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  1. Peer disagreement and higher order evidence.Thomas Kelly - 2011 - In Alvin I. Goldman & Dennis Whitcomb (eds.), Social Epistemology: Essential Readings. New York: Oxford University Press. pp. 183--217.
    My aim in this paper is to develop and defend a novel answer to a question that has recently generated a considerable amount of controversy. The question concerns the normative significance of peer disagreement. Suppose that you and I have been exposed to the same evidence and arguments that bear on some proposition: there is no relevant consideration which is available to you but not to me, or vice versa. For the sake of concreteness, we might picture.
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  • Background.[author unknown] - 2004 - The Chesterton Review 30 (3-4):411-413.
    I was born in Philadelphia, in 1928. I stayed there until I went through undergraduate school at the University of Pennsylvania, then went on to Harvard for a couple of a years in a research fellowship, and graduate school. When I was done with that, went over to MIT, and I've been in Boston ever since, around Boston since about..
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  • What should we do when we disagree?Jennifer Lackey - 2005 - In Tamar Szabó Gendler & John Hawthorne (eds.), Oxford Studies in Epistemology. Oxford University Press. pp. 274-93.
    You and I have been colleagues for ten years, during which we have tirelessly discussed the reasons both for and against the existence of God. There is no argument or piece of evidence bearing directly on this question that one of us is aware of that the other is not—we are, then, evidential equals relative to the topic of God’s existence. There is also no cognitive virtue or capacity, or cognitive vice or incapacity, that one of us possesses that the (...)
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  • Peer Disagreement and Higher Order Evidence.Thomas Kelly - 2010 - In Richard Feldman & Ted A. Warfield (eds.), Disagreement. Oxford, GB: Oxford University Press.
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  • Epistemology of disagreement: The good news.David Christensen - 2007 - Philosophical Review 116 (2):187-217.
    How should one react when one has a belief, but knows that other people—who have roughly the same evidence as one has, and seem roughly as likely to react to it correctly—disagree? This paper argues that the disagreement of other competent inquirers often requires one to be much less confident in one’s opinions than one would otherwise be.
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  • Subjective Probabilities Should be Sharp.Adam Elga - 2010 - Philosophers' Imprint 10.
    Many have claimed that unspecific evidence sometimes demands unsharp, indeterminate, imprecise, vague, or interval-valued probabilities. Against this, a variant of the diachronic Dutch Book argument shows that perfectly rational agents always have perfectly sharp probabilities.
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  • Disagreement, equal weight and commutativity.Alastair Wilson - 2010 - Philosophical Studies 149 (3):321 - 326.
    How should we respond to cases of disagreement where two epistemic agents have the same evidence but come to different conclusions? Adam Elga has provided a Bayesian framework for addressing this question. In this paper, I shall highlight two unfortunate consequences of this framework, which Elga does not anticipate. Both problems derive from a failure of commutativity between application of the equal weight view and updating in the light of other evidence.
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  • Peer Disagreement and Independence Preservation.Carl G. Wagner - 2011 - Erkenntnis 74 (2):277-288.
    It has often been recommended that the differing probability distributions of a group of experts should be reconciled in such a way as to preserve each instance of independence common to all of their distributions. When probability pooling is subject to a universal domain condition, along with state-wise aggregation, there are severe limitations on implementing this recommendation. In particular, when the individuals are epistemic peers whose probability assessments are to be accorded equal weight, universal preservation of independence is, with a (...)
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  • Probability kinematics and commutativity.Carl G. Wagner - 2002 - Philosophy of Science 69 (2):266-278.
    The so-called "non-commutativity" of probability kinematics has caused much unjustified concern. When identical learning is properly represented, namely, by identical Bayes factors rather than identical posterior probabilities, then sequential probability-kinematical revisions behave just as they should. Our analysis is based on a variant of Field's reformulation of probability kinematics, divested of its (inessential) physicalist gloss.
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  • Jeffrey conditioning and external Bayesianity.Carl Wagner - 2010 - Logic Journal of the IGPL 18 (2):336-345.
    Suppose that several individuals who have separately assessed prior probability distributions over a set of possible states of the world wish to pool their individual distributions into a single group distribution, while taking into account jointly perceived new evidence. They have the option of first updating their individual priors and then pooling the resulting posteriors or first pooling their priors and then updating the resulting group prior. If the pooling method that they employ is such that they arrive at the (...)
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  • Allocation, Lehrer models, and the consensus of probabilities.Carl Wagner - 1982 - Theory and Decision 14 (2):207-220.
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  • Scoring Rules and Epistemic Compromise.Sarah Moss - 2011 - Mind 120 (480):1053-1069.
    It is commonly assumed that when we assign different credences to a proposition, a perfect compromise between our opinions simply ‘splits the difference’ between our credences. I introduce and defend an alternative account, namely that a perfect compromise maximizes the average of the expected epistemic values that we each assign to alternative credences in the disputed proposition. I compare the compromise strategy I introduce with the traditional strategy of compromising by splitting the difference, and I argue that my strategy is (...)
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  • Destroying the consensus.Barry Loewer & Robert Laddaga - 1985 - Synthese 62 (1):79 - 95.
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  • Aggregating sets of judgments: An impossibility result.Christian List & Philip Pettit - 2002 - Economics and Philosophy 18 (1):89-110.
    Suppose that the members of a group each hold a rational set of judgments on some interconnected questions, and imagine that the group itself has to form a collective, rational set of judgments on those questions. How should it go about dealing with this task? We argue that the question raised is subject to a difficulty that has recently been noticed in discussion of the doctrinal paradox in jurisprudence. And we show that there is a general impossibility theorem that that (...)
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  • The Enterprise of Knowledge, An Essay on Knowledge, Credal Probability, and Chances.Henry E. Kyburg - 1984 - Noûs 18 (2):347-354.
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  • The Enterprise of Knowledge: An Essay on Knowledge, Credal Probability, and Chance.Isaac Levi - 1980 - MIT Press.
    This major work challenges some widely held positions in epistemology - those of Peirce and Popper on the one hand and those of Quine and Kuhn on the other.
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  • Probability amalgamation and the independence issue: A reply to Laddaga.Keith Lehrer & Carl Wagner - 1983 - Synthese 55 (3):339 - 346.
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  • The Logic of Decision.Richard C. Jeffrey - 1965 - New York, NY, USA: University of Chicago Press.
    "[This book] proposes new foundations for the Bayesian principle of rational action, and goes on to develop a new logic of desirability and probabtility."—Frederic Schick, _Journal of Philosophy_.
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  • The Logic of Decision.Brian Skyrms - 1965 - Journal of Symbolic Logic 50 (1):247-248.
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  • The Logic of Decision. [REVIEW]Frederic Schick - 1967 - Journal of Philosophy 64 (12):396-400.
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  • What is the “Equal Weight View'?Branden Fitelson & David Jehle - 2009 - Episteme 6 (3):280-293.
    In this paper, we investigate various possible (Bayesian) precisifications of the (somewhat vague) statements of “the equal weight view” (EWV) that have appeared in the recent literature on disagreement. We will show that the renditions of (EWV) that immediately suggest themselves are untenable from a Bayesian point of view. In the end, we will propose some tenable (but not necessarily desirable) interpretations of (EWV). Our aim here will not be to defend any particular Bayesian precisification of (EWV), but rather to (...)
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  • A note on Jeffrey conditionalization.Hartry Field - 1978 - Philosophy of Science 45 (3):361-367.
    Bayesian decision theory can be viewed as the core of psychological theory for idealized agents. To get a complete psychological theory for such agents, you have to supplement it with input and output laws. On a Bayesian theory that employs strict conditionalization, the input laws are easy to give. On a Bayesian theory that employs Jeffrey conditionalization, there appears to be a considerable problem with giving the input laws. However, Jeffrey conditionalization can be reformulated so that the problem disappears, and (...)
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  • Reflection and disagreement.Adam Elga - 2007 - Noûs 41 (3):478–502.
    How should you take into account the opinions of an advisor? When you completely defer to the advisor's judgment, then you should treat the advisor as a guru. Roughly, that means you should believe what you expect she would believe, if supplied with your extra evidence. When the advisor is your own future self, the resulting principle amounts to a version of the Reflection Principle---a version amended to handle cases of information loss. When you count an advisor as an epistemic (...)
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  • Social Choice and Individual Values.Irving M. Copi - 1952 - Science and Society 16 (2):181-181.
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  • Social Choice and Individual Values.Kenneth Joseph Arrow - 1951 - New York, NY, USA: Wiley: New York.
    The literature on the theory of social choice has grown considerably beyond the few items in existence at the time the first edition of this book appeared in 1951. Some of the new literature has dealt with the technical, mathematical aspects, more with the interpretive. My own thinking has also evolved somewhat, although I remain far from satisfied with present formulations. The exhaustion of the first edition provides a convenient time for a selective and personal stocktaking in the form of (...)
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  • Bayesianism With A Human Face.Richard C. Jeffrey - 1983 - In John Earman (ed.), Testing Scientific Theories. University of Minnesota Press. pp. 133--156.
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