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Holistic Modeling—An Objection to Weisberg’s Weighted Feature-Matching Account

Fang, Wei (2017) Holistic Modeling—An Objection to Weisberg’s Weighted Feature-Matching Account. [Preprint]

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Michael Weisberg’s account of scientific models concentrates on the ways in which models are similar to their targets. He intends not merely to explain what similarity consists in, but also to capture similarity judgments made by scientists. In order to scrutinize whether his account fulfills this goal, I outline one common way in which scientists judge whether a model is similar enough to its target, namely maximum likelihood estimation method (MLE). Then I consider whether Weisberg’s account could capture the judgments involved in this practice. I argue that his account fails for three reasons. First, his account is simply too abstract to capture what is going on in MLE. Second, it implies an atomistic conception of similarity, while MLE operates in a holistic manner. Third, Weisberg’s atomistic conception of similarity can be traced back to a problematic set-theoretic approach to the structure of models. Finally, I tentatively suggest how these problems might be solved by a holistic approach in which models and targets are compared in a non-set-theoretic fashion.

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Item Type: Preprint
Fang, Weiwesleyfang@outlook.com0000000198560599
Subjects: General Issues > Models and Idealization
Depositing User: Dr. Wei Fang
Date Deposited: 08 May 2024 18:46
Last Modified: 08 May 2024 18:46
Item ID: 23388
DOI or Unique Handle:
Subjects: General Issues > Models and Idealization
Date: 2017

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