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The Elusive Basis of Inferential Robustness

Published online by Cambridge University Press:  01 January 2022

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.

Type
Inference and Statistics
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

For helpful feedback, thanks to John Matthewson, Carl Salk, Jan Sprenger, and audiences at the Philosophy of Science Association Biennial Meeting at Montreal (November 2010) and the International Society for the History, Philosophy, and Social Studies of Biology at Salt Lake City (July 2011). Special thanks to Jan Sprenger for organizing the PSA session in which this article was presented.

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