Robustness Analysis as Explanatory Reasoning


Authors
Jonah N. Schupbach
University of Utah
Abstract
When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be robust. This paper investigates the logic of such "robustness analysis" [RA]. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a unified, explanatory account of diversity in RAs. The resulting account is, I argue, truer to actual cases of RA in science; moreover, this account affords us a helpful, new foothold on the logic undergirding RAs.
Keywords Robustness Analysis  Bayesianism  General Philosophy of Science  Explanatory Reasoning
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DOI 10.1093/bjps/axw008
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References found in this work BETA

Error and the Growth of Experimental Knowledge.Deborah Mayo - 1996 - International Studies in the Philosophy of Science 15 (1):455-459.
Robustness Analysis.Michael Weisberg - 2006 - Philosophy of Science 73 (5):730-742.
The Logic of Explanatory Power.Jonah N. Schupbach & Jan Sprenger - 2011 - Philosophy of Science 78 (1):105-127.
Representing and Intervening.Ian Hacking - 1984 - British Journal for the Philosophy of Science 35 (4):381-390.

View all 37 references / Add more references

Citations of this work BETA

Robustness and Independent Evidence.Jacob Stegenga & Tarun Menon - 2017 - Philosophy of Science 84 (3):414-435.
Psychopathology and Truth: A Defense of Realism.Markus I. Eronen - 2019 - Journal of Medicine and Philosophy 44 (4):507-520.
Robust Realism for the Life Sciences.Markus I. Eronen - 2019 - Synthese 196 (6):2341-2354.
When Expert Disagreement Supports the Consensus.Finnur Dellsén - 2018 - Australasian Journal of Philosophy 96 (1):142-156.

View all 9 citations / Add more citations

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