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Revisiting abstraction and idealization: How not to criticize mechanistic explanation in molecular biology

Zach, Martin (2022) Revisiting abstraction and idealization: How not to criticize mechanistic explanation in molecular biology. [Preprint]

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Abstract

Abstraction and idealization are the two notions that are most often discussed in the context of assumptions employed in the process of model building. These notions are also routinely used in philosophical debates such as that on the mechanistic account of explanation. Indeed, an objection to the mechanistic account has recently been formulated precisely on these grounds: mechanists cannot account for the common practice of idealizing difference-making factors in models in molecular biology. In this paper I revisit the debate and I argue that the objection does not stand up to scrutiny. This is because it is riddled with a number of conceptual inconsistencies. By attempting to resolve the tensions, I also draw several general lessons regarding the difficulties of applying abstraction and idealization in scientific practice. Finally, I argue that more care is needed only when speaking of abstraction and idealization in a context in which these concepts play an important role in an argument, such as that on mechanistic explanation.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Zach, Martinzach@flu.cas.cz0000-0001-7181-0391
Additional Information: Forthcoming in the European Journal for Philosophy of Science
Keywords: abstraction; idealization; mechanistic explanation; molecular biology; scientific models
Subjects: Specific Sciences > Biology
Specific Sciences > Biology > Molecular Biology/Genetics
General Issues > Models and Idealization
General Issues > Philosophers of Science
Depositing User: Dr. Martin Zach
Date Deposited: 12 Feb 2022 22:47
Last Modified: 12 Feb 2022 22:47
Item ID: 20219
Subjects: Specific Sciences > Biology
Specific Sciences > Biology > Molecular Biology/Genetics
General Issues > Models and Idealization
General Issues > Philosophers of Science
Date: 2022
URI: http://philsci-archive.pitt.edu/id/eprint/20219

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