Tȃrziu, Gabriel and Trpin, Borut (2025) Learning Without Representation: The Epistemic Role of Models in Climate Science. [Preprint]

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Abstract

This paper aims to develop a novel account of how scientific models of complex systems can provide us with knowledge, drawing on insights from climate modelling. We begin by critically examining the prevalent representation-based views of models, which struggle to account for the common practice of using contradictory models and model hierarchies. We then argue that scientific models (especially those of complex systems) are better understood as structures that do not need to represent the target system to be epistemically useful. Instead, their usefulness lies in the fact that they are part of an iterative process of knowledge improvement and restructuring.

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Item Type:	Preprint
Creators:	Creators Email ORCID Tȃrziu, Gabriel Gabriel.Tarziu@lmu.de 0000-0002-7331-5412 Trpin, Borut borut.trpin1@um.si 0000-0002-1121-9388
Keywords:	scientific models, inconsistency of models, hierarchies of models, climate modelling, model-based reasoning, philosophy of science
Subjects:	Specific Sciences > Climate Science and Meteorology General Issues > Models and Idealization General Issues > Theory/Observation
Depositing User:	Dr. Borut Trpin
Date Deposited:	15 May 2025 12:19
Last Modified:	15 May 2025 12:19
Item ID:	25316
Subjects:	Specific Sciences > Climate Science and Meteorology General Issues > Models and Idealization General Issues > Theory/Observation
Date:	2025
URI:	https://philsci-archive.pitt.edu/id/eprint/25316

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