leading proponents of such thesis for failing to explicate in virtue of what properties or features minimal models supposedly prompt learning and for substantially overstating the epistemic import of minimal models. I then examine and refute several arguments one may put forward to demonstrate that consideration of minimal models can prompt learning about real-world targets. In doing so, I illustrate the implications of my critique for the wider debate on the epistemology of scientific modelling.

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Roberto Fumagalli
King's College London

Citations of this work

Model Pluralism.Walter Veit - 2019 - Philosophy of the Social Sciences 50 (2):91-114.
Understanding (with) Toy Models.Alexander Reutlinger, Dominik Hangleiter & Stephan Hartmann - 2018 - British Journal for the Philosophy of Science 69 (4):1069-1099.
Understanding (With) Toy Models.Alexander Reutlinger, Dominik Hangleiter & Stephan Hartmann - 2016 - British Journal for the Philosophy of Science:axx005.
It’s Not a Game: Accurate Representation with Toy Models.James Nguyen - 2020 - British Journal for the Philosophy of Science 71 (3):1013-1041.

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References found in this work

The Scientific Image.William Demopoulos & Bas C. van Fraassen - 1982 - Philosophical Review 91 (4):603.
Three Kinds of Idealization.Michael Weisberg - 2007 - Journal of Philosophy 104 (12):639-659.
How models are used to represent reality.Ronald N. Giere - 2004 - Philosophy of Science 71 (5):742-752.

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