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  1. Rational Consensus in Science and Society a Philosophical and Mathematical Study.Keith Lehrer & Carl Wagner - 1981
     
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  • Disagreement as Evidence: The Epistemology of Controversy.David Christensen - 2009 - Philosophy Compass 4 (5):756-767.
    How much should your confidence in your beliefs be shaken when you learn that others – perhaps 'epistemic peers' who seem as well-qualified as you are – hold beliefs contrary to yours? This article describes motivations that push different philosophers towards opposite answers to this question. It identifies a key theoretical principle that divides current writers on the epistemology of disagreement. It then examines arguments bearing on that principle, and on the wider issue. It ends by describing some outstanding questions (...)
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  • Experts: Which Ones Should You Trust?Alvin I. Goldman - 2001 - Philosophy and Phenomenological Research 63 (1):85-110.
    Mainstream epistemology is a highly theoretical and abstract enterprise. Traditional epistemologists rarely present their deliberations as critical to the practical problems of life, unless one supposes—as Hume, for example, did not—that skeptical worries should trouble us in our everyday affairs. But some issues in epistemology are both theoretically interesting and practically quite pressing. That holds of the problem to be discussed here: how laypersons should evaluate the testimony of experts and decide which of two or more rival experts is most (...)
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  • Disagreement as Evidence: The Epistemology of Controversy.David Christensen - 2009 - Philosophy Compass 4 (5):754-767.
    How much should your confidence in your beliefs be shaken when you learn that others – perhaps ‘epistemic peers’ who seem as well-qualified as you are – hold beliefs contrary to yours? This article describes motivations that push different philosophers towards opposite answers to this question. It identifies a key theoretical principle that divides current writers on the epistemology of disagreement. It then examines arguments bearing on that principle, and on the wider issue. It ends by describing some outstanding questions (...)
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  • Subjective Probability: The Real Thing.Richard Jeffrey - 2002 - Cambridge and New York: Cambridge University Press.
    This book offers a concise survey of basic probability theory from a thoroughly subjective point of view whereby probability is a mode of judgment. Written by one of the greatest figures in the field of probability theory, the book is both a summation and synthesis of a lifetime of wrestling with these problems and issues. After an introduction to basic probability theory, there are chapters on scientific hypothesis-testing, on changing your mind in response to generally uncertain observations, on expectations of (...)
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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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  • A Theory of Bayesian Groups.Franz Dietrich - 2019 - Noûs 53 (3):708-736.
    A group is often construed as one agent with its own probabilistic beliefs (credences), which are obtained by aggregating those of the individuals, for instance through averaging. In their celebrated “Groupthink”, Russell et al. (2015) require group credences to undergo Bayesian revision whenever new information is learnt, i.e., whenever individual credences undergo Bayesian revision based on this information. To obtain a fully Bayesian group, one should often extend this requirement to non-public or even private information (learnt by not all or (...)
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  • Weighted Averaging, Jeffrey Conditioning and Invariance.Denis Bonnay & Mikaël Cozic - 2018 - Theory and Decision 85 (1):21-39.
    Jeffrey conditioning tells an agent how to update her priors so as to grant a given probability to a particular event. Weighted averaging tells an agent how to update her priors on the basis of testimonial evidence, by changing to a weighted arithmetic mean of her priors and another agent’s priors. We show that, in their respective settings, these two seemingly so different updating rules are axiomatized by essentially the same invariance condition. As a by-product, this sheds new light on (...)
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  • All Agreed: Aumann Meets DeGroot.Jan-Willem Romeijn & Olivier Roy - 2018 - Theory and Decision 85 (1):41-60.
    We represent consensus formation processes based on iterated opinion pooling as a dynamic approach to common knowledge of posteriors :1236–1239, 1976; Geanakoplos and Polemarchakis in J Econ Theory 28:192–200, 1982). We thus provide a concrete and plausible Bayesian rationalization of consensus through iterated pooling. The link clarifies the conditions under which iterated pooling can be rationalized from a Bayesian perspective, and offers an understanding of iterated pooling in terms of higher-order beliefs.
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  • Probabilistic Opinion Pooling.Franz Dietrich & Christian List - 2016 - In Alan Hajek & Christopher Hitchcock (eds.), Oxford Handbook of Philosophy and Probability. Oxford: Oxford University Press.
    Suppose several individuals (e.g., experts on a panel) each assign probabilities to some events. How can these individual probability assignments be aggregated into a single collective probability assignment? This article reviews several proposed solutions to this problem. We focus on three salient proposals: linear pooling (the weighted or unweighted linear averaging of probabilities), geometric pooling (the weighted or unweighted geometric averaging of probabilities), and multiplicative pooling (where probabilities are multiplied rather than averaged). We present axiomatic characterisations of each class of (...)
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  • Updating on the Credences of Others: Disagreement, Agreement, and Synergy.Kenny Easwaran, Luke Fenton-Glynn, Christopher Hitchcock & Joel D. Velasco - 2016 - Philosophers’ Imprint 16:1--39.
    We introduce a family of rules for adjusting one's credences in response to learning the credences of others. These rules have a number of desirable features. 1. They yield the posterior credences that would result from updating by standard Bayesian conditionalization on one's peers' reported credences if one's likelihood function takes a particular simple form. 2. In the simplest form, they are symmetric among the agents in the group. 3. They map neatly onto the familiar Condorcet voting results. 4. They (...)
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  • Learning From Others: Conditioning Versus Averaging.Richard Bradley - 2017 - Theory and Decision 85 (1):5-20.
    How should we revise our beliefs in response to the expressed probabilistic opinions of experts on some proposition when these experts are in disagreement? In this paper I examine the suggestion that in such circumstances we should adopt a linear average of the experts’ opinions and consider whether such a belief revision policy is compatible with Bayesian conditionalisation. By looking at situations in which full or partial deference to the expressed opinions of others is required by Bayesianism I show that (...)
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  • Direct Inference.Isaac Levi - 1977 - Journal of Philosophy 74 (1):5-29.
  • Belief and the Will.Bas C. van Fraassen - 1984 - Journal of Philosophy 81 (5):235-256.
  • Groupthink.Jeffrey Sanford Russell, John Hawthorne & Lara Buchak - 2015 - Philosophical Studies 172 (5):1287-1309.
    How should a group with different opinions (but the same values) make decisions? In a Bayesian setting, the natural question is how to aggregate credences: how to use a single credence function to naturally represent a collection of different credence functions. An extension of the standard Dutch-book arguments that apply to individual decision-makers recommends that group credences should be updated by conditionalization. This imposes a constraint on what aggregation rules can be like. Taking conditionalization as a basic constraint, we gather (...)
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  • Bayesian Group Belief.Franz Dietrich - 2010 - Social Choice and Welfare 35 (4):595-626.
    If a group is modelled as a single Bayesian agent, what should its beliefs be? I propose an axiomatic model that connects group beliefs to beliefs of group members, who are themselves modelled as Bayesian agents, possibly with different priors and different information. Group beliefs are proven to take a simple multiplicative form if people’s information is independent, and a more complex form if information overlaps arbitrarily. This shows that group beliefs can incorporate all information spread over the individuals without (...)
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  • On the Application of Inductive Logic.Rudolf Carnap - 1947 - Philosophy and Phenomenological Research 8 (1):133-148.
  • Testimony as Evidence: More Problems for Linear Pooling. [REVIEW]Katie Steele - 2012 - Journal of Philosophical Logic 41 (6):983-999.
    This paper considers a special case of belief updating—when an agent learns testimonial data, or in other words, the beliefs of others on some issue. The interest in this case is twofold: (1) the linear averaging method for updating on testimony is somewhat popular in epistemology circles, and it is important to assess its normative acceptability, and (2) this facilitates a more general investigation of what it means/requires for an updating method to have a suitable Bayesian representation (taken here as (...)
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  • An Interpretation of Weights in Linear Opinion Pooling.Jan-Willem Romeijn - forthcoming - Episteme:1-15.
    This paper explores the fact that linear opinion pooling can be represented as a Bayesian update on the opinions of others. It uses this fact to propose a new interpretation of the pooling weights. Relative to certain modelling assumptions the weights can be equated with the so-called truth-conduciveness known from the context of Condorcet's jury theorem. This suggests a novel way to elicit the weights.
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  • Reaching a Consensus.Richard Bradley - unknown
    This paper explores some aspects of the relation between different ways of achieving a consensus on the judgemental values of a group of indviduals; in particular, aggregation and deliberation. We argue firstly that the framing of an aggregation problem itself generates information that individuals are rationally obliged to take into account. And secondly that outputs of the deliberative process that this initiates is in tension with constraints on consensual values typically imposed by aggregation theory, at least when deliberation is modelled (...)
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  • On the Principle of Total Evidence.I. J. Good - 1966 - British Journal for the Philosophy of Science 17 (4):319-321.
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  • Resolving Some Contradictions in the Theory of Linear Opinion Pools.A. Philip Dawid & Julia Mortera - 2020 - Theory and Decision 88 (3):453-456.
    Bradley develops some theory of the linear opinion pool, in apparent contradiction to results of Dawid et al.. We investigate the sources of these contradictions, and in particular identify a mathematical error in Bradley that invalidates his main result.
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  • Taking Advantage of Difference in Opinion.Richard Bradley - 2006 - Episteme 3 (3):141-155.
    Diversity of opinion both presents problems and aff ords opportunities. Diff erences of opinion can stand in the way of reaching an agreement within a group on what decisions to take. But at the same time, the fact that the differences in question could derive from access to different information or from the exercise of diff erent judgemental skills means that they present individuals with the opportunity to improve their own opinions. This paper explores the implications for solutions to the (...)
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  • On the Application of Inductive Logic.Rudolf Carnap - 1948 - Journal of Symbolic Logic 13 (2):120-121.
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  • Belief and the Will.Bas C. van Fraassen - 2010 - In Antony Eagle (ed.), Philosophy of Probability: Contemporary Readings. Routledge. pp. 235-256.
  • The Common Prior Assumption in Economic Theory.Stephen Morris - 1995 - Economics and Philosophy 11 (2):227.
    Why is common priors are implicit or explicit in the vast majority of the differential information literature in economics and game theory? Why has the economic community been unwilling, in practice, to accept and actually use the idea of truly personal probabilities in much the same way that it did accept the idea of personal utility functions? After all, in, both the utilities and probabilities are derived separately for each decision maker. Why were the utilities accepted as personal, and the (...)
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