David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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European Journal for Philosophy of Science 2 (1):21-43 (2012)
Some accounts of evidence regard it as an objective relationship holding between data and hypotheses, perhaps mediated by a testing procedure. Mayo’s error-statistical theory of evidence is an example of such an approach. Such a view leaves open the question of when an epistemic agent is justified in drawing an inference from such data to a hypothesis. Using Mayo’s account as an illustration, I propose a framework for addressing the justification question via a relativized notion, which I designate security , meant to conceptualize practices aimed at the justification of inferences from evidence. I then show how the notion of security can be put to use by showing how two quite different theoretical approaches to model criticism in statistics can both be viewed as strategies for securing claims about statistical evidence
|Keywords||Evidence Statistics Robustness Mis-specification testing Error-statistics Justification Security Statistical models|
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References found in this work BETA
Jaakko Hintikka (1962). Knowledge and Belief. Ithaca, N.Y.,Cornell University Press.
Deborah G. Mayo (2001). Error and the Growth of Experimental Knowledge. International Studies in the Philosophy of Science 15 (1):455-459.
Peter Achinstein (2001). The Book of Evidence. Oxford University Press.
David J. Chalmers (2011). The Nature of Epistemic Space. In Andy Egan & Brian Weatherson (eds.), Epistemic Modality. Oxford University Press
Keith DeRose (1991). Epistemic Possibilities. Philosophical Review 100 (4):581-605.
Citations of this work BETA
William L. Harper, Kent W. Staley, Henk W. de Regt & Peter Achinstein (2014). Objective Evidence and Rules of Strategy: Achinstein on Method. Metascience 23 (3):413-442.
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