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Idealized models as inferentially veridical representations : a conceptual framework

In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. Routledge (2011)

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  1. Models, Idealisations, and Realism.Juha Saatsi - 2016 - In Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.), Models and Inferences in Science. Cham: Springer.
    I explore a challenge that idealisations pose to scientific realism and argue that the realist can best accommodate idealisations by capitalising on certain modal features of idealised models that are underwritten by laws of nature.
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  • Inconsistency and scientific realism.Juha Saatsi - 2014 - Synthese 191 (13):2941-2955.
    I erect a framework within the semantic view of theories for explaining the empirical success of internally inconsistent models and theories, with scientific realism in mind. The framework is an instance of the ‘content-driven’ approach to inconsistency, advocated by both Norton (Philos Sci 54:327–350, 1987) and Smith (Stud Hist Philos Sci 19:429–445, 1988a, In: Fine A, Leplin J (eds) PSA1988, 1988b), whose ideas my analysis aims to clarify and substantiate.
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  • A Defense of Truth as a Necessary Condition on Scientific Explanation.Christopher Pincock - 2021 - Erkenntnis 88 (2):621-640.
    How can a reflective scientist put forward an explanation using a model when they are aware that many of the assumptions used to specify that model are false? This paper addresses this challenge by making two substantial assumptions about explanatory practice. First, many of the propositions deployed in the course of explaining have a non-representational function. In particular, a proposition that a scientist uses and also believes to be false, i.e. an “idealization”, typically has some non-representational function in the practice, (...)
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