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1952 found
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  1. Geometric Pooling: A User's Guide.Richard Pettigrew & Jonathan Weisberg - forthcoming - British Journal for the Philosophy of Science.
    Much of our information comes to us indirectly, in the form of conclusions others have drawn from evidence they gathered. When we hear these conclusions, how can we modify our own opinions so as to gain the benefit of their evidence? In this paper we study the method known as geometric pooling. We consider two arguments in its favour, raising several objections to one, and proposing an amendment to the other.
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  2. Knowledge in Action.Jonathan Weisberg - 2013 - Philosophers' Imprint 13.
    Recent proposals that frame norms of action in terms of knowledge have been challenged by Bayesian decision theorists. Bayesians object that knowledge-based norms conflict with the highly successful and established view that rational action is rooted in degrees of belief. I argue that the knowledge-based and Bayesian pictures are not as incompatible as these objectors have made out. Attending to the mechanisms of practical reasoning exposes space for both knowledge and degrees of belief to play their respective roles.
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  3. New Boundary Lines.Alejandro Pérez Carballo - manuscript
    Intellectual progress involves forming a more accurate picture of the world. But it also figuring out which concepts to use for theorizing about the world. Bayesian epistemology has had much to say about the former aspect of our cognitive lives, but little if at all about the latter. I outline a framework for formulating questions about conceptual change in a broadly Bayesian framework. By enriching the resources of Epistemic Utility Theory with a more expansive conception of epistemic value, I offer (...)
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  4. An Even Better Solution to the Paradox of the Ravens.James Hawthorne & Branden Fitelson - manuscript
    Think of confirmation in the context of the Ravens Paradox this way. The likelihood ratio measure of incremental confirmation gives us, for an observed Black Raven and for an observed non-Black non-Raven, respectively, the following “full” likelihood ratios.
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  5. The Literalist Fallacy & the Free Energy Principle: Model building, Scientific Realism and Instrumentalism.Michael David Kirchhoff, Julian Kiverstein & Ian Robertson - manuscript
    Disagreement about how best to think of the relation between theories and the realities they represent has a longstanding and venerable history. We take up this debate in relation to the free energy principle (FEP) - a contemporary framework in computational neuroscience, theoretical biology and the philosophy of cognitive science. The FEP is very ambitious, extending from the brain sciences to the biology of self-organisation. In this context, some find apparent discrepancies between the map (the FEP) and the territory (target (...)
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  6. Causal Modeling Semantics for Counterfactuals with Disjunctive Antecedents.Giuliano Rosella & Jan Sprenger - manuscript
    Causal Modeling Semantics (CMS, e.g., Galles and Pearl 1998; Pearl 2000; Halpern 2000) is a powerful framework for evaluating counterfactuals whose antecedent is a conjunction of atomic formulas. We extend CMS to an evaluation of the probability of counterfactuals with disjunctive antecedents, and more generally, to counterfactuals whose antecedent is an arbitrary Boolean combination of atomic formulas. Our main idea is to assign a probability to a counterfactual (A ∨ B) > C at a causal model M as a weighted (...)
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  7. Confirmation by Explanation: A Bayesian Justification of IBE.Marko Tesic, Benjamin Eva & Stephan Hartmann - manuscript
    We provide a novel Bayesian justification of inference to the best explanation. More specifically, we present conditions under which explanatory considerations can provide a significant confirmatory boost for hypotheses that provide the best explanation of the relevant evidence. Furthermore, we show that the proposed Bayesian model of IBE is able to deal naturally with the best known criticisms of IBE such as van Fraassen?s?bad lot? argument.
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  8. Plausible Permissivism.Michael G. Titelbaum & Matthew Kopec - manuscript
    Abstract. Richard Feldman’s Uniqueness Thesis holds that “a body of evidence justifies at most one proposition out of a competing set of proposi- tions”. The opposing position, permissivism, allows distinct rational agents to adopt differing attitudes towards a proposition given the same body of evidence. We assess various motivations that have been offered for Uniqueness, including: concerns about achieving consensus, a strong form of evidentialism, worries about epistemically arbitrary influences on belief, a focus on truth-conduciveness, and consequences for peer disagreement. (...)
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  9. Can knowledge be justified true belief? (Pdf 69k).Ken Binmore - manuscript
    Knowledge was traditionally held to be justified true belief. This paper examines the implications of maintaining this view if justication is interpreted algorithmically. It is argued that if we move sufficiently far from the small worlds to which Bayesian decision theory properly applies, we can steer between the rock of fallibilism and the whirlpool of skepticism only by explicitly building into our framing of the underlying decision problem the possibility that its attempt to describe the world is inadequate.
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  10. Making decisions in large worlds (pdf 141k).Ken Binmore - manuscript
    This paper argues that we need to look beyond Bayesian decision theory for an answer to the general problem of making rational decisions under uncertainty. The view that Bayesian decision theory is only genuinely valid in a small world was asserted very firmly by Leonard Savage [18] when laying down the principles of the theory in his path-breaking Foundations of Statistics. He makes the distinction between small and large worlds in a folksy way by quoting the proverbs ”Look before you (...)
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  11. Inductive rules are no problem.Daniel Steel - manuscript
    This essay defends the view that inductive reasoning involves following inductive rules against objections that inductive rules are undesirable because they ignore background knowledge and unnecessary because Bayesianism is not an inductive rule. I propose that inductive rules be understood as sets of functions from data to hypotheses that are intended as solutions to inductive problems. According to this proposal, background knowledge is important in the application of inductive rules and Bayesianism qualifies as an inductive rule. Finally, I consider a (...)
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  12. Bayesian epistemology.Robert Williams - manuscript
    Synthese 156 (3) (2007). Special issue ed. with Luc Bovens. With contributions by Max Albert, Branden Fitelson, Dennis Dieks, Igor Douven and Wouter Meijs, Alan Hájek, Colin Howson, James Joyce, and Patrick Suppes.
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  13. A Basic Course in Probability Theory.Rabi Bhattacharya & Edward C. Waymire - forthcoming - Analysis.
    The book develops the necessary background in probability theory underlying diverse treatments of stochastic processes and their wide-ranging applications. With this goal in mind, the pace is lively, yet thorough. Basic notions of independence and conditional expectation are introduced relatively early on in the text, while conditional expectation is illustrated in detail in the context of martingales, Markov property and strong Markov property. Weak convergence of probabilities on metric spaces and Brownian motion are two highlights. The historic role of size-biasing (...)
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  14. An Epistemic Advantage of Accommodation over Prediction.Finnur Dellsén - forthcoming - Philosophers' Imprint.
    Many philosophers have argued that a hypothesis is better confirmed by some data if the hypothesis was not specifically designed to fit the data. ‘Prediction’, they argue, is superior to ‘accommodation’. Others deny that there is any epistemic advantage to prediction, and conclude that prediction and accommodation are epistemically on a par. This paper argues that there is a respect in which accommodation is superior to prediction. Specifically, the information that the data was accommodated rather than predicted suggests that the (...)
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  15. Broadband or Bust!George F. Gilder & John Wohlstetter - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
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  16. Reasonable Doubt and Alternative Hypotheses: A Bayesian Analysis.Stephan Hartmann & Ulrike Hahn - forthcoming - Journal.
    A longstanding question is the extent to which "reasonable doubt" may be expressed simply in terms of a threshold degree of belief. In this context, we examine the extent to which learning about possible alternatives may alter one's beliefs about a target hypothesis, even when no new "evidence" linking them to the hypothesis is acquired. Imagine the following scenario: a crime has been committed and Alice, the police's main suspect has been brought to trial. There are several pieces of evidence (...)
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  17. Prediction error minimization, mental and developmental disorder, and statistical theories of consciousness.Jakob Hohwy - forthcoming - In Rocco Gennaro (ed.), Disturbed Consciousness: New Essays on Psychopathology and Theories of Consciousness. MIT Press.
    This chapter seeks to recover an approach to consciousness from a general theory of brain function, namely the prediction error minimization theory. The way this theory applies to mental and developmental disorder demonstrates its relevance to consciousness. The resulting view is discussed in relation to a contemporary theory of consciousness, namely the idea that conscious perception depends on Bayesian metacognition; this theory is also supported by considerations of psychopathology. This Bayesian theory is first disconnected from the higher-order thought theory, and (...)
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  18. Know Your Way Out of St. Petersburg: An Exploration of "Knowledge-First" Decision Theory.Frank Hong - forthcoming - Erkenntnis:1-20.
    This paper explores the consequences of applying two natural ideas from epistemology to decision theory: (1) that knowledge should guide our actions, and (2) that we know a lot of non-trivial things. In particular, we explore the consequences of these ideas as they are applied to standard decision theoretic puzzles such as the St. Petersburg Paradox. In doing so, we develop a “knowledge-first” decision theory and we will see how it can help us avoid fanaticism with regard to the St. (...)
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  19. Hydrography: Compiling and updating the nautical chart.B. Hutton - forthcoming - Veritas – Revista de Filosofia da Pucrs.
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  20. How should your beliefs change when your awareness grows?Richard Pettigrew - forthcoming - Episteme:1-25.
    Epistemologists who study credences have a well-developed account of how you should change them when you learn new evidence; that is, when your body of evidence grows. What's more, they boast a diverse range of epistemic and pragmatic arguments that support that account. But they do not have a satisfactory account of when and how you should change your credences when you become aware of possibilities and propositions you have not entertained before; that is, when your awareness grows. In this (...)
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  21. Which Models of Scientific Explanation are (In)Compatible with IBE?Yunus Prasetya - forthcoming - British Journal for the Philosophy of Science.
    In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Philip Kitcher’s unificationist account supports IBE; Peter Railton’s deductive-nomological-probabilistic model, Wesley Salmon’s statistical-relevance Model, and Bas van (...)
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  22. Bayesian Norms and Non-Ideal Agents.Julia Staffel - forthcoming - In Maria Lasonen-Aarnio & Clayton M. Littlejohn (eds.), Routledge Handbook of the Philosophy Evidence. Routledge.
    Bayesian epistemology provides a popular and powerful framework for modeling rational norms on credences, including how rational agents should respond to evidence. The framework is built on the assumption that ideally rational agents have credences, or degrees of belief, that are representable by numbers that obey the axioms of probability. From there, further constraints are proposed regarding which credence assignments are rationally permissible, and how rational agents’ credences should change upon learning new evidence. While the details are hotly disputed, all (...)
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  23. Bayes, God, and the Multiverse.Richard Swinburne - forthcoming - Philosophical Explorations.
  24. Epistemic Probabilities are Degrees of Support, not Degrees of (Rational) Belief.Nevin Climenhaga - 2024 - Philosophy and Phenomenological Research 108 (1):153-176.
    I argue that when we use ‘probability’ language in epistemic contexts—e.g., when we ask how probable some hypothesis is, given the evidence available to us—we are talking about degrees of support, rather than degrees of belief. The epistemic probability of A given B is the mind-independent degree to which B supports A, not the degree to which someone with B as their evidence believes A, or the degree to which someone would or should believe A if they had B as (...)
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  25. Fine-Tuning Should Make Us More Confident that Other Universes Exist.Bradford Saad - 2024 - American Philosophical Quarterly 61 (1):29-44.
    This paper defends the view that discovering that our universe is fine-tuned should make us more confident that other universes exist. My defense exploits a distinction between ideal and non-ideal evidential support. I use that distinction in concert with a simple model to disarm the most influential objection—the this-universe objection—to the view that fine-tuning supports the existence of other universes. However, the simple model fails to capture some important features of our epistemic situation with respect to fine-tuning. To capture these (...)
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  26. Probability and Informed Consent.Nir Ben-Moshe, Benjamin A. Levinstein & Jonathan Livengood - 2023 - Theoretical Medicine and Bioethics 44 (6):545-566.
    In this paper, we illustrate some serious difficulties involved in conveying information about uncertain risks and securing informed consent for risky interventions in a clinical setting. We argue that in order to secure informed consent for a medical intervention, physicians often need to do more than report a bare, numerical probability value. When probabilities are given, securing informed consent generally requires communicating how probability expressions are to be interpreted and communicating something about the quality and quantity of the evidence for (...)
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  27. 'Logic Will Get You From A to B, Imagination Will Take You Anywhere'.Francesco Berto - 2023 - Noûs.
    There is some consensus on the claim that imagination as suppositional thinking can have epistemic value insofar as it’s constrained by a principle of minimal alteration of how we know or believe reality to be – compatibly with the need to accommodate the supposition initiating the imaginative exercise. But in the philosophy of imagination there is no formally precise account of how exactly such minimal alteration is to work. I propose one. I focus on counterfactual imagination, arguing that this can (...)
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  28. Downwards Propriety in Epistemic Utility Theory.Alejandro Pérez Carballo - 2023 - Mind 132 (525):30-62.
    Epistemic Utility Theory is often identified with the project of *axiology-first epistemology*—the project of vindicating norms of epistemic rationality purely in terms of epistemic value. One of the central goals of axiology-first epistemology is to provide a justification of the central norm of Bayesian epistemology, Probabilism. The first part of this paper presents a new challenge to axiology first epistemology: I argue that in order to justify Probabilism in purely axiological terms, proponents of axiology first epistemology need to justify a (...)
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  29. The comparison problem for approximating epistemic ideals.Marc-Kevin Daoust - 2023 - Ratio 36 (1):22-31.
    Some epistemologists think that the Bayesian ideals matter because we can approximate them. That is, our attitudes can be more or less close to the ones of our ideal Bayesian counterpart. In this paper, I raise a worry for this justification of epistemic ideals. The worry is this: In order to correctly compare agents to their ideal counterparts, we need to imagine idealized agents who have the same relevant information, knowledge, or evidence. However, there are cases in which one’s ideal (...)
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  30. Updating without evidence.Yoaav Isaacs & Jeffrey Sanford Russell - 2023 - Noûs 57 (3):576-599.
    Sometimes you are unreliable at fulfilling your doxastic plans: for example, if you plan to be fully confident in all truths, probably you will end up being fully confident in some falsehoods by mistake. In some cases, there is information that plays the classical role of evidence—your beliefs are perfectly discriminating with respect to some possible facts about the world—and there is a standard expected‐accuracy‐based justification for planning to conditionalize on this evidence. This planning‐oriented justification extends to some cases where (...)
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  31. Epistemic Entitlement, Epistemic Risk and Leaching.Luca Moretti & Crispin Wright - 2023 - Philosophy and Phenomenological Research 106 (3):566-580.
    One type of argument to sceptical paradox proceeds by making a case that a certain kind of metaphysically “heavyweight or “cornerstone” proposition is beyond all possible evidence and hence may not be known or justifiably believed. Crispin Wright has argued that we can concede that our acceptance of these propositions is evidentially risky and still remain rationally entitled to those of our ordinary knowledge claims that are seemingly threatened by that concession. A problem for Wright’s proposal is the so-called Leaching (...)
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  32. Why We Doubt: A Cognitive Account of Our Skeptical Inclinations.N. Ángel Pinillos - 2023 - Oxford: Oxford University Press.
    This book, the first of its kind, puts forward a novel, unified cognitive account of skeptical doubt. Historically, most philosophers have tried to tackle this difficult topic by directly arguing that skeptical doubt is false. But N. Ángel Pinillos does something different. He begins by trying to uncover the hidden mental rule which, for better or worse, motivates our skeptical inclinations. He then gives an account of the broader cognitive purpose of having and applying this rule. Based on these ideas, (...)
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  33. Probability without Tears.Julia Staffel - 2023 - Teaching Philosophy 46 (1):65-84.
    This paper is about teaching probability to students of philosophy who don’t aim to do primarily formal work in their research. These students are unlikely to seek out classes about probability or formal epistemology for various reasons, for example because they don’t realize that this knowledge would be useful for them or because they are intimidated by the material. However, most areas of philosophy now contain debates that incorporate probability, and basic knowledge of it is essential even for philosophers whose (...)
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  34. Essential materials for Bayesian Mindsponge Framework analytics.Aisdl Team - 2023 - Sm3D Science Portal.
    Acknowledging that many members of the SM3D Portal need reference documents related to Bayesian Mindsponge Framework (BMF) analytics to conduct research projects effectively, we present the essential materials and most up-to-date studies employing the method in this post. By summarizing all the publications and preprints associated with BMF analytics, we also aim to help researchers reduce the time and effort for information seeking, enhance proactive self-learning, and facilitate knowledge exchange and community dialogue through transparency.
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  35. Ad hocness, accommodation and consilience: a Bayesian account.John Wilcox - 2023 - Synthese 201 (2):1-42.
    All of us, including scientists, make judgments about what is true or false, probable or improbable. And in the process, we frequently appeal to concepts such as evidential support or explanation. Bayesian philosophers of science have given illuminating formal accounts of these concepts. This paper aims to follow in their footsteps, providing a novel formal account of various additional concepts: the likelihood-prior trade-off, successful accommodation of evidence, ad hocness, and, finally, consilience—sometimes also called “unification”. Using these accounts, I also provide (...)
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  36. Answering More of the Same: A Reply to Nahm.Keith Augustine - 2022 - Journal of Scientific Exploration 36 (4):794-808.
    Michael Nahm's preceding commentary accuses me of seven misrepresentations. One of these is an acknowledged good-faith error about a peripheral detail, while the remaining six are demonstrably accurate descriptions of Nahm's statements. At the same time, Nahm verifiably misrepresents me frequently and intentionally over issues that he takes to be consequential, which is a much more serious offense. All authors should call out when an interlocutor get their points wrong, but only when they can definitively back up the charge. Where (...)
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  37. The Landscape of Affective Meaning.Víctor Carranza-Pinedo - 2022 - Dissertation, Institut Jean Nicod
    Swear words are highly colloquial expressions that have the capacity to signal the speaker's affective states, i.e., to display the speaker's feelings with respect to a certain stimulus. For this reason, swear words are often called 'expressives'. Which linguistic mechanisms allow swear words display affective states, and, more importantly, how can such 'affective content' be characterized in a theory of meaning? Even though research on expressive meaning has produced models that integrate the affective aspects of swear words in a compositional (...)
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  38. A Phenomenological Approach to the Bayesian Grue Problem.Ibrahim Dagher - 2022 - Aporia 22 (1):1-12.
    It is a common intuition in scientific practice that positive instances confirm. This confirmation, at least based purely on syntactic considerations, is what Nelson Goodman’s ‘Grue Problem’, and more generally the ‘New Riddle’ of Induction, attempt to defeat. One treatment of the Grue Problem has been made along Bayesian lines, wherein the riddle reduces to a question of probability assignments. In this paper, I consider this so-called Bayesian Grue Problem and evaluate how one might proffer a solution to this problem (...)
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  39. Degrees of Acceptance.Alexander Dinges - 2022 - Philosophical Quarterly (3):578-594.
    While many authors distinguish belief from acceptance, it seems almost universally agreed that no similar distinction can be drawn between degrees of belief, or credences, and degrees of acceptance. I challenge this assumption in this paper. Acceptance comes in degrees and acknowledging this helps to resolve problems in at least two philosophical domains. Degrees of acceptance play vital roles when we simplify our reasoning, and they ground the common ground of a conversation if we assume context probabilism, i.e., that the (...)
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  40. Inductive risk: does it really refute value-freedom?Markus Dressel - 2022 - Theoria 37 (2):181-207.
    The argument from inductive risk is considered to be one of the strongest challenges for value-free science. A great part of its appeal lies in the idea that even an ideal epistemic agent—the “perfect scientist” or “scientist qua scientist”—cannot escape inductive risk. In this paper, I scrutinize this ambition by stipulating an idealized Bayesian decision setting. I argue that inductive risk does not show that the “perfect scientist” must, descriptively speaking, make non-epistemic value-judgements, at least not in a way that (...)
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  41. Late scholastic probable arguments and their contrast with rhetorical and demonstrative arguments.James Franklin - 2022 - Philosophical Inquiries 10 (2).
    Aristotle divided arguments that persuade into the rhetorical (which happen to persuade), the dialectical (which are strong so ought to persuade to some degree) and the demonstrative (which must persuade if rightly understood). Dialectical arguments were long neglected, partly because Aristotle did not write a book about them. But in the sixteenth and seventeenth century late scholastic authors such as Medina, Cano and Soto developed a sound theory of probable arguments, those that have logical and not merely psychological force but (...)
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  42. Scientific Theories as Bayesian Nets: Structure and Evidence Sensitivity.Patrick Grim, Frank Seidl, Calum McNamara, Hinton E. Rago, Isabell N. Astor, Caroline Diaso & Peter Ryner - 2022 - Philosophy of Science 89 (1):42-69.
    We model scientific theories as Bayesian networks. Nodes carry credences and function as abstract representations of propositions within the structure. Directed links carry conditional probabilities and represent connections between those propositions. Updating is Bayesian across the network as a whole. The impact of evidence at one point within a scientific theory can have a very different impact on the network than does evidence of the same strength at a different point. A Bayesian model allows us to envisage and analyze the (...)
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  43. (Almost) all evidence is higher-order evidence.Brian Hedden & Kevin Dorst - 2022 - Analysis 82 (3):417-425.
    Higher-order evidence is evidence about what is rational to think in light of your evidence. Many have argued that it is special – falling into its own evidential category, or leading to deviations from standard rational norms. But it is not. Given standard assumptions, almost all evidence is higher-order evidence.
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  44. Multiple Universes and Self-Locating Evidence.Yoaav Isaacs, John Hawthorne & Jeffrey Sanford Russell - 2022 - Philosophical Review 131 (3):241-294.
    Is the fact that our universe contains fine-tuned life evidence that we live in a multiverse? Ian Hacking and Roger White influentially argue that it is not. We approach this question through a systematic framework for self-locating epistemology. As it turns out, leading approaches to self-locating evidence agree that the fact that our own universe contains fine-tuned life indeed confirms the existence of a multiverse. This convergence is no accident: we present two theorems showing that, in this setting, any updating (...)
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  45. Immortal Beauty: Does Existence Confirm Reincarnation?Jens Jäger - 2022 - Australasian Journal of Philosophy 100 (4):789-807.
    I argue that a popular view about self-locating evidence implies that there are cases in which agents have surprisingly strong evidence for their own reincarnation. The central case is an ‘Immortal Beauty' scenario, modelled after the well-known Sleeping Beauty puzzle. I argue that if the popular ‘thirder’ solution to the puzzle is correct, then Immortal Beauty should be confident that she's going to be reincarnated. The essay also examines another pro-reincarnation argument due to Michael Huemer (2021). I argue that his (...)
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  46. The World From Within: An Investigation into the Hard Problem of Consciousness from the Perspective of Bayesian Cognitive Science.Peter Kuhn - 2022 - Dissertation, Goethe University Frankfurt
    The thesis develops a naturalist theory of phenomenal consciousness. The argument proceeds in three broad steps. The first consists in a defense of a representationalist view of consciousness. The second part argues that the relevant form of mental representation can be explained in terms of the predictive processing approach to brain function. The final part consists in an attack on metaphysical realism inspired by Bayesian approaches to cognition and a discussion of the implications of metaphysical anti-realism for the hard problem (...)
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  47. Is an Increase in Probability Always an Increase in Evidential Support?Artūrs Https://Orcidorg Logins - 2022 - Erkenntnis 87 (3):1231-1255.
    Peter Achinstein has argued at length and on many occasions that the view according to which evidential support is defined in terms of probability-raising faces serious counterexamples and, hence, should be abandoned. Proponents of the positive probabilistic relevance view have remained unconvinced. The debate seems to be in a deadlock. This paper is an attempt to move the debate forward and revisit some of the central claims within this debate. My conclusion here will be that while Achinstein may be right (...)
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  48. The Material Theory of Induction, by John Norton. [REVIEW]William Peden - 2022 - BJPS Review of Books.
    Even prior to its publication, John Norton’s book has stimulated debates about induction. Its publication will galvanize these discussions. Does it merit all this attention? Yes, and not just from philosophers of science. Practically all philosophers will find novel and thought-provoking ideas, with implications for their research.
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  49. Bayesian belief protection: A study of belief in conspiracy theories.Nina Poth & Krzysztof Dolega - 2022 - Philosophical Psychology.
    Several philosophers and psychologists have characterized belief in conspiracy theories as a product of irrational reasoning. Proponents of conspiracy theories apparently resist revising their beliefs given disconfirming evidence and tend to believe in more than one conspiracy, even when the relevant beliefs are mutually inconsistent. In this paper, we bring leading views on conspiracy theoretic beliefs closer together by exploring their rationality under a probabilistic framework. We question the claim that the irrationality of conspiracy theoretic beliefs stems from an inadequate (...)
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  50. That’s Not IBE: Reply to Park.Yunus Prasetya - 2022 - Axiomathes 32 (2):621-627.
    Park (2017, 2018, 2019) argues that Bas van Fraassen uses inference to the best explanation to defend his contextual theory of explanation. If Park is right, then van Fraassen is in trouble because he rejects IBE as a rational rule of inference. In this reply, I argue that van Fraassen does not use IBE in defending the contextual theory of explanation. I distinguish between several conceptions of IBE: heuristic IBE, objective Bayesian IBE, and ampliative IBE. I argue that van Fraassen (...)
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