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  1. On Being a Random Sample.David Manley - manuscript
    It is well known that de se (or ‘self-locating’) propositions complicate the standard picture of how we should respond to evidence. This has given rise to a substantial literature centered around puzzles like Sleeping Beauty, Dr. Evil, and Doomsday—and it has also sparked controversy over a style of argument that has recently been adopted by theoretical cosmologists. These discussions often dwell on intuitions about a single kind of case, but it’s worth seeking a rule that can unify our treatment of (...)
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  2. Fragmentation and Old Evidence.Will Fleisher - forthcoming - Episteme:1-26.
    Bayesian confirmation theory is our best formal framework for describing inductive reasoning. The problem of old evidence is a particularly difficult one for confirmation theory, because it suggests that this framework fails to account for central and important cases of inductive reasoning and scientific inference. I show that we can appeal to the fragmentation of doxastic states to solve this problem for confirmation theory. This fragmentation solution is independently well-motivated because of the success of fragmentation in solving other problems. I (...)
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  3. God and the Bayesian Conception of Evidence.David Manley - forthcoming - Religious Studies.
    Contemporary arguments for and against the existence of God are often formulated within a broadly Bayesian framework. Arguments of this sort focus on a specific feature of the world that is taken to provide probabilistic evidence for or against the existence of God: the existence of life in a ‘fine-tuned’ universe, the magnitude of suffering, divine hiddenness, etc. In each case, the idea is that things were more likely to be this way if God existed than if God did not (...)
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  4. Logical Ignorance and Logical Learning.Richard G. Pettigrew - forthcoming - Synthese:1-30.
    According to certain normative theories in epistemology, rationality requires us to be logically omniscient. Yet this prescription clashes with our ordinary judgments of rationality. How should we resolve this tension? In this paper, I focus particularly on the logical omniscience requirement in Bayesian epistemology. Building on a key insight by Ian Hacking (1967), I develop a version of Bayesianism that permits logical ignorance. This includes an account of the synchronic norms that govern a logically ignorant individual at any given time, (...)
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  5. Belief Revision for Growing Awareness.Katie Steele & H. Orri Stefánsson - forthcoming - Mind.
    The Bayesian maxim for rational learning could be described as conservative change from one probabilistic belief or credence function to another in response to newinformation. Roughly: ‘Hold fixed any credences that are not directly affected by the learning experience.’ This is precisely articulated for the case when we learn that some proposition that we had previously entertained is indeed true (the rule of conditionalisation). But can this conservative-change maxim be extended to revising one’s credences in response to entertaining propositions or (...)
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  6. Beyond Uncertainty: Reasoning with Unknown Possibilities.Katie Steele & H. Orri Stefansson - forthcoming - Cambridge University Press.
    The main aim of this book is to introduce the topic of limited awareness, and changes in awareness, to those interested in the philosophy of decision-making and uncertain reasoning. (This is for the series Elements of Decision Theory published by Cambridge University Press and edited by Martin Peterson).
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  7. On the Origins of Old Evidence.Benjamin Eva & Stephan Hartmann - 2020 - Australasian Journal of Philosophy 98 (3):481-494.
    The problem of old evidence, first described by Glymour [1980], is still widely regarded as one of the most pressing foundational challenges to the Bayesian account of scientific reasoning. Many so...
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  8. Inductive Explanation and Garber–Style Solutions to the Problem of Old Evidence.David Kinney - 2017 - Synthese 196 (10):3995-4009.
    The Problem of Old Evidence is a perennial issue for Bayesian confirmation theory. Garber famously argues that the problem can be solved by conditionalizing on the proposition that a hypothesis deductively implies the existence of the old evidence. In recent work, Hartmann and Fitelson :712–717, 2015) and Sprenger :383–401, 2015) aim for similar, but more general, solutions to the Problem of Old Evidence. These solutions are more general because they allow the explanatory relationship between a new hypothesis and old evidence (...)
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  9. Inductive Explanation and Garber–Style Solutions to the Problem of Old Evidence.David Kinney - 2017 - Synthese:1-15.
    The Problem of Old Evidence is a perennial issue for Bayesian confirmation theory. Garber famously argues that the problem can be solved by conditionalizing on the proposition that a hypothesis deductively implies the existence of the old evidence. In recent work, Hartmann and Fitelson :712–717, 2015) and Sprenger :383–401, 2015) aim for similar, but more general, solutions to the Problem of Old Evidence. These solutions are more general because they allow the explanatory relationship between a new hypothesis and old evidence (...)
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  10. New Theory About Old Evidence. A Framework for Open-Minded Bayesianism.Sylvia9 Wenmackers & Jan-Willem Romeijn - 2016 - Synthese 193 (4).
    We present a conservative extension of a Bayesian account of confirmation that can deal with the problem of old evidence and new theories. So-called open-minded Bayesianism challenges the assumption—implicit in standard Bayesianism—that the correct empirical hypothesis is among the ones currently under consideration. It requires the inclusion of a catch-all hypothesis, which is characterized by means of sets of probability assignments. Upon the introduction of a new theory, the former catch-all is decomposed into a new empirical hypothesis and a new (...)
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  11. A Critical Introduction to Formal Epistemology.Darren Bradley - 2015 - London: Bloomsbury.
  12. A New Solution to the Problem of Old Evidence.Stephan Hartmann - 2014 - In Conference PSA 2014. Chicago, USA:
    The Problem of Old Evidence has troubled Bayesians ever since Clark Glymour first presented it in 1980. Several solutions have been proposed, but all of them have drawbacks and none of them is considered to be the definite solution. In this article, I propose a new solution which combines several old ideas with a new one. It circumvents the crucial omniscience problem in an elegant way and leads to a considerable confirmation of the hypothesis in question.
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  13. Bayesianism II: Applications and Criticisms.Kenny Easwaran - 2011 - Philosophy Compass 6 (5):321-332.
    In the first paper, I discussed the basic claims of Bayesianism (that degrees of belief are important, that they obey the axioms of probability theory, and that they are rationally updated by either standard or Jeffrey conditionalization) and the arguments that are often used to support them. In this paper, I will discuss some applications these ideas have had in confirmation theory, epistemol- ogy, and statistics, and criticisms of these applications.
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  14. Reconsidering Authority.Michael Strevens - 2010 - In Tamar Szabo Gendler & John Hawthorne (eds.), Oxford Studies in Epistemology Volume 3. Oxford University Press. pp. 294-330.
    How to regard the weight we give to a proposition on the grounds of its being endorsed by an authority? I examine this question as it is raised within the epistemology of science, and I argue that “authority-based weight” should receive special handling, for the following reason. Our assessments of other scientists’ competence or authority are nearly always provisional, in the sense that to save time and money, they are not made nearly as carefully as they could be---indeed, they are (...)
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  15. Goodman’s “New Riddle‘.Branden Fitelson - 2008 - Journal of Philosophical Logic 37 (6):613-643.
    First, a brief historical trace of the developments in confirmation theory leading up to Goodman's infamous "grue" paradox is presented. Then, Goodman's argument is analyzed from both Hempelian and Bayesian perspectives. A guiding analogy is drawn between certain arguments against classical deductive logic, and Goodman's "grue" argument against classical inductive logic. The upshot of this analogy is that the "New Riddle" is not as vexing as many commentators have claimed. Specifically, the analogy reveals an intimate connection between Goodman's problem, and (...)
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  16. Horgan on Sleeping Beauty.Joel Pust - 2008 - Synthese 160 (1):97 - 101.
    With the notable exception of David Lewis, most of those writing on the Sleeping Beauty problem have argued that 1/3 is the correct answer. Terence Horgan has provided the clearest account of why, contrary to Lewis, Beauty has evidence against the proposition that the coin comes up heads when she awakens on Monday. In this paper, I argue that Horgan’s proposal fails because it neglects important facts about epistemic probability.
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  17. Probabilistic Arguments for Multiple Universes.Kai Draper, Paul Draper & Joel Pust - 2007 - Pacific Philosophical Quarterly 88 (3):288–307.
    In this paper, we discuss three probabilistic arguments for the existence of multiple universes. First, we provide an analysis of total evidence and use that analysis to defend Roger White's "this universe" objection to a standard fine-tuning argument for multiple universes. Second, we explain why Rodney Holder's recent cosmological argument for multiple universes is unconvincing. Third, we develop a "Cartesian argument" for multiple universes. While this argument is not open to the objections previously noted, we show that, given certain highly (...)
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  18. Cartesian Knowledge and Confirmation.Joel Pust - 2007 - Journal of Philosophy 104 (6):269-289.
    Bayesian conceptions of evidence have been invoked in recent arguments regarding the existence of God, the hypothesis of multiple physical universes, and the Doomsday Argument. Philosophers writing on these topics often claim that, given a Bayesian account of evidence, our existence or something entailed by our existence (perhaps in conjunction with some background knowledge or assumption) may serve as evidence for each of us. In this paper, I argue that this widespread view is mistaken. The mere fact of one's existence (...)
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  19. Fine-Tuning is Not Surprising.Cory Juhl - 2006 - Analysis 66 (4):269-275.
    This paper is a response to Stephen Leeds’s "Juhl on Many Worlds". Contrary to what Leeds claims, we can legitimately argue for nontrivial conclusions by appeal to our existence. The ’problem of old evidence’, applied to the ’old evidence’ that we exist, seems to be a red herring in the context of determining whether there is a rationally convincing argument for the existence of many universes. A genuinely salient worry is whether multiversers can avoid illicit reuse of empirical evidence in (...)
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  20. God, Fine-Tuning, and the Problem of Old Evidence.Bradley Monton - 2006 - British Journal for the Philosophy of Science 57 (2):405-424.
    The fundamental constants that are involved in the laws of physics which describe our universe are finely-tuned for life, in the sense that if some of the constants had slightly different values life could not exist. Some people hold that this provides evidence for the existence of God. I will present a probabilistic version of this fine-tuning argument which is stronger than all other versions in the literature. Nevertheless, I will show that one can have reasonable opinions such that the (...)
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  21. Degree-of-Belief and Degree-of-Support: Why Bayesians Need Both Notions.James Hawthorne - 2005 - Mind 114 (454):277-320.
    I argue that Bayesians need two distinct notions of probability. We need the usual degree-of-belief notion that is central to the Bayesian account of rational decision. But Bayesians also need a separate notion of probability that represents the degree to which evidence supports hypotheses. Although degree-of-belief is well suited to the theory of rational decision, Bayesians have tried to apply it to the realm of hypothesis confirmation as well. This double duty leads to the problem of old evidence, a problem (...)
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  22. Subjective Probabilities as Basis for Scientific Reasoning?Franz Huber - 2005 - British Journal for the Philosophy of Science 56 (1):101-116.
    Bayesianism is the position that scientific reasoning is probabilistic and that probabilities are adequately interpreted as an agent's actual subjective degrees of belief, measured by her betting behaviour. Confirmation is one important aspect of scientific reasoning. The thesis of this paper is the following: if scientific reasoning is at all probabilistic, the subjective interpretation has to be given up in order to get right confirmation—and thus scientific reasoning in general. The Bayesian approach to scientific reasoning Bayesian confirmation theory The example (...)
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  23. The Old Evidence Problem and Agm Theory.Satoru Suzuki - 2005 - Annals of the Japan Association for Philosophy of Science 13 (2):105-126.
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  24. Three Models of Sequential Belief Updating on Uncertain Evidence.James Hawthorne - 2004 - Journal of Philosophical Logic 33 (1):89-123.
    Jeffrey updating is a natural extension of Bayesian updating to cases where the evidence is uncertain. But, the resulting degrees of belief appear to be sensitive to the order in which the uncertain evidence is acquired, a rather un-Bayesian looking effect. This order dependence results from the way in which basic Jeffrey updating is usually extended to sequences of updates. The usual extension seems very natural, but there are other plausible ways to extend Bayesian updating that maintain order-independence. I will (...)
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  25. Review: The Foundations of Causal Decision Theory. [REVIEW]Branden Fitelson - 2003 - Mind 112 (447):545-551.
  26. Comments and Criticism: Measuring Confirmation and Evidence.Ellery Eells & Branden Fitelson - 2000 - Journal of Philosophy 97 (12):663-672.
    Bayesian epistemology suggests various ways of measuring the support that a piece of evidence provides a hypothesis. Such measures are defined in terms of a subjective probability assignment, pr, over propositions entertained by an agent. The most standard measure (where “H” stands for “hypothesis” and “E” stands for “evidence”) is: the difference measure: d(H,E) = pr(H/E) - pr(H).0 This may be called a “positive (probabilistic) relevance measure” of confirmation, since, according to it, a piece of evidence E qualitatively confirms a (...)
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  27. Knowledge and its Limits.Timothy Williamson - 2000 - Oxford University Press.
    Knowledge and its Limits presents a systematic new conception of knowledge as a kind of mental stage sensitive to the knower's environment. It makes a major contribution to the debate between externalist and internalist philosophies of mind, and breaks radically with the epistemological tradition of analyzing knowledge in terms of true belief. The theory casts new light on such philosophical problems as scepticism, evidence, probability and assertion, realism and anti-realism, and the limits of what can be known. The arguments are (...)
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  28. The Quantitative Problem of Old Evidence.E. C. Barnes - 1999 - British Journal for the Philosophy of Science 50 (2):249-264.
    The quantitative problem of old evidence is the problem of how to measure the degree to which e confirms h for agent A at time t when A regards e as justified at t. Existing attempts to solve this problem have applied the e-difference approach, which compares A's probability for h at t with what probability A would assign h if A did not regard e as justified at t. The quantitative problem has been widely regarded as unsolvable primarily on (...)
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  29. Measuring Confirmation.David Christensen - 1999 - Journal of Philosophy 96 (9):437-461.
  30. The Foundations of Causal Decision Theory.James M. Joyce - 1999 - Cambridge University Press.
    This book defends the view that any adequate account of rational decision making must take a decision maker's beliefs about causal relations into account. The early chapters of the book introduce the non-specialist to the rudiments of expected utility theory. The major technical advance offered by the book is a 'representation theorem' that shows that both causal decision theory and its main rival, Richard Jeffrey's logic of decision, are both instances of a more general conditional decision theory. The book solves (...)
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  31. Old Evidence and New Explanation II.Carl G. Wagner - 1999 - Philosophy of Science 66 (2):283-288.
    Additional results are reported on the author's earlier generalization of Richard Jeffrey's solution to the problem of old evidence and new explanation.
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  32. Old Evidence and New Explanation.Carl G. Wagner - 1997 - Philosophy of Science 64 (4):677-691.
    Jeffrey has devised a probability revision method that increases the probability of hypothesis H when it is discovered that H implies previously known evidence E. A natural extension of Jeffrey's method likewise increases the probability of H when E has been established with sufficiently high probability and it is then discovered, quite apart from this, that H confers sufficiently higher probability on E than does its logical negation H̄.
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  33. Subjective and Objective Confirmation.Patrick Maher - 1996 - Philosophy of Science 63 (2):149-174.
    Confirmation is commonly identified with positive relevance, E being said to confirm H if and only if E increases the probability of H. Today, analyses of this general kind are usually Bayesian ones that take the relevant probabilities to be subjective. I argue that these subjective Bayesian analyses are irremediably flawed. In their place I propose a relevance analysis that makes confirmation objective and which, I show, avoids the flaws of the subjective analyses. What I am proposing is in some (...)
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  34. Scientific Reasoning: The Bayesian Approach.Peter Urbach & Colin Howson - 1993 - Open Court.
    Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...
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  35. Bayes or Bust?John Earman - 1992 - Bradford.
    There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. (...)
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  36. Bayes or Bust? A Critical Examination of Bayesian Confirmation Theory.John Earman - 1992 - MIT Press.
    There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes’s original paper to contemporary formal learning theory.In (...)
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  37. Problems of Old Evidence.Ellery Eells - 1985 - Pacific Philosophical Quarterly 66 (3):283.
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  38. A Historical Comment Concerning Novel Confirmation.I. J. Good - 1985 - British Journal for the Philosophy of Science 36 (2):184-185.
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  39. Testing Scientific Theories.John Earman (ed.) - 1984 - Minneapolis: University of Minnesota Press.
    Rich with historical and cultural value, these works are published unaltered from the original University of Minnesota Press editions.
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  40. Theory and Evidence.Clark Glymour - 1980 - Princeton University Press.
  41. Old Evidence Again.Simon Evnine - manuscript
    A critique of Mark Kaplan's attempt to solve the problem of old evidence by restricting the principle of when something is evidence explicitly to cases in which we are less than certain of it.
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  42. Comments on Carl Wagner's Jeffrey Conditioning and External Bayesianity.Steve Petersen - manuscript
    Jeffrey conditioning allows updating in Bayesian style when the evidence is uncertain. A weighted average, essentially, over classically updating on the alternatives. Unlike classical Bayesian conditioning, this allows learning to be unlearned.
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  43. Surprise and Evidence in Statistical Model Checking.Jan Sprenger - unknown
    There is considerable confusion about the role of p-values in statistical model checking. To clarify that point, I introduce the distinction between measures of surprise and measures of evidence which come with different epistemological functions. I argue that p-values, often understood as measures of evidence against a null model, do not count as proper measures of evidence and are closer to measures of surprise. Finally, I sketch how the problem of old evidence may be tackled by acknowledging the epistemic role (...)
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