David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Synthese 163 (3):305 - 314 (2008)
We argue for a naturalistic account for appraising scientific methods that carries non-trivial normative force. We develop our approach by comparison with Laudan’s (American Philosophical Quarterly 24:19–31, 1987, Philosophy of Science 57:20–33, 1990) “normative naturalism” based on correlating means (various scientific methods) with ends (e.g., reliability). We argue that such a meta-methodology based on means–ends correlations is unreliable and cannot achieve its normative goals. We suggest another approach for meta-methodology based on a conglomeration of tools and strategies (from statistical modeling, experimental design, and related fields) that affords forward looking procedures for learning from error and for controlling error. The resulting “error statistical” appraisal is empirical—methods are appraised by examining their capacities to control error. At the same time, this account is normative, in that the strategies that pass muster are claims about how actually to proceed in given contexts to reach reliable inferences from limited data.
|Keywords||Normative naturalism Reliable inference Methodology Meta-methodology Error statistics Learning from error Controlling error Appraising scientific methods Laudan Canonical models of error Means–ends approaches|
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References found in this work BETA
Thomas S. Kuhn (1962). The Structure of Scientific Revolutions Vol. The University of Chicago Press.
Ronald N. Giere (2006). Scientific Perspectivism. University of Chicago Press.
Hilary Kornblith (2002). Knowledge and its Place in Nature. Oxford University Press.
Deborah G. Mayo (2001). Error and the Growth of Experimental Knowledge. International Studies in the Philosophy of Science 15 (1):455-459.
A. F. Chalmers (1999). What is This Thing Called Science? Monograph Collection (Matt - Pseudo).
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