Counterfactuals, Models, and Scientific Realism

In Emiliano Ippoliti, Lorenzo Magnani & Selene Arfini, Model-Based Reasoning, Abductive Cognition, Creativity. Cham: Springer. pp. 89-116 (2024)
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Abstract

Counterfactuals abound in science, especially when one deals with models. Some models, namely highly idealized models, have assumptions that are metaphysically impossible. This means that in science one has often to deal with counterpossibles. According to the standard semantics for counterfactuals, all counterpossibles are vacuously true. But scientific practice shows that counterpossibles are not always regarded as vacuously true by scientists. To do justice of the use of counterpossibles in science, some authors think that we should adopt a semantics that allows for impossible worlds. It seems difficult to reconcile the role played by highly idealized models in science with scientific realism. Nevertheless, some authors think that it is possible to provide a realist account of highly idealized models. In this view, scientific realism should not be interpreted as the claim that models aim to provide accurate representations of models’ targets, rather it should be interpreted as the claim that models aim to provide true modal information about models’ targets. This variant of scientific realism seems to imply a commitment to some form of modal realism. I develop an objection to that variant of scientific realism by elaborating on some arguments originally developed to show that there are unknowable facts.

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Fabio Sterpetti
Università degli Studi di Roma La Sapienza

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References found in this work

On the Plurality of Worlds.David K. Lewis - 1986 - Malden, Mass.: Wiley-Blackwell.
A Theory of Conditionals.Robert Stalnaker - 1968 - In Nicholas Rescher, Studies in Logical Theory. Oxford,: Blackwell. pp. 98-112.
On Computable Numbers, with an Application to the Entscheidungsproblem.Alan Turing - 1936 - Proceedings of the London Mathematical Society 42 (1):230-265.
Impossible Worlds.Francesco Berto & Mark Jago - 2019 - Oxford: Oxford University Press. Edited by Mark Jago.

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