The error statistical philosopher as normative naturalist

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
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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