Contextual and Global Falsification of Scientific Models: An Integrated Theory of Epistemic Validity

The classical and widely received Popperian theory of falsification operates with an idealized binary picture of scientific rationality, according to which a theory is in principle undermined by a conflicting observation (Popper [1934] 1959). Even though Popper himself acknowledges methodological side conditions, this binary-eliminative structure remains too coarse for analyzing modern modeling practice. Models such as Newtonian mechanics, classical thermodynamics, or contemporary climate models are empirically limited in certain subdomains yet remain epistemically indispensable in others. This paper develops an integrative framework of model validity as a philosophy-of-science specialization of model management under finite conditions. It combines insights from Popper, Kuhn, Lakatos, da Costa/French, and contemporary model theory; distinguishes global from contextual falsification; and introduces the epistemic enabling space E(t). E(t) renders explicit the methodological, technical, and institutional conditions under which models can be formulated, tested, stabilized, and replaced by alternatives. "Falsification" is understood here not as a purely logical criterion of truth or falsity but as a rational-pragmatic mechanism of model evaluation. The decisive issue is not merely whether a model's performance declines in a given domain, but whether available alternatives within the same relevant domain prove stably more epistemically competitive over time. The proposed reconstructive evaluative structure links approximate truth, explanatory power, and model costs without treating scientific rationality as generally algorithmically computable. A case study of climate models illustrates how ensemble methods, parameterizations, and probabilistic weighting procedures contribute to domain refinement. The theory thereby reconstructs central structures of modern modeling practice and explains why models remain stable despite partial falsifications, when they are revised, and under which conditions global model replacement occurs.

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Publication Details

Journal
PhilPapers (PhilPapers Foundation)
Published
2026-04-27
DOI
https://doi.org/10.5281/zenodo.17714966
Primary Topic
Philosophy and History of Science
Type
article
Field-Weighted Citation Impact
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article

Contextual and Global Falsification of Scientific Models: An Integrated Theory of Epistemic Validity

PhilPapers (PhilPapers Foundation)
Philosophy and History of Science
article

Contextual and Global Falsification of Scientific Models: An Integrated Theory of Epistemic Validity

article en

Abstract

The classical and widely received Popperian theory of falsification operates with an idealized binary picture of scientific rationality, according to which a theory is in principle undermined by a conflicting observation (Popper [1934] 1959). Even though Popper himself acknowledges methodological side conditions, this binary-eliminative structure remains too coarse for analyzing modern modeling practice. Models such as Newtonian mechanics, classical thermodynamics, or contemporary climate models are empirically limited in certain subdomains yet remain epistemically indispensable in others. This paper develops an integrative framework of model validity as a philosophy-of-science specialization of model management under finite conditions. It combines insights from Popper, Kuhn, Lakatos, da Costa/French, and contemporary model theory; distinguishes global from contextual falsification; and introduces the epistemic enabling space E(t). E(t) renders explicit the methodological, technical, and institutional conditions under which models can be formulated, tested, stabilized, and replaced by alternatives. "Falsification" is understood here not as a purely logical criterion of truth or falsity but as a rational-pragmatic mechanism of model evaluation. The decisive issue is not merely whether a model's performance declines in a given domain, but whether available alternatives within the same relevant domain prove stably more epistemically competitive over time. The proposed reconstructive evaluative structure links approximate truth, explanatory power, and model costs without treating scientific rationality as generally algorithmically computable. A case study of climate models illustrates how ensemble methods, parameterizations, and probabilistic weighting procedures contribute to domain refinement. The theory thereby reconstructs central structures of modern modeling practice and explains why models remain stable despite partial falsifications, when they are revised, and under which conditions global model replacement occurs.

PhilPapers (PhilPapers Foundation)
RWP (Germany) (DE)
Climate action
Openalex Percentile: Top 99%
Philosophy and History of Science
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