Abstract
This paper provides an inferentialist account of model-based understanding by combining a counterfactual account of explanation and an inferentialist account of representation with a view of modeling as extended cognition. This account makes it understandable how the manipulation of surrogate systems like models can provide genuinely new empirical understanding about the world. Similarly, the account provides an answer to the question how models, that always incorporate assumptions that are literally untrue of the model target, can still provide factive explanations. Finally, the paper shows how the contrastive counterfactual theory of explanation can provide tools for assessing the explanatory power of models.
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Notes
This should not be taken as a stance in the ontology of models discussion. We do not deny that it makes sense to abstract away from the concrete instantiations of these artifacts to their inferential properties and define the identity in these terms (see Kuorikoski and Lehtinen 2009).
Although realist, our view is therefore not ontic in the sense of equating explanations and explanatory factors. Indeed, it would be rather strange to insist that causes and mechanisms would somehow do the explaining by themselves. As has been noted in the literature, little of substance depends on this metaphysical (or more likely grammatical) issue alone (Illari 2013).
The checkerboard model is perhaps also the most used stock example in the philosophy of social science literature, and worries have been raised that using it repeatedly may have created biases in philosophical views. Granted, the checkerboard model might not be representative of economic and sociological models in general. However, as the model has been heralded as an example of a good explanation in social sciences (Sugden 2000; Hedström and Ylikoski 2010), it must embody at least some of the key virtues that social scientists expect their theoretical models to have. Secondly, and more importantly, in the present context it just provides a simple and well-known example to illustrate our points about using external representations in science. Nothing in our argument depends on the choice of this specific example.
Suárez (2003) presents arguments based on the variety of ways of representation, the logical properties of the representation relation, the necessity of accounting for misrepresentation, and nonsufficiency and nonnecessity arguments, to persuasively discredit proposed philosophical accounts of “the” representation relation between scientific models and their targets.
In this sense, the representational properties of a model are still defined in relation (and in this sense “subjective”) to the cognitive agent using the model. However, there is nothing subjective or relative about the correctness, range, and reliability of the inferences carried out by the extended cognitive system.
There remains the logical possibility that a model originally not intended to represent a specific system or one built using unsound epistemic principles could reliably facilitate correct counterfactual inferences by purely accident. We do not know of any cases of such accidental representational success,
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Acknowledgments
This paper is based on a presentation given in a Workshop on Explanatory Power at Ruhr University Bochum in 2012, and presented in the Philosophy of Science Seminar at the University of Helsinki in 2013. We thank the audiences of these events, as well as the reviewers, for their valuable comments.
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Kuorikoski, J., Ylikoski, P. External representations and scientific understanding. Synthese 192, 3817–3837 (2015). https://doi.org/10.1007/s11229-014-0591-2
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DOI: https://doi.org/10.1007/s11229-014-0591-2