The epistemic benefits of generalisation in modelling I: Systems and applicability

Synthese 199 (3-4):10343-10370 (2021)
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Abstract

This paper provides a conceptual framework that allows for distinguishing between different kinds of generalisation and applicability. It is argued that generalising models may bring epistemic benefits. They do so if they show that restrictive and unrealistic assumptions do not threaten the credibility of results derived from models. There are two different notions of applicability, generic and specific, which give rise to three different kinds of generalizations. Only generalising a result brings epistemic benefits concerning the truth of model components or results. Abstracting the model and applying the model into new systems are not intrinsically epistemically beneficial in this way. The Dixit-Stiglitz model of monopolistic competition is used as an illustration.

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Author's Profile

Aki Petteri Lehtinen
Nankai University

Citations of this work

Simulated Data in Empirical Science.Aki Lehtinen & Jani Raerinne - forthcoming - Foundations of Science:1-22.
Defending De-idealization in Economic Modeling: A Case Study.Edoardo Peruzzi & Gustavo Cevolani - 2021 - Sage Publications Inc: Philosophy of the Social Sciences 52 (1-2):25-52.
Defending De-idealization in Economic Modeling: A Case Study.Edoardo Peruzzi & Gustavo Cevolani - 2022 - Philosophy of the Social Sciences 52 (1-2):25-52.

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References found in this work

Depth: An Account of Scientific Explanation.Michael Strevens - 2008 - Cambridge, Mass.: Harvard University Press.
Idealization and the Aims of Science.Angela Potochnik - 2017 - Chicago: University of Chicago Press.
Explanatory unification and the causal structure of the world.Philip Kitcher - 1989 - In Philip Kitcher & Wesley Salmon (eds.), Scientific Explanation. Minneapolis: University of Minnesota Press. pp. 410-505.
The strategy of model-based science.Peter Godfrey-Smith - 2006 - Biology and Philosophy 21 (5):725-740.

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