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Scientific Representation: An Inferentialist-Expressivist Manifesto

Khalifa, Kareem and Millson, Jared and Risjord, Mark (2022) Scientific Representation: An Inferentialist-Expressivist Manifesto. [Preprint]

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Abstract

This essay presents a fully inferentialist-expressivist account of scientific representation. In general, inferentialist approaches to scientific representation argue that the capacity of a model to represent a target system depends on inferences from models to target systems (surrogative inference). Inferentialism is attractive because it makes the epistemic function of models central to their representational capacity. Prior inferentialist approaches to scientific representation, however, have depended on some representational element, such as denotation or representational force. Brandom’s Making It Explicit provides a model of how to fully discharge such representational vocabulary, but it cannot be applied directly to scientific representations. Pursuing a strategy parallel to Brandom’s, this essay begins with an account of how surrogative inference is justified. Scientific representation and the denotation of model elements are then explained in terms of surrogative inference by treating scientific representation and denotation as expressive, analogous to Brandom’s account of truth. The result is a thoroughgoing inferentialism: M is a scientific representation of T if and only if M has scientifically justified surrogative consequences that are answers to questions about T.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Khalifa, Kareemkkhalifa@middlebury.edu
Millson, Jaredmillsonj@rhodes.edu
Risjord, Markmrisjor@emory.edu
Keywords: scientific representation, surrogative inference, scientific models, denotation
Subjects: General Issues > Models and Idealization
Depositing User: Dr. Kareem Khalifa
Date Deposited: 27 Oct 2022 15:48
Last Modified: 27 Oct 2022 15:48
Item ID: 21321
Official URL: https://www.jstor.org/stable/48681556
DOI or Unique Handle: 10.5840/philtopics202250112
Subjects: General Issues > Models and Idealization
Date: 2022
URI: https://philsci-archive.pitt.edu/id/eprint/21321

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