Abstract
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.
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Farrell, R.P., Hooker, C.A. Error, Error-Statistics and Self-Directed Anticipative Learning. Found Sci 14, 249–271 (2009). https://doi.org/10.1007/s10699-008-9155-6
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DOI: https://doi.org/10.1007/s10699-008-9155-6