
Contents
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1 Engineering for truth-seeking 1 Engineering for truth-seeking
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2 Systematizing epistemic normativity: a priori aspects and richly empirical aspects 2 Systematizing epistemic normativity: a priori aspects and richly empirical aspects
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3 Tractability: ought implies can 3 Tractability: ought implies can
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4 Idealization and epistemic competence 4 Idealization and epistemic competence
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5 Epistemic competence and the meliorative dimension of epistemology 5 Epistemic competence and the meliorative dimension of epistemology
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6 Epistemic competence and the E-spectrum 6 Epistemic competence and the E-spectrum
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7 Toward a theory of epistemic competence 7 Toward a theory of epistemic competence
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7.1 High-church computationalism 7.1 High-church computationalism
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7.2 Functional analysis 7.2 Functional analysis
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7.3 Connectionist resources 7.3 Connectionist resources
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8 Some relevant work in cognitive science 8 Some relevant work in cognitive science
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8.1 Judgmental heuristics 8.1 Judgmental heuristics
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8.2 Fast and frugal decision processes 8.2 Fast and frugal decision processes
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8.3 Mental models 8.3 Mental models
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9 Conclusion 9 Conclusion
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6 Epistemic Competence and the Call to Naturalize Epistemology
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Published:June 2011
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Abstract
Justificatory cognitive processes must be tractable. That one ought to produce and sustain beliefs in certain ways entails that one can. Fitting epistemic standards for human epistemic agents must be sensitive to which potential belief-forming processes humans are capable of employing, at least with training. Such (low-grade a priori) points call for a naturalized epistemology. This chapter clarifies this demand by elaborating upon the kind of idealized normative standards one can expect from a naturalized epistemology, and on the range of disciplines that can contribute to normative naturalized epistemology. It also advances a way of thinking about naturalized epistemology as encompassing a broad spectrum of inquiry ranging from low-grade reflection about central evaluative concepts to richly empirical inquiry revealing the character of actual human cognitive processes and the possibilities for variation. The organizing principle that holds the spectrum together is the concern for a kind of engineering for truth seeking. Just as various kinds of inquiry find a place within common engineering disciplines, so likewise a wide range of inquiries can find a place within naturalized epistemology. The spectrum of inquiry falling within naturalized epistemology is the E-spectrum (the ‘E’ standing both for epistemology and for engineering).
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