Synthese 194 (10):3931-3954 (2017)

Authors
Aidan Lyon
University of Maryland, College Park
Abstract
It is natural to think of precise probabilities as being special cases of imprecise probabilities, the special case being when one’s lower and upper probabilities are equal. I argue, however, that it is better to think of the two models as representing two different aspects of our credences, which are often vague to some degree. I show that by combining the two models into one model, and understanding that model as a model of vague credence, a natural interpretation arises that suggests a hypothesis concerning how we can improve the accuracy of aggregate credences. I present empirical results in support of this hypothesis. I also discuss how this modeling interpretation of imprecise probabilities bears upon a philosophical objection that has been raised against them, the so-called inductive learning problem.
Keywords Vagueness  Imprecise  Indeterminate  Credence   Subjective probability  Degree of belief  Aggregation
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DOI 10.1007/s11229-015-0782-5
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References found in this work BETA

Vagueness.Timothy Williamson - 1994 - London and New York: Routledge.
A Treatise on Probability.John Maynard Keynes - 1921 - London, England: Dover Publications.
Probability and the Logic of Rational Belief.Henry Ely Kyburg - 1961 - Middletown, CT, USA: Middletown, Conn., Wesleyan University Press.

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Citations of this work BETA

Imprecise Probabilities.Seamus Bradley - 2019 - Stanford Encyclopedia of Philosophy.
Maximal Cluelessness.Andreas L. Mogensen - 2021 - Philosophical Quarterly 71 (1):141-162.
When Econs Are Human.John R. Welch - 2020 - Journal of Economic Methodology 27 (3):212-225.

View all 9 citations / Add more citations

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