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Published online by Cambridge University Press:  04 December 2018


In this paper, we seek a reliabilist account of justified credence. Reliabilism about justified beliefs comes in two varieties: process reliabilism (Goldman 1979, 2008) and indicator reliabilism (Alston 1988, 2005). Existing accounts of reliabilism about justified credence come in the same two varieties: Jeff Dunn (2015) proposes a version of process reliabilism, while Weng Hong Tang (2016) offers a version of indicator reliabilism. As we will see, both face the same objection. If they are right about what justification is, it is mysterious why we care about justification, for neither of the accounts explains how justification is connected to anything of epistemic value. We will call this the Connection Problem. I begin by describing Dunn's process reliabilism and Tang's indicator reliabilism. I argue that, understood correctly, they are, in fact, extensionally equivalent. That is, Dunn and Tang reach the top of the same mountain, albeit by different routes. However, I argue that both face the Connection Problem. In response, I offer my own version of reliabilism, which is both process and indicator, and I argue that it solves that problem. Furthermore, I show that it is also extensionally equivalent to Dunn's reliabilism and Tang's. Thus, I reach the top of the same mountain as well.

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Alston, W. 1988. ‘An Internalist Externalism.’ Synthese, 74: 265–83.CrossRefGoogle Scholar
Alston, W. 2005. Beyond ‘Justification’: Dimensions of Epistemic Evaluation. Ithaca, NY: Cornell University Press.Google Scholar
Comesaña, J. 2006. ‘A Well-founded Solution to the Generality Problem.’ Philosophical Studies, 129: 2747.CrossRefGoogle Scholar
de Finetti, B. 1974. Theory of Probability, Vol. I. New York, NY: John Wiley & Sons.Google Scholar
Dorst, K. 2017. ‘Lockeans Maximize Expected Accuracy.’ Mind 10.1093/mind/fzx028.CrossRefGoogle Scholar
Dunn, J. 2015. ‘Reliability for Degrees of Belief.’ Philosophical Studies, 172(7): 1929–52.CrossRefGoogle Scholar
Easwaran, K. 2016. ‘Dr Truthlove, Or: How I Learned to Stop Worrying and Love Bayesian Probabilities.’ Noûs, 50(4): 816–53.CrossRefGoogle Scholar
Feldman, R. 1985. ‘Reliability and Justification.’ The Monist, 68(2): 159–74.CrossRefGoogle Scholar
Goldman, A. 1979. ‘What is Justified Belief?’ In Pappas, G. S. (ed.), Justification and Knowledge, pp. 125. Dordrecht: D. Reidel.Google Scholar
Goldman, A. 2008. ‘Immediate Justification and Process Reliabilism.’ In Smith, Q. (ed.), Epistemology: New Essays, pp. 6382. New York, NY: Oxford University Press.CrossRefGoogle Scholar
Greaves, H. and Wallace, D. 2006. ‘Justifying Conditionalization: Conditionalization Maximizes Expected Epistemic Utility.’ Mind, 115(459): 607–32.CrossRefGoogle Scholar
Hájek, A. ms. ‘A Puzzle about Partial Belief.’Google Scholar
Horowitz, S. 2014. ‘Immoderately Rational.’ Philosophical Studies, 167: 4156.CrossRefGoogle Scholar
Joyce, J. M. 1998. ‘A Nonpragmatic Vindication of Probabilism.’ Philosophy of Science, 65(4): 575603.CrossRefGoogle Scholar
Joyce, J. M. 2009. ‘Accuracy and Coherence: Prospects for an Alethic Epistemology of Partial Belief.’ In Huber, F. and Schmidt-Petri, C. (eds), Degrees of Belief, pp. 263–97. New York, NY: Springer.CrossRefGoogle Scholar
Lange, M. 1999. ‘Calibration and the Epistemological Role of Bayesian Conditionalization.’ Journal of Philosophy, 96(6): 294324.CrossRefGoogle Scholar
Levinstein, B. A. 2015. ‘With All Due Respect: The Macro-Epistemology of Disagreement.’ Philosophers’ Imprint, 15(3): 120.Google Scholar
Moss, S. 2011. ‘Scoring Rules and Epistemic Compromise.’ Mind, 120(480): 1053–69.CrossRefGoogle Scholar
Pettigrew, R. 2012. ‘Accuracy, Chance, and the Principal Principle.’ Philosophical Review, 121(2): 241–75.CrossRefGoogle Scholar
Pettigrew, R. 2013. ‘A New Epistemic Utility Argument for the Principal Principle.’ Episteme, 10(1): 1935.CrossRefGoogle Scholar
Pettigrew, R. 2016a. Accuracy and the Laws of Credence. Oxford: Oxford University Press.CrossRefGoogle Scholar
Pettigrew, R. 2016b. ‘Jamesian Epistemology Formalised: An Explication of ‘The Will to Believe’.’ Episteme, 13(3): 253–68.CrossRefGoogle Scholar
Pettigrew, R. Forthcoming. ‘On the Accuracy of Group Credences.’ In Gendler, T. S. and Hawthorne, J. (eds), Oxford Studies in Epistemology, Vol. 6. Oxford: Oxford University Press.Google Scholar
Predd, J., Seiringer, R., Lieb, E. H., Osherson, D., Poor, V. and Kulkarni, S. 2009. ‘Probabilistic Coherence and Proper Scoring Rules.’ IEEE Transactions of Information Theory, 55(10): 4786–92.CrossRefGoogle Scholar
Savage, L. J. 1971. ‘Elicitation of Personal Probabilities and Expectations.’ Journal of the American Statistical Association, 66(336): 783801.CrossRefGoogle Scholar
Schoenfield, M. 2015. ‘Bridging Rationality and Accuracy.’ Journal of Philosophy, 112(12): 633–57.CrossRefGoogle Scholar
Seidenfeld, T. 1985. ‘Calibration, Coherence, and Scoring Rules.’ Philosophy of Science, 52(2): 274–94.CrossRefGoogle Scholar
Shimony, A. 1988. ‘An Adamite Derivation of the Calculus of Probability.’ In Fetzer, J. (ed.), Probability and Causality, pp. 7989. Dordrecht: D. Reidel.CrossRefGoogle Scholar
Tang, W. H. 2016. ‘Reliability Theories of Justified Credence.’ Mind, 125(497): 6394.CrossRefGoogle Scholar
van Fraassen, B. C. 1983. ‘Calibration: Frequency Justification for Personal Probability.’ In Cohen, R. S. and Laudan, L. (eds), Physics, Philosophy, and Psychoanalysis, pp. 295319. Dordrecht: Springer.CrossRefGoogle Scholar