Weiskopf, Daniel (2025) Trading Evidence: The Role of Models in Interfield Unification. [Preprint]

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Abstract

Scientific fields frequently need to exchange data to advance their own inquiries. Data unification is the process of stabilizing these forms of interfield data exchange. I present an account of the epistemic structure of data unification, drawing on case studies from model-based cognitive neuroscience (MBCN). MBCN is distinctive because it shows that modeling practices play an essential role in mediating these data exchanges. Models often serve as interfield evidential integrators, and models built for this purpose have their own representational and inferential functions. This form of data unification should be seen as autonomous from other forms, particularly explanatory unification.

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Item Type:	Preprint
Creators:	Creators Email ORCID Weiskopf, Daniel dweiskopf@gsu.edu
Keywords:	Modeling; Data; Interfield relations; Unification; Integration; Model-Based Cognitive Neuroscience
Subjects:	General Issues > Data Specific Sciences > Neuroscience > Cognitive Neuroscience General Issues > Models and Idealization
Depositing User:	Daniel Weiskopf
Date Deposited:	13 Mar 2025 14:28
Last Modified:	13 Mar 2025 14:28
Item ID:	24909
Official URL:	https://doi.org/10.1017/psa.2025.14
DOI or Unique Handle:	10.1017/psa.2025.14
Subjects:	General Issues > Data Specific Sciences > Neuroscience > Cognitive Neuroscience General Issues > Models and Idealization
Date:	13 March 2025
URI:	https://philsci-archive.pitt.edu/id/eprint/24909

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