David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophy of Science 74 (5):588-600 (2007)
The simple question, what is empirical success? turns out to have a surprisingly complicated answer. We need to distinguish between meritorious fit and ‘fudged fit', which is akin to the distinction between prediction and accommodation. The final proposal is that empirical success emerges in a theory dependent way from the agreement of independent measurements of theoretically postulated quantities. Implications for realism and Bayesianism are discussed. ‡This paper was written when I was a visiting fellow at the Center for Philosophy of Science at the University of Pittsburgh; I thank everyone for their support. †To contact the author, please write to: Department of Philosophy, University of Wisconsin–Madison, 5185 Helen C. White Hall, 600 North Park Street, Madison, WI 53706; e-mail: firstname.lastname@example.org.
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References found in this work BETA
Malcolm Forster (1988). Unification, Explanation, and the Composition of Causes in Newtonian Mechanics. Studies in History and Philosophy of Science 19 (1):55-101.
Malcolm R. Forster (2006). Counterexamples to a Likelihood Theory of Evidence. Minds and Machines 16 (3):319-338.
Malcolm R. Forster (2002). Predictive Accuracy as an Achievable Goal of Science. Proceedings of the Philosophy of Science Association 2002 (3):S124-S134.
Malcolm Forster & Elliott Sober (1994). How to Tell When Simpler, More Unified, or Less Ad Hoc Theories Will Provide More Accurate Predictions. British Journal for the Philosophy of Science 45 (1):1-35.
William Harper (2007). Newton's Methodology and Mercury's Perihelion Before and After Einstein. Philosophy of Science 74 (5):932-942.
Citations of this work BETA
Peter Vickers (2013). A Confrontation of Convergent Realism. Philosophy of Science 80 (2):189-211.
Maureen A. O'Malley (2009). Making Knowledge in Synthetic Biology: Design Meets Kludge. Biological Theory 4 (4):378-389.
Teru Miyake (2013). Underdetermination, Black Boxes, and Measurement. Philosophy of Science 80 (5):697-708.
Jan Sprenger (2013). The Role of Bayesian Philosophy Within Bayesian Model Selection. European Journal for Philosophy of Science 3 (1):101-114.
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