David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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British Journal for the Philosophy of Science 55 (1):1-34 (2004)
an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the key is the concept of overfitting. We float the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of overfitting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the conflict between instrumentalism and scientific realism. Introduction Predictivisms—a taxonomy Observations Formulating the problem What might Annie be doing wrong? Solutions Observations explained Mayo on severe tests The miracle argument and scientific realism Concluding comments.
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Citations of this work BETA
David Harker (2010). Two Arguments for Scientific Realism Unified. Studies in History and Philosophy of Science Part A 41 (2):192-202.
M. Colombo & P. Series (2012). Bayes in the Brain--On Bayesian Modelling in Neuroscience. British Journal for the Philosophy of Science 63 (3):697-723.
Maarten Boudry & Bert Leuridan (2011). Where the Design Argument Goes Wrong: Auxiliary Assumptions and Unification. Philosophy of Science 78 (4):558-578.
David Harker (2008). On the Predilections for Predictions. British Journal for the Philosophy of Science 59 (3):429-453.
Kevin McCain (2012). A Predictivist Argument Against Scepticism. Analysis 72 (4):660-665.
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