Error, error-statistics and self-directed anticipative learning

Foundations of Science 14 (4):249-271 (2009)
Error is protean, ubiquitous and crucial in scientific process. In this paper it is argued that understanding scientific process requires what is currently absent: an adaptable, context-sensitive functional role for error in science that naturally harnesses error identification and avoidance to positive, success-driven, science. This paper develops a new account of scientific process of this sort, error and success driving Self-Directed Anticipative Learning (SDAL) cycling, using a recent re-analysis of ape-language research as test example. The example shows the limitations of other accounts of error, in particular Mayo’s (Error and the growth of experimental knowledge, 1996) error-statistical approach, and SDAL cycling shows how they can be fruitfully contextualised.
Keywords Error in science  Scientific method  Adaptive learning
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DOI 10.1007/s10699-008-9155-6
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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.

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Citations of this work BETA
Cliff Hooker (2013). Georg Simmel and Naturalist Interactivist Epistemology of Science. Studies in History and Philosophy of Science Part A 44 (3):311-317.

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