The Elusive Basis of Inferential Robustness

Philosophy of Science 79 (5):795-807 (2012)
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Abstract

Robustness concepts are often invoked to manage two obstacles confronting models of ecological systems: complexity and uncertainty. The intuitive idea is that any result derived from many idealized but credible models is thereby made more reliable or is better confirmed. An appropriate basis for this inference has proven elusive. Here, several representations of robustness analysis are vetted, paying particular attention to complex models of ecosystems and the global climate. The claim that robustness is itself confirmatory because robustness analysis employs a Bayesian variety-of-evidence argument is criticized, but recent overwhelming pessimism about robustness may have a silver lining.

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James Justus
Florida State University

Citations of this work

Robustness Analysis as Explanatory Reasoning.Jonah N. Schupbach - 2018 - British Journal for the Philosophy of Science 69 (1):275-300.
Robustness analysis and tractability in modeling.Chiara Lisciandra - 2017 - European Journal for Philosophy of Science 7 (1):79-95.
Allocating confirmation with derivational robustness.Aki Lehtinen - 2016 - Philosophical Studies 173 (9):2487-2509.

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References found in this work

Robustness Analysis.Michael Weisberg - 2006 - Philosophy of Science 73 (5):730-742.
Confirmation and Robustness of Climate Models.Elisabeth A. Lloyd - 2010 - Philosophy of Science 77 (5):971–984.
Mathematics and indispensability.Elliott Sober - 1993 - Philosophical Review 102 (1):35-57.

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