Knowledge, Noise, and Curve-Fitting: A methodological argument for JTB?

In R. Borges, C. de Almeida & P. Klein (eds.), Explaining Knowledge: New Essays on the Gettier Problem. Oxford University Press (forthcoming)
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Abstract
The developing body of empirical work on the "Gettier effect" indicates that, in general, the presence of a Gettier-type structure in a case makes participants less likely to attribute knowledge in that case. But is that a sufficient reason to diverge from a JTB theory of knowledge? I argue that considerations of good model selection, and worries about noise and overfitting, should lead us to consider that a live, open question. The Gettier effect is perhaps so transient, and so sensitive to other, epistemologically-inappropriate factors, that it raises the question of whether it ought to be counted as something to include in our theories -- or as a piece of noise to be excluded from them.
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