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  1. The Legitimate Route to the Scientific Truth - The Gondor Principle.Joseph Krecz - manuscript
    We leave in a beautiful and uniform world, a world where everything probable is possible. Since the epic theory of relativity many scientists have embarked in a pursuit of astonishing theoretical fantasies, abandoning the prudent and logical path to scientific inquiry. The theory is a complex theoretical framework that facilitates the understanding of the universal laws of physics. It is based on the space-time continuum fabric abstract concept, and it is well suited for interpreting cosmic events. However, it is not (...)
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  2. Justification, Normalcy and Evidential Probability.Martin Smith - manuscript
    NOTE: This paper is a reworking of some aspects of an earlier paper – ‘What else justification could be’ and also an early draft of chapter 2 of Between Probability and Certainty. I'm leaving it online as it has a couple of citations and there is some material here which didn't make it into the book (and which I may yet try to develop elsewhere). My concern in this paper is with a certain, pervasive picture of epistemic justification. On this (...)
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  3. Higher-Order Uncertainty.Kevin Dorst - forthcoming - In Mattias Skipper & Asbjørn Steglich Petersen (eds.), Higher-Order Evidence: New Essays.
    You have higher-order uncertainty iff you are uncertain of what opinions you should have. I defend three claims about it. First, the higher-order evidence debate can be helpfully reframed in terms of higher-order uncertainty. The central question becomes how your first- and higher-order opinions should relate—a precise question that can be embedded within a general, tractable framework. Second, this question is nontrivial. Rational higher-order uncertainty is pervasive, and lies at the foundations of the epistemology of disagreement. Third, the answer is (...)
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  4. Against Legal Probabilism.Martin Smith - forthcoming - In Jon Robson & Zachary Hoskins (eds.), The Social Epistemology of Legal Trials. Routledge.
    Is it right to convict a person of a crime on the basis of purely statistical evidence? Many who have considered this question agree that it is not, posing a direct challenge to legal probabilism – the claim that the criminal standard of proof should be understood in terms of a high probability threshold. Some defenders of legal probabilism have, however, held their ground: Schoeman (1987) argues that there are no clear epistemic or moral problems with convictions based on purely (...)
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  5. Civil Liability and the 50%+ Standard of Proof.Martin Smith - forthcoming - International Journal of Evidence and Proof.
    The standard of proof applied in civil trials is the preponderance of evidence, often said to be met when a proposition is shown to be more than 50% likely to be true. A number of theorists have argued that this 50%+ standard is too weak – there are circumstances in which a court should find that the defendant is not liable, even though the evidence presented makes it more than 50% likely that the plaintiff’s claim is true. In this paper, (...)
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  6. Evidence: A Guide for the Uncertain.Kevin Dorst - 2020 - Philosophy and Phenomenological Research 100 (3):586-632.
    Assume that it is your evidence that determines what opinions you should have. I argue that since you should take peer disagreement seriously, evidence must have two features. (1) It must sometimes warrant being modest: uncertain what your evidence warrants, and (thus) uncertain whether you’re rational. (2) But it must always warrant being guided: disposed to treat your evidence as a guide. Surprisingly, it is very difficult to vindicate both (1) and (2). But diagnosing why this is so leads to (...)
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  7. Varieties of Risk.Philip A. Ebert, Martin Smith & Ian Durbach - 2020 - Philosophy and Phenomenological Research 101 (2):432-455.
    The notion of risk plays a central role in economics, finance, health, psychology, law and elsewhere, and is prevalent in managing challenges and resources in day-to-day life. In recent work, Duncan Pritchard (2015, 2016) has argued against the orthodox probabilistic conception of risk on which the risk of a hypothetical scenario is determined by how probable it is, and in favour of a modal conception on which the risk of a hypothetical scenario is determined by how modally close it is. (...)
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  8. Structuring Decisions Under Deep Uncertainty.Casey Helgeson - 2020 - Topoi 39 (2):257-269.
    Innovative research on decision making under ‘deep uncertainty’ is underway in applied fields such as engineering and operational research, largely outside the view of normative theorists grounded in decision theory. Applied methods and tools for decision support under deep uncertainty go beyond standard decision theory in the attention that they give to the structuring of decisions. Decision structuring is an important part of a broader philosophy of managing uncertainty in decision making, and normative decision theorists can both learn from, and (...)
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  9. Bayesian Decision Theory and Stochastic Independence.Philippe Mongin - 2020 - Philosophy of Science 87 (1):152-178.
    As stochastic independence is essential to the mathematical development of probability theory, it seems that any foundational work on probability should be able to account for this property. Bayesian decision theory appears to be wanting in this respect. Savage’s postulates on preferences under uncertainty entail a subjective expected utility representation, and this asserts only the existence and uniqueness of a subjective probability measure, regardless of its properties. What is missing is a preference condition corresponding to stochastic independence. To fill this (...)
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  10. Comparative Infinite Lottery Logic.Matthew W. Parker - 2020 - Studies in History and Philosophy of Science Part A 84:28-36.
    As an application of his Material Theory of Induction, Norton (2018; manuscript) argues that the correct inductive logic for a fair infinite lottery, and also for evaluating eternal inflation multiverse models, is radically different from standard probability theory. This is due to a requirement of label independence. It follows, Norton argues, that finite additivity fails, and any two sets of outcomes with the same cardinality and co-cardinality have the same chance. This makes the logic useless for evaluating multiverse models based (...)
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  11. Inductive Logic From the Viewpoint of Quantum Information.Vasil Penchev - 2020 - Logic and Philosophy of Mathematics eJournal (Elsevier: SSRN) 12 (13):1-2.
    The resolving of the main problem of quantum mechanics about how a quantum leap and a smooth motion can be uniformly described resolves also the problem of how a distribution of reliable data and a sequence of deductive conclusions can be uniformly described by means of a relevant wave function “Ψdata”.
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  12. Believing Probabilistic Contents: On the Expressive Power and Coherence of Sets of Sets of Probabilities.Catrin Campbell-Moore & Jason Konek - 2019 - Analysis Reviews:anz076.
    Moss (2018) argues that rational agents are best thought of not as having degrees of belief in various propositions but as having beliefs in probabilistic contents, or probabilistic beliefs. Probabilistic contents are sets of probability functions. Probabilistic belief states, in turn, are modeled by sets of probabilistic contents, or sets of sets of probability functions. We argue that this Mossean framework is of considerable interest quite independently of its role in Moss’ account of probabilistic knowledge or her semantics for epistemic (...)
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  13. How to Avoid Maximizing Expected Utility.Bradley Monton - 2019 - Philosophers' Imprint 19.
    The lesson to be learned from the paradoxical St. Petersburg game and Pascal’s Mugging is that there are situations where expected utility maximizers will needlessly end up poor and on death’s door, and hence we should not be expected utility maximizers. Instead, when it comes to decision-making, for possibilities that have very small probabilities of occurring, we should discount those probabilities down to zero, regardless of the utilities associated with those possibilities.
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  14. Generalized Information Theory Meets Human Cognition: Introducing a Unified Framework to Model Uncertainty and Information Search.Vincenzo Crupi, Jonathan D. Nelson, Björn Meder, Gustavo Cevolani & Katya Tentori - 2018 - Cognitive Science 42 (5):1410-1456.
    Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people’s goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the (...)
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  15. A Probabilistic Epistemology of Perceptual Belief.Ralph Wedgwood - 2018 - Philosophical Issues 28 (1):1-25.
    There are three well-known models of how to account for perceptual belief within a probabilistic framework: (a) a Cartesian model; (b) a model advocated by Timothy Williamson; and (c) a model advocated by Richard Jeffrey. Each of these models faces a problem—in effect, the problem of accounting for the defeasibility of perceptual justification and perceptual knowledge. It is argued here that the best way of responding to this the best way of responding to this problem effectively vindicates the Cartesian model. (...)
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  16. Probabilistic Consistency Norms and Quantificational Credences.Benjamin Lennertz - 2017 - Synthese 194 (6).
    In addition to beliefs, people have attitudes of confidence called credences. Combinations of credences, like combinations of beliefs, can be inconsistent. It is common to use tools from probability theory to understand the normative relationships between a person’s credences. More precisely, it is common to think that something is a consistency norm on a person’s credal state if and only if it is a simple transformation of a truth of probability. Though it is common to challenge the right-to-left direction of (...)
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  17. Truth in Evidence and Truth in Arguments Without Logical Omniscience.Gregor Betz - 2016 - British Journal for the Philosophy of Science 67 (4):1117-1137.
    Science advances by means of argument and debate. Based on a formal model of complex argumentation, this article assesses the interplay between evidential and inferential drivers in scientific controversy, and explains, in particular, why both evidence accumulation and argumentation are veritistically valuable. By improving the conditions for applying veritistic indicators , novel evidence and arguments allow us to distinguish true from false hypotheses more reliably. Because such veritistic indicators also underpin inductive reasoning, evidence accumulation and argumentation enhance the reliability of (...)
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  18. Subjective Probability as Sampling Propensity.Thomas Icard - 2016 - Review of Philosophy and Psychology 7 (4):863-903.
    Subjective probability plays an increasingly important role in many fields concerned with human cognition and behavior. Yet there have been significant criticisms of the idea that probabilities could actually be represented in the mind. This paper presents and elaborates a view of subjective probability as a kind of sampling propensity associated with internally represented generative models. The resulting view answers to some of the most well known criticisms of subjective probability, and is also supported by empirical work in neuroscience and (...)
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  19. Between Probability and Certainty: What Justifies Belief.Martin Smith - 2016 - Oxford University Press UK.
    This book explores a question central to philosophy--namely, what does it take for a belief to be justified or rational? According to a widespread view, whether one has justification for believing a proposition is determined by how probable that proposition is, given one's evidence. In this book this view is rejected and replaced with another: in order for one to have justification for believing a proposition, one's evidence must normically support it--roughly, one's evidence must make the falsity of that proposition (...)
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  20. A Decision Theory for Imprecise Probabilities.Susanna Rinard - 2015 - Philosophers' Imprint 15.
    Those who model doxastic states with a set of probability functions, rather than a single function, face a pressing challenge: can they provide a plausible decision theory compatible with their view? Adam Elga and others claim that they cannot, and that the set of functions model should be rejected for this reason. This paper aims to answer this challenge. The key insight is that the set of functions model can be seen as an instance of the supervaluationist approach to vagueness (...)
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  21. The Phylogeography Debate and the Epistemology of Model-Based Evolutionary Biology.Alfonso Arroyo-Santos, Mark E. Olson & Francisco Vergara-Silva - 2014 - Biology and Philosophy 29 (6):833-850.
    Although there is increasing recognition that theory and practice in science are often inseparably intertwined, discussions of scientific controversies often continue to focus on theory, and not practice or methodologies. As a contribution to constructing a framework towards understanding controversies linked to scientific practices, we introduce the notion of borrowed epistemic credibility, to describe the situation in which scientists exploit fallacious similarities between accepted tenets in other fields to garner support for a given position in their own field. Our proposal (...)
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  22. Philosophy and Probability.Timothy Childers - 2013 - Oxford University Press.
    Probability is increasingly important for our understanding of the world. What is probability? How do we model it, and how do we use it? Timothy Childers presents a lively introduction to the foundations of probability and to philosophical issues it raises. He keeps technicalities to a minimum, and assumes no prior knowledge of the subject.
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  23. Is What is Worse More Likely?—The Probabilistic Explanation of the Epistemic Side-Effect Effect.Nikolaus Dalbauer & Andreas Hergovich - 2013 - Review of Philosophy and Psychology 4 (4):639-657.
    One aim of this article is to explore the connection between the Knobe effect and the epistemic side-effect effect (ESEE). Additionally, we report evidence about a further generalization regarding probability judgments. We demonstrate that all effects can be found within German material, using ‘absichtlich’ [intentionally], ‘wissen’ [know] and ‘wahrscheinlich’ [likely]. As the explanations discussed with regard to the Knobe effect do not suffice to explicate the ESEE, we survey whether the characteristic asymmetry in knowledge judgments is caused by a differing (...)
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  24. Akaike’s Theorem and Weak Predictivism in Science.Wang-Yen Lee - 2013 - Studies in History and Philosophy of Science Part A 44 (4):594-599.
  25. Popper’s Measure of Corroboration and P.Darrell Patrick Rowbottom - 2013 - British Journal for the Philosophy of Science 64 (4):axs029.
    This article shows that Popper’s measure of corroboration is inapplicable if, as Popper argued, the logical probability of synthetic universal statements is zero relative to any evidence that we might possess. It goes on to show that Popper’s definition of degree of testability, in terms of degree of logical content, suffers from a similar problem. 1 The Corroboration Function and P(h|b) 2 Degrees of Testability and P(h|b).
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  26. Can It Be Rational to Have Faith?Lara Buchak - 2012 - In Jake Chandler & Victoria Harrison (eds.), Probability in the Philosophy of Religion. Oxford University Press. pp. 225.
    This paper provides an account of what it is to have faith in a proposition p, in both religious and mundane contexts. It is argued that faith in p doesn’t require adopting a degree of belief that isn’t supported by one’s evidence but rather it requires terminating one’s search for further evidence and acting on the supposition that p. It is then shown, by responding to a formal result due to I.J. Good, that doing so can be rational in a (...)
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  27. Forecasted Risk Taking in Youth: Evidence for a Bounded-Rationality Perspective.Mandeep K. Dhami & David R. Mandel - 2012 - Synthese 189 (S1):161-171.
    This research examined whether youth's forecasted risk taking is best predicted by a compensatory (namely, subjective expected utility) or non-compensatory (e.g., single-factor) model. Ninety youth assessed the importance of perceived benefits, importance of perceived drawbacks, subjective probability of benefits, and subjective probability of drawbacks for 16 risky behaviors clustered evenly into recreational and health/safety domains. In both domains, there was strong support for a noncompensatory model in which only the perceived importance of the benefits of engaging in a risky behavior (...)
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  28. Carnap’s Thought on Inductive Logic.Yusuke Kaneko - 2012 - Philosophy Study 2 (11).
    Although we often see references to Carnap’s inductive logic even in modern literatures, seemingly its confusing style has long obstructed its correct understanding. So instead of Carnap, in this paper, I devote myself to its necessary and sufficient commentary. In the beginning part (Sections 2-5), I explain why Carnap began the study of inductive logic and how he related it with our thought on probability (Sections 2-4). Therein, I trace Carnap’s thought back to Wittgenstein’s Tractatus as well (Section 5). In (...)
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  29. The Confirmation of Singular Causal Statements by Carnap’s Inductive Logic.Yusuke Kaneko - 2012 - Logica Year Book 2011.
    The aim of this paper is to apply inductive logic to the field that, presumably, Carnap never expected: legal causation. Legal causation is expressible in the form of singular causal statements; but it is distinguished from the customary concept of scientific causation, because it is subjective. We try to express this subjectivity within the system of inductive logic. Further, by semantic complement, we compensate a defect found in our application, to be concrete, the impossibility of two-place predicates (for causal relationship) (...)
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  30. Logical Questions Behind the Lottery and Preface Paradoxes: Lossy Rules for Uncertain Inference.David Makinson - 2012 - Synthese 186 (2):511-529.
    We reflect on lessons that the lottery and preface paradoxes provide for the logic of uncertain inference. One of these lessons is the unreliability of the rule of conjunction of conclusions in such contexts, whether the inferences are probabilistic or qualitative; this leads us to an examination of consequence relations without that rule, the study of other rules that may nevertheless be satisfied in its absence, and a partial rehabilitation of conjunction as a ‘lossy’ rule. A second lesson is the (...)
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  31. The Effects of Source Trustworthiness and Inference Type on Human Belief Revision.Ann G. Wolf, Susann Rieger & Markus Knauff - 2012 - Thinking and Reasoning 18 (4):417-440.
  32. Luminosity and Vagueness.Elia Zardini - 2012 - Dialectica 66 (3):375-410.
    The paper discusses some ways in which vagueness and its phenomena may be thought to impose certain limits on our knowledge and, more specifically, may be thought to bear on the traditional philosophical idea that certain domains of facts are luminous, i.e., roughly, fully open to our view. The discussion focuses on a very influential argument to the effect that almost no such interesting domains exist. Many commentators have felt that the vagueness unavoidably inherent in the description of the facts (...)
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  33. Probability in the Many-Worlds Interpretation of Quantum Mechanics.Lev Vaidman - 2011 - In Yemima Ben-Menahem & Meir Hemmo (eds.), Probability in Physics. Springer. pp. 299--311.
    It is argued that, although in the Many-Worlds Interpretation of quantum mechanics there is no ``probability'' for an outcome of a quantum experiment in the usual sense, we can understand why we have an illusion of probability. The explanation involves: a). A ``sleeping pill'' gedanken experiment which makes correspondence between an illegitimate question: ``What is the probability of an outcome of a quantum measurement?'' with a legitimate question: ``What is the probability that ``I'' am in the world corresponding to that (...)
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  34. Belief and Contextual Acceptance.Eleonora Cresto - 2010 - Synthese 177 (1):41-66.
    I develop a strategy for representing epistemic states and epistemic changes that seeks to be sensitive to the difference between voluntary and involuntary aspects of our epistemic life, as well as to the role of pragmatic factors in epistemology. The model relies on a particular understanding of the distinction between full belief and acceptance , which makes room for the idea that our reasoning on both practical and theoretical matters typically proceeds in a contextual way. Within this framework, I discuss (...)
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  35. A Complete Theory of Everything (Will Be Subjective).Marcus Hutter - 2010 - Algorithms 3 (4):329-350.
    Increasingly encompassing models have been suggested for our world. Theories range from generally accepted to increasingly speculative to apparently bogus. The progression of theories from ego- to geo- to helio-centric models to universe and multiverse theories and beyond was accompanied by a dramatic increase in the sizes of the postulated worlds, with humans being expelled from their center to ever more remote and random locations. Rather than leading to a true theory of everything, this trend faces a turning point after (...)
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  36. Probability Logic of Finitely Additive Beliefs.Chunlai Zhou - 2010 - Journal of Logic, Language and Information 19 (3):247-282.
    Probability logics have been an active topic of investigation of beliefs in type spaces in game theoretical economics. Beliefs are expressed as subjective probability measures. Savage’s postulates in decision theory imply that subjective probability measures are not necessarily countably additive but finitely additive. In this paper, we formulate a probability logic Σ + that is strongly complete with respect to this class of type spaces with finitely additive probability measures, i.e. a set of formulas is consistent in Σ + iff (...)
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  37. Dynamic Update with Probabilities.Johan van Benthem, Jelle Gerbrandy & Barteld Kooi - 2009 - Studia Logica 93 (1):67 - 96.
    Current dynamic-epistemic logics model different types of information change in multi-agent scenarios. We generalize these logics to a probabilistic setting, obtaining a calculus for multi-agent update with three natural slots: prior probability on states, occurrence probabilities in the relevant process taking place, and observation probabilities of events. To match this update mechanism, we present a complete dynamic logic of information change with a probabilistic character. The completeness proof follows a compositional methodology that applies to a much larger class of dynamic-probabilistic (...)
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  38. Subjective Probability Weighting and the Discovered Preference Hypothesis.Gijs van de Kuilen - 2009 - Theory and Decision 67 (1):1-22.
    Numerous studies have convincingly shown that prospect theory can better describe risky choice behavior than the classical expected utility model because it makes the plausible assumption that risk aversion is driven not only by the degree of sensitivity toward outcomes, but also by the degree of sensitivity toward probabilities. This article presents the results of an experiment aimed at testing whether agents become more sensitive toward probabilities over time when they repeatedly face similar decisions, receive feedback on the consequences of (...)
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  39. Quantifier Probability Logic and the Confirmation Paradox.Theodore Hailperin - 2007 - History and Philosophy of Logic 28 (1):83-100.
    Exhumation and study of the 1945 paradox of confirmation brings out the defect of its formulation. In the context of quantifier conditional-probability logic it is shown that a repair can be accomplished if the truth-functional conditional used in the statement of the paradox is replaced with a connective that is appropriate to the probabilistic context. Description of the quantifier probability logic involved in the resolution of the paradox is presented in stages. Careful distinction is maintained between a formal logic language (...)
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  40. On the Martingale Representation Theorem and on Approximate Hedging a Contingent Claim in the Minimum Deviation Square Criterion.Nguyen Van Huu & Quan-Hoang Vuong - 2007 - In Ta-Tsien Li Rolf Jeltsch (ed.), Some Topics in Industrial and Applied Mathematics. Shanghai, China: World Scientific. pp. 134-151.
    In this work we consider the problem of the approximate hedging of a contingent claim in the minimum mean square deviation criterion. A theorem on martingale representation in case of discrete time and an application of the result for semi-continuous market model are also given.
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  41. Ranking Functions and Rankings on Languages.Franz Huber - 2006 - Artificial Intelligence 170 (4-5):462-471.
    The Spohnian paradigm of ranking functions is in many respects like an order-of-magnitude reverse of subjective probability theory. Unlike probabilities, however, ranking functions are only indirectly—via a pointwise ranking function on the underlying set of possibilities W —defined on a field of propositions A over W. This research note shows under which conditions ranking functions on a field of propositions A over W and rankings on a language L are induced by pointwise ranking functions on W and the set of (...)
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  42. Bovens and Hartmann on Coherence.Wouter Meijs & Igor Douven - 2005 - Mind 114 (454):355-363.
  43. James Woodward, Making Things Happen: A Theory of Causal Explanation, Oxford, 2003, 418pp, &Dollar;65.00 ISBN 0195155270. [REVIEW]Clark Glymour - 2004 - British Journal for the Philosophy of Science 55 (4):779-790.
    "Goodness of Fit": Clinical Applications from Infancy through Adult Life. By Stella Chess & Alexander Thomas. Brunner/Mazel, Philadelphia, PA, 1999. pp. 229. pound24.95 (hb). Chess and Thomas's pioneering longitudinal studies of temperamental individuality started over 40 years ago (Thomas et al., 1963). Their publications soon became and remain classics. Their concept of "goodness of fit" emerges out of this monumental work but has had a long gestation period. In their new book, the authors distinguish between behaviour disorders that are reactive (...)
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  44. From Classical to Intuitionistic Probability.Brian Weatherson - 2003 - Notre Dame Journal of Formal Logic 44 (2):111-123.
    We generalize the Kolmogorov axioms for probability calculus to obtain conditions defining, for any given logic, a class of probability functions relative to that logic, coinciding with the standard probability functions in the special case of classical logic but allowing consideration of other classes of "essentially Kolmogorovian" probability functions relative to other logics. We take a broad view of the Bayesian approach as dictating inter alia that from the perspective of a given logic, rational degrees of belief are those representable (...)
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  45. Statistical Model Selection Criteria and the Philosophical Problem of Underdetermination.I. A. Kieseppä - 2001 - British Journal for the Philosophy of Science 52 (4):761-794.
    I discuss the philosophical significance of the statistical model selection criteria, in particular their relevance for philosophical of underdetermination. I present an easily comprehensible account of their simplest possible application and contrast it with their application to curve-fitting problems. I embed philosophers' earlier discussion concerning the situations in which the criteria yield implausible results into a more general framework. Among other things, I discuss a difficulty which is related to the so-called subfamily problem, and I show that it has analogies (...)
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  46. Model Selection in Science: The Problem of Language Variance.M. R. Forster - 1999 - British Journal for the Philosophy of Science 50 (1):83-102.
    Recent solutions to the curve-fitting problem, described in Forster and Sober ([1995]), trade off the simplicity and fit of hypotheses by defining simplicity as the paucity of adjustable parameters. Scott De Vito ([1997]) charges that these solutions are 'conventional' because he thinks that the number of adjustable parameters may change when the hypotheses are described differently. This he believes is exactly what is illustrated in Goodman's new riddle of induction, otherwise known as the grue problem. However, the 'number of adjustable (...)
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  47. How to Set a Surprise Exam.Ned Hall - 1999 - Mind 108 (432):647-703.
    The professor announces a surprise exam for the upcoming week; her clever student purports to demonstrate by reductio that she cannot possibly give such an exam. Diagnosing his puzzling argument reveals a deeper puzzle: Is the student justified in believing the announcement? It would seem so, particularly if the upcoming 'week' is long enough. On the other hand, a plausible principle states that if, at the outset, the student is justified in believing some proposition, then he is also justified in (...)
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  48. A Theory of Physical Probability.Richard Alexander Johns - 1999 - Dissertation, The University of British Columbia (Canada)
    It is now common to hold that causes do not always determine their effects, and indeed theories of "probabilistic causation" abound. The basic idea of these theories is that C causes E just in case C and E both occur, and the chance of E would have been lower than it is had C not occurred. The problems with these accounts are that the notion of chance remains primitive, and this account of causation does not coincide with the intuitive notion (...)
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  49. A Gruesome Problem for the Curve-Fitting Solution.Scott DeVito - 1997 - British Journal for the Philosophy of Science 48 (3):391-396.
    This paper is a response to Forster and Sober's [1994] solution to the curve-fitting problem. If their solution is correct, it will provide us with a solution to the New Riddle of Induction as well as provide a basis for choosing realism over conventionalism. Examining this solution is also important as Forster and Sober incorporate it in much of their other philosophical work (see Forster [1995a, b, 1994] and Sober [1996, 1995, 1993]). I argue that Forster and Sober's solution is (...)
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  50. Towards a Rough Mereology-Based Logic for Approximate Solution Synthesis. Part.Jan Komorowski, Lech T. Polkowski & Andrzej Skowron - 1997 - Studia Logica 58 (1):143-184.
    We are concerned with formal models of reasoning under uncertainty. Many approaches to this problem are known in the literature e.g. Dempster-Shafer theory [29], [42], bayesian-based reasoning [21], [29], belief networks [29], many-valued logics and fuzzy logics [6], non-monotonic logics [29], neural network logics [14]. We propose rough mereology developed by the last two authors [22-25] as a foundation for approximate reasoning about complex objects. Our notion of a complex object includes, among others, proofs understood as schemes constructed in order (...)
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