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  1. Problems for Dogmatism.Roger White - 2006 - Philosophical Studies 131 (3):525-557.
    I argue that its appearing to you that P does not provide justification for believing that P unless you have independent justification for the denial of skeptical alternatives – hypotheses incompatible with P but such that if they were true, it would still appear to you that P. Thus I challenge the popular view of ‘dogmatism,’ according to which for some contents P, you need only lack reason to suspect that skeptical alternatives are true, in order for an experience as (...)
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  • How to Disagree about How to Disagree.Adam Elga - 2010 - In Richard Feldman & Ted A. Warfield (eds.), Disagreement. Oxford, GB: Oxford University Press. pp. 175-186.
    When one encounters disagreement about the truth of a factual claim from a trusted advisor who has access to all of one's evidence, should that move one in the direction of the advisor's view? Conciliatory views on disagreement say "yes, at least a little." Such views are extremely natural, but they can give incoherent advice when the issue under dispute is disagreement itself. So conciliatory views stand refuted. But despite first appearances, this makes no trouble for *partly* conciliatory views: views (...)
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  • Imprecise Probabilities.Seamus Bradley - 2019 - In Claus Beisbart & Nicole J. Saam (eds.), Computer Simulation Validation: Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives. Springer Verlag. pp. 525-540.
    This chapter explores the topic of imprecise probabilities as it relates to model validation. IP is a family of formal methods that aim to provide a better representationRepresentation of severe uncertainty than is possible with standard probabilistic methods. Among the methods discussed here are using sets of probabilities to represent uncertainty, and using functions that do not satisfy the additvity property. We discuss the basics of IP, some examples of IP in computer simulation contexts, possible interpretations of the IP framework (...)
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  • Statistical Reasoning with Imprecise Probabilities.Peter Walley - 1991 - Chapman & Hall.
    An examination of topics involved in statistical reasoning with imprecise probabilities. The book discusses assessment and elicitation, extensions, envelopes and decisions, the importance of imprecision, conditional previsions and coherent statistical models.
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  • Chilling out on epistemic rationality: A defense of imprecise credences.Miriam Schoenfield - 2012 - Philosophical Studies 158 (2):197-219.
    A defense of imprecise credences (and other imprecise doxastic attitudes).
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  • The skeptic and the dogmatist.James Pryor - 2000 - Noûs 34 (4):517–549.
    Consider the skeptic about the external world. Let’s straightaway concede to such a skeptic that perception gives us no conclusive or certain knowledge about our surroundings. Our perceptual justification for beliefs about our surroundings is always defeasible—there are always possible improvements in our epistemic state which would no longer support those beliefs. Let’s also concede to the skeptic that it’s metaphysically possible for us to have all the experiences we’re now having while all those experiences are false. Some philosophers dispute (...)
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  • Immodest inductive methods.David Lewis - 1971 - Philosophy of Science 38 (1):54-63.
    Inductive methods can be used to estimate the accuracies of inductive methods. Call a method immodest if it estimates that it is at least as accurate as any of its rivals. It would be unreasonable to adopt any but an immodest method. Under certain assumptions, exactly one of Carnap's lambda-methods is immodest. This may seem to solve the problem of choosing among the lambda-methods; but sometimes the immodest lambda-method is λ =0, which it would not be reasonable to adopt. We (...)
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  • New Rational Reflection and Internalism about Rationality.Maria Lasonen-Aarnio - 2015 - Oxford Studies in Epistemology 5.
    Numerous authors have defended the rough idea that it is irrational to fail to conform to one’s judgments about what it would be rational to do, or what doxastic states it would be rational to be in. This chapter examines rational reflection principles as an attempt to implement this idea in contexts of uncertainty about what credence distributions are rational. After outlining some problems with Old Rational Reflection, the chapter discusses what seems like a well-motivated fix, New Rational Reflection. It (...)
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  • Distorted reflection.Rachael Briggs - 2009 - Philosophical Review 118 (1):59-85.
    Diachronic Dutch book arguments seem to support both conditionalization and Bas van Fraassen's Reflection principle. But the Reflection principle is vulnerable to numerous counterexamples. This essay addresses two questions: first, under what circumstances should an agent obey Reflection, and second, should the counterexamples to Reflection make us doubt the Dutch book for conditionalization? In response to the first question, this essay formulates a new "Qualified Reflection" principle, which states that an agent should obey Reflection only if he or she is (...)
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  • Bayesian Orgulity.Gordon Belot - 2013 - Philosophy of Science 80 (4):483-503.
    A piece of folklore enjoys some currency among philosophical Bayesians, according to which Bayesian agents that, intuitively speaking, spread their credence over the entire space of available hypotheses are certain to converge to the truth. The goals of the present discussion are to show that kernel of truth in this folklore is in some ways fairly small and to argue that Bayesian convergence-to-the-truth results are a liability for Bayesianism as an account of rationality, since they render a certain sort of (...)
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  • Imprecise Probabilities.Seamus Bradley - 2019 - Stanford Encyclopedia of Philosophy.
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