Highly idealized models of scientific inquiry as conceptual systems

Abstract The social epistemology of science has adopted agent-based computer simulations as one of its core methods for investigating the dynamics of scientific inquiry. The epistemic status of these highly idealized models is currently under active debate in which they are often associated either with predictive or the argumentative functions. These two functions roughly correspond to interpreting simulations as virtual experiments or formalized thought experiments, respectively. This paper advances the argumentative account of modeling by proposing that models serve as a means to (re)conceptualize the macro-level dynamics of complex social epistemic interactions. I apply results from the epistemology of scientific modeling and the psychology of mental simulation to the ongoing debate in the social epistemology of science. Instead of considering simulation models as predictive devices, I view them as artifacts that exemplify abstract hypothetical properties of complex social epistemic processes in order to advance scientific understanding, hypothesis formation, and communication. Models need not be accurate representations to serve these purposes. They should be regarded as pragmatic cognitive tools that engender rather than replace intuitions in philosophical reasoning and argumentation. Furthermore, I aim to explain why the community tends to converge around few model templates: Since models have the potential to transform our intuitive comprehension of the subject of inquiry, successful models may literally capture the imagination of the modeling community.

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Publication Details

Journal
European Journal for Philosophy of Science
Published
2024-08-09
DOI
https://doi.org/10.1007/s13194-024-00601-9
Citations
1
Primary Topic
Philosophy and History of Science
Type
article
Field-Weighted Citation Impact
6.04

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article

Highly idealized models of scientific inquiry as conceptual systems

Renne Pesonen
1 citations
European Journal for Philosophy of Science
Philosophy and History of Science
6.04
article

Highly idealized models of scientific inquiry as conceptual systems

Renne Pesonen
article en
1 citations

Abstract

Abstract The social epistemology of science has adopted agent-based computer simulations as one of its core methods for investigating the dynamics of scientific inquiry. The epistemic status of these highly idealized models is currently under active debate in which they are often associated either with predictive or the argumentative functions. These two functions roughly correspond to interpreting simulations as virtual experiments or formalized thought experiments, respectively. This paper advances the argumentative account of modeling by proposing that models serve as a means to (re)conceptualize the macro-level dynamics of complex social epistemic interactions. I apply results from the epistemology of scientific modeling and the psychology of mental simulation to the ongoing debate in the social epistemology of science. Instead of considering simulation models as predictive devices, I view them as artifacts that exemplify abstract hypothetical properties of complex social epistemic processes in order to advance scientific understanding, hypothesis formation, and communication. Models need not be accurate representations to serve these purposes. They should be regarded as pragmatic cognitive tools that engender rather than replace intuitions in philosophical reasoning and argumentation. Furthermore, I aim to explain why the community tends to converge around few model templates: Since models have the potential to transform our intuitive comprehension of the subject of inquiry, successful models may literally capture the imagination of the modeling community.

European Journal for Philosophy of ScienceVol. 14(3)
Tampere University (FI)
Suomen Kulttuurirahasto, Tays
Openalex Percentile: Top 5%
Philosophy and History of Science
6.04
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Highly idealized models of scientific inquiry as conceptual systems — Renne Pesonen · European Journal for Philosophy of Science (2024) | TGRS Research Map | TGRS