Results for 'Legal Probabilism'

969 found
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  1. Against legal probabilism.Martin Smith - 2021 - 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 (...)
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  2. Legal Probabilism and Anti-Probabilism.Lewis Ross - 2024 - In The Philosophy of Legal Proof. Cambridge University Press.
    Discusses whether legal proof is merely probabilistic, focusing on the famous proof paradox.
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  3. Legal Epistemology.Georgi Gardiner - 2019 - Oxford Bibliographies Online.
    An annotated bibliography of legal epistemology.
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  4. Statistical Evidence, Sensitivity, and the Legal Value of Knowledge.David Enoch, Levi Spectre & Talia Fisher - 2012 - Philosophy and Public Affairs 40 (3):197-224.
    The law views with suspicion statistical evidence, even evidence that is probabilistically on a par with direct, individual evidence that the law is in no way suspicious of. But it has proved remarkably hard to either justify this suspicion, or to debunk it. In this paper, we connect the discussion of statistical evidence to broader epistemological discussions of similar phenomena. We highlight Sensitivity – the requirement that a belief be counterfactually sensitive to the truth in a specific way – as (...)
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  5. On Evidence, Medical and Legal.Donald W. Miller & Clifford Miller - 2005 - Journal of American Physicians and Surgeons 10 (3):70-75.
    Medicine, like law, is a pragmatic, probabilistic activity. Both require that decisions be made on the basis of available evidence, within a limited time. In contrast to law, medicine, particularly evidence-based medicine as it is currently practiced, aspires to a scientific standard of proof, one that is more certain than the standards of proof courts apply in civil and criminal proceedings. But medicine, as Dr. William Osler put it, is an "art of probabilities," or at best, a "science of uncertainty." (...)
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  6. Reasoning about Criminal Evidence: Revealing Probabilistic Reasoning Behind Logical Conclusions.Michelle B. Cowley-Cunningham - 2007 - SSRN E-Library Maurer School of Law Law and Society eJournals.
    There are two competing theoretical frameworks with which cognitive sciences examines how people reason. These frameworks are broadly categorized into logic and probability. This paper reports two applied experiments to test which framework explains better how people reason about evidence in criminal cases. Logical frameworks predict that people derive conclusions from the presented evidence to endorse an absolute value of certainty such as ‘guilty’ or ‘not guilty’ (e.g., Johnson-Laird, 1999). But probabilistic frameworks predict that people derive conclusions from the presented (...)
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  7. Probability of Guilt.Mario Günther - manuscript
    In legal proceedings, a fact-finder needs to decide whether a defendant is guilty or not based on probabilistic evidence. We defend the thesis that the defendant should be found guilty just in case it is rational for the fact-finder to believe that the defendant is guilty. We draw on Leitgeb’s stability theory for an appropriate notion of rational belief and show how our thesis solves the problem of statistical evidence. Finally, we defend our account of legal proof against (...)
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  8. Knowledge, Evidence, and Naked Statistics.Sherrilyn Roush - 2023 - In Luis R. G. Oliveira (ed.), Externalism about Knowledge. Oxford: Oxford University Press.
    Many who think that naked statistical evidence alone is inadequate for a trial verdict think that use of probability is the problem, and something other than probability – knowledge, full belief, causal relations – is the solution. I argue that the issue of whether naked statistical evidence is weak can be formulated within the probabilistic idiom, as the question whether likelihoods or only posterior probabilities should be taken into account in our judgment of a case. This question also identifies a (...)
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  9. The Science of Conjecture: Evidence and Probability Before Pascal.James Franklin - 2001 - Baltimore, USA: Johns Hopkins University Press.
    How were reliable predictions made before Pascal and Fermat's discovery of the mathematics of probability in 1654? What methods in law, science, commerce, philosophy, and logic helped us to get at the truth in cases where certainty was not attainable? The book examines how judges, witch inquisitors, and juries evaluated evidence; how scientists weighed reasons for and against scientific theories; and how merchants counted shipwrecks to determine insurance rates. Also included are the problem of induction before Hume, design arguments for (...)
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  10. ‘The Innocent v The Fickle Few’: How Jurors Understand Random-Match-Probabilities and Judges’ Directions when Reasoning about DNA and Refuting Evidence.Michelle B. Cowley-Cunningham - 2017 - Journal of Forensic Science and Criminal Investigation 3 (5):April/May 2017.
    DNA evidence is one of the most significant modern advances in the search for truth since the cross examination, but its format as a random-match-probability makes it difficult for people to assign an appropriate probative value (Koehler, 2001). While Frequentist theories propose that the presentation of the match as a frequency rather than a probability facilitates more accurate assessment (e.g., Slovic et al., 2000), Exemplar-Cueing Theory predicts that the subjective weight assigned may be affected by the frequency or probability format, (...)
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  11. 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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  12. Improving Numerical Performance in Grade-7 Students through Effective Remedial Instruction.Pearl Marie A. Legal & Gregorio A. Legal - 2024 - International Journal of Multidisciplinary Educational Research and Innovation 2 (1):1-20.
    This study aimed to assess the effectiveness of remedial instruction in improving the numeracy skills of Grade 7 students at Malbug National High School during the school year 2023-2024. Adopting a quasi-experimental research design, the research focused on Grade 7 students at Malbug National High School, Cawayan East District, Masbate Province Division, Philippines, identified as non-numerates, employing pre-tests and post-tests as essential research tools. The independent variable was the remedial instruction in numeracy, while the dependent variable was students' numeracy performance (...)
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  13. Improving Responsiveness to Stakeholders: A Mobile Application of Selected School Services for the Mary Perpetua E. Brioso National High School.Gregorio A. Legal - 2023 - International Journal of Multidisciplinary Educational Research and Innovation 1 (4):252-269.
    This capstone project aimed to enhance the operational efficiency of school transactions at Mary Perpetua E. Brioso National High School (MPEBNHS) in response to challenges posed by the COVID-19 pandemic. This goal was achieved by developing and implementing the Mobile-Based Selected School Services Application, "iSkulSerb." The development of iSkulSerb followed the systematic approach of Borg and Gall's (1983) Research and Development (R&D) methodology for creating and validating educational products. To ensure the validity and reliability of the application, it underwent rigorous (...)
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  14. Probabilistic Actual Causation.Fenton-Glynn Luke - manuscript
    Actual causes - e.g. Suzy's being exposed to asbestos - often bring about their effects - e.g. Suzy's suffering mesothelioma - probabilistically. I use probabilistic causal models to tackle one of the thornier difficulties for traditional accounts of probabilistic actual causation: namely probabilistic preemption.
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  15. Probabilistic Proofs, Lottery Propositions, and Mathematical Knowledge.Yacin Hamami - 2021 - Philosophical Quarterly 72 (1):77-89.
    In mathematics, any form of probabilistic proof obtained through the application of a probabilistic method is not considered as a legitimate way of gaining mathematical knowledge. In a series of papers, Don Fallis has defended the thesis that there are no epistemic reasons justifying mathematicians’ rejection of probabilistic proofs. This paper identifies such an epistemic reason. More specifically, it is argued here that if one adopts a conception of mathematical knowledge in which an epistemic subject can know a mathematical proposition (...)
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  16. Does probabilism solve the great quantum mystery?Nicholas Maxwell - 2010 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 19 (3):321-336.
    I put forward a micro realistic, probabilistic version of quantum theory, which specifies the precise nature of quantum entities thus solving the quantum wave/particle dilemma, and which both reproduces the empirical success of orthodox quantum theory, and yields predictions that differ from orthodox quantum theory for as yet unperformed experiments.
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  17. Probabilistically coherent credences despite opacity.Christian List - forthcoming - Economics and Philosophy:1-10.
    Real human agents, even when they are rational by everyday standards, sometimes assign different credences to objectively equivalent statements, such as “George Orwell is a writer” and “Eric Arthur Blair is a writer”, or credences less than 1 to necessarily true statements, such as not-yet-proven theorems of arithmetic. Anna Mahtani calls this the phenomenon of “opacity” (a form of hyperintensionality). Opaque credences seem probabilistically incoherent, which goes against a key modelling assumption of probability theory. I sketch a modelling strategy for (...)
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  18. Probabilistic Opinion Pooling Generalized. Part One: General Agendas.Franz Dietrich & Christian List - 2017 - Social Choice and Welfare 48 (4):747–786.
    How can different individuals' probability assignments to some events be aggregated into a collective probability assignment? Classic results on this problem assume that the set of relevant events -- the agenda -- is a sigma-algebra and is thus closed under disjunction (union) and conjunction (intersection). We drop this demanding assumption and explore probabilistic opinion pooling on general agendas. One might be interested in the probability of rain and that of an interest-rate increase, but not in the probability of rain or (...)
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  19. Probabilistic semantics for epistemic modals: Normality assumptions, conditional epistemic spaces and the strength of must and might.Guillermo Del Pinal - 2021 - Linguistics and Philosophy 45 (4):985-1026.
    The epistemic modal auxiliaries must and might are vehicles for expressing the force with which a proposition follows from some body of evidence or information. Standard approaches model these operators using quantificational modal logic, but probabilistic approaches are becoming increasingly influential. According to a traditional view, must is a maximally strong epistemic operator and might is a bare possibility one. A competing account—popular amongst proponents of a probabilisitic turn—says that, given a body of evidence, must \ entails that \\) is (...)
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  20. Is probabilistic evidence a source of knowledge?Ori Friedman & John Turri - 2015 - Cognitive Science 39 (5):1062-1080.
    We report a series of experiments examining whether people ascribe knowledge for true beliefs based on probabilistic evidence. Participants were less likely to ascribe knowledge for beliefs based on probabilistic evidence than for beliefs based on perceptual evidence or testimony providing causal information. Denial of knowledge for beliefs based on probabilistic evidence did not arise because participants viewed such beliefs as unjustified, nor because such beliefs leave open the possibility of error. These findings rule out traditional philosophical accounts for why (...)
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  21. Are probabilism and special relativity incompatible?Nicholas Maxwell - 1985 - Philosophy of Science 52 (1):23-43.
    In this paper I expound an argument which seems to establish that probabilism and special relativity are incompatible. I examine the argument critically, and consider its implications for interpretative problems of quantum theory, and for theoretical physics as a whole.
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  22. (2 other versions)Are probabilism and special relativity compatible?Nicholas Maxwell - 1988 - Philosophy of Science 55 (4):640-645.
    Are special relativity and probabilism compatible? Dieks argues that they are. But the possible universe he specifies, designed to exemplify both probabilism and special relativity, either incorporates a universal "now" (and is thus incompatible with special relativity), or amounts to a many world universe (which I have discussed, and rejected as too ad hoc to be taken seriously), or fails to have any one definite overall Minkowskian-type space-time structure (and thus differs drastically from special relativity as ordinarily understood). (...)
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  23. Probabilistic Regresses and the Availability Problem for Infinitism.Adam C. Podlaskowski & Joshua A. Smith - 2014 - Metaphilosophy 45 (2):211-220.
    Recent work by Peijnenburg, Atkinson, and Herzberg suggests that infinitists who accept a probabilistic construal of justification can overcome significant challenges to their position by attending to mathematical treatments of infinite probabilistic regresses. In this essay, it is argued that care must be taken when assessing the significance of these formal results. Though valuable lessons can be drawn from these mathematical exercises (many of which are not disputed here), the essay argues that it is entirely unclear that the form of (...)
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  24. Accuracy, probabilism, and the insufficiency of the alethic.Corey Dethier - 2021 - Philosophical Studies 179 (7):2285-2301.
    The best and most popular argument for probabilism is the accuracy-dominance argument, which purports to show that alethic considerations alone support the view that an agent’s degrees of belief should always obey the axioms of probability. I argue that extant versions of the accuracy-dominance argument face a problem. In order for the mathematics of the argument to function as advertised, we must assume that every omniscient credence function is classically consistent; there can be no worlds in the set of (...)
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  25. (1 other version)Probabilistic promotion and ability.Luke Elson - 2019 - Ergo: An Open Access Journal of Philosophy 6.
    We often have some reason to do actions insofar as they promote outcomes or states of affairs, such as the satisfaction of a desire. But what is it to promote an outcome? I defend a new version of 'probabilism about promotion'. According to Minimal Probabilistic Promotion, we promote some outcome when we make that outcome more likely than it would have been if we had done something (anything) else. This makes promotion easy and reasons cheap.
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  26. A probabilistic analysis of argument cogency.David Godden & Frank Zenker - 2018 - Synthese 195 (4):1715-1740.
    This paper offers a probabilistic treatment of the conditions for argument cogency as endorsed in informal logic: acceptability, relevance, and sufficiency. Treating a natural language argument as a reason-claim-complex, our analysis identifies content features of defeasible argument on which the RSA conditions depend, namely: change in the commitment to the reason, the reason’s sensitivity and selectivity to the claim, one’s prior commitment to the claim, and the contextually determined thresholds of acceptability for reasons and for claims. Results contrast with, and (...)
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  27. Probabilistic opinion pooling generalised. Part two: The premise-based approach.Franz Dietrich & Christian List - 2017 - Social Choice and Welfare 48 (4):787–814.
    How can different individuals' probability functions on a given sigma-algebra of events be aggregated into a collective probability function? Classic approaches to this problem often require 'event-wise independence': the collective probability for each event should depend only on the individuals' probabilities for that event. In practice, however, some events may be 'basic' and others 'derivative', so that it makes sense first to aggregate the probabilities for the former and then to let these constrain the probabilities for the latter. We formalize (...)
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  28. Probabilistic Opinion Pooling.Franz Dietrich & Christian List - 2016 - In Alan Hájek & Christopher Hitchcock (eds.), The Oxford Handbook of Probability and Philosophy. 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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  29. Probabilistic Arguments in the Epistemological Approach to Argumentation.Christoph Lumer - 2011 - In Frans H. van Eemeren, Bart Garssen, David Godden & Gordon Mitchell (eds.), Proceedings of the Seventh International Conference of the International Society for the Study of Argumentation. Rozenberg / Sic Sat. pp. 1141-1154.
    The aim of the paper is to develop general criteria of argumentative validity and adequacy for probabilistic arguments on the basis of the epistemological approach to argumentation. In this approach, as in most other approaches to argumentation, proabilistic arguments have been neglected somewhat. Nonetheless, criteria for several special types of probabilistic arguments have been developed, in particular by Richard Feldman and Christoph Lumer. In the first part (sects. 2-5) the epistemological basis of probabilistic arguments is discussed. With regard to the (...)
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  30. 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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  31. (1 other version)Probabilistic causation and the explanatory role of natural selection.Pablo Razeto-Barry & Ramiro Frick - 2011 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 42 (3):344-355.
    The explanatory role of natural selection is one of the long-term debates in evolutionary biology. Nevertheless, the consensus has been slippery because conceptual confusions and the absence of a unified, formal causal model that integrates different explanatory scopes of natural selection. In this study we attempt to examine two questions: (i) What can the theory of natural selection explain? and (ii) Is there a causal or explanatory model that integrates all natural selection explananda? For the first question, we argue that (...)
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  32. Probabilistic representations in perception: Are there any, and what would they be?Steven Gross - 2020 - Mind and Language 35 (3):377-389.
    Nick Shea’s Representation in Cognitive Science commits him to representations in perceptual processing that are about probabilities. This commentary concerns how to adjudicate between this view and an alternative that locates the probabilities rather in the representational states’ associated “attitudes”. As background and motivation, evidence for probabilistic representations in perceptual processing is adduced, and it is shown how, on either conception, one can address a specific challenge Ned Block has raised to this evidence.
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  33. Probabilism for stochastic theories.Jer Steeger - 2019 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 66:34–44.
    I defend an analog of probabilism that characterizes rationally coherent estimates for chances. Specifically, I demonstrate the following accuracy-dominance result for stochastic theories in the C*-algebraic framework: supposing an assignment of chance values is possible if and only if it is given by a pure state on a given algebra, your estimates for chances avoid accuracy-dominance if and only if they are given by a state on that algebra. When your estimates avoid accuracy-dominance (roughly: when you cannot guarantee that (...)
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  34. Non-probabilistic Causation without Necessitation.Daniel Von Wachter - manuscript
    This article introduces the notion of the directedness of a process, which underlies event causation as well as the persistence of things. Using this notion it investigates what happens in typical cases of active event causation. Causes never necessitate their effects because even non- probabilistic causes can be counteracted.
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  35. Context Probabilism.Seth Yalcin - 2012 - In M. Aloni (ed.), 18th Amsterdam Colloquium. Springer. pp. 12-21.
    We investigate a basic probabilistic dynamic semantics for a fragment containing conditionals, probability operators, modals, and attitude verbs, with the aim of shedding light on the prospects for adding probabilistic structure to models of the conversational common ground.
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  36. Probabilistic Knowledge in Action.Carlotta Pavese - 2020 - Analysis 80 (2):342-356.
    According to a standard assumption in epistemology, if one only partially believes that p , then one cannot thereby have knowledge that p. For example, if one only partially believes that that it is raining outside, one cannot know that it is raining outside; and if one only partially believes that it is likely that it will rain outside, one cannot know that it is likely that it will rain outside. Many epistemologists will agree that epistemic agents are capable of (...)
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  37. Qualitative probabilistic inference under varied entropy levels.Paul D. Thorn & Gerhard Schurz - 2016 - Journal of Applied Logic 19 (2):87-101.
    In previous work, we studied four well known systems of qualitative probabilistic inference, and presented data from computer simulations in an attempt to illustrate the performance of the systems. These simulations evaluated the four systems in terms of their tendency to license inference to accurate and informative conclusions, given incomplete information about a randomly selected probability distribution. In our earlier work, the procedure used in generating the unknown probability distribution (representing the true stochastic state of the world) tended to yield (...)
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  38. Debunking Debunking: Explanationism, Probabilistic Sensitivity, and Why There is No Specifically Metacognitive Debunking Principle.David Bourget & Angela Mendelovici - 2023 - Midwest Studies in Philosophy 47:25-52.
    On explanationist accounts of genealogical debunking, roughly, a belief is debunked when its explanation is not suitably related to its content. We argue that explanationism cannot accommodate cases in which beliefs are explained by factors unrelated to their contents but are nonetheless independently justified. Justification-specific versions of explanationism face an iteration of the problem. The best account of debunking is a probabilistic account according to which subject S’s justification J for their belief that P is debunked when S learns that (...)
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  39. (1 other version)A Proposed Probabilistic Extension of the Halpern and Pearl Definition of ‘Actual Cause’.Luke Fenton-Glynn - 2017 - British Journal for the Philosophy of Science 68 (4):1061-1124.
    In their article 'Causes and Explanations: A Structural-Model Approach. Part I: Causes', Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of 'actual cause'. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation.
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  40. Cognitivist Probabilism.Paul D. Thorn - 2013 - In Vit Puncochar & Petr Svarny (eds.), The Logica Yearbook 2012. College Publications. pp. 201-213.
    In this article, I introduce the term “cognitivism” as a name for the thesis that degrees of belief are equivalent to full beliefs about truth-valued propositions. The thesis (of cognitivism) that degrees of belief are equivalent to full beliefs is equivocal, inasmuch as different sorts of equivalence may be postulated between degrees of belief and full beliefs. The simplest sort of equivalence (and the sort of equivalence that I discuss here) identifies having a given degree of belief with having a (...)
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  41. Purely Probabilistic Measures of Explanatory Power: A Critique.William Roche & Elliott Sober - 2023 - Philosophy of Science 90 (1):129-149.
    All extant purely probabilistic measures of explanatory power satisfy the following technical condition: if Pr(E | H1) > Pr(E | H2) and Pr(E | ∼H1) < Pr(E | ∼H2), then H1’s explanatory power with respect to E is greater than H2’s explanatory power with respect to E. We argue that any measure satisfying this condition faces three serious problems—the Problem of Temporal Shallowness, the Problem of Negative Causal Interactions, and the Problem of Nonexplanations. We further argue that many such measures (...)
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  42. Probabilistic causation and causal processes: A critique of Lewis.Peter Menzies - 1989 - Philosophy of Science 56 (4):642-663.
    This paper examines a promising probabilistic theory of singular causation developed by David Lewis. I argue that Lewis' theory must be made more sophisticated to deal with certain counterexamples involving pre-emption. These counterexamples appear to show that in the usual case singular causation requires an unbroken causal process to link cause with effect. I propose a new probabilistic account of singular causation, within the framework developed by Lewis, which captures this intuition.
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  43. Probabilistic proofs and transferability.Kenny Easwaran - 2009 - Philosophia Mathematica 17 (3):341-362.
    In a series of papers, Don Fallis points out that although mathematicians are generally unwilling to accept merely probabilistic proofs, they do accept proofs that are incomplete, long and complicated, or partly carried out by computers. He argues that there are no epistemic grounds on which probabilistic proofs can be rejected while these other proofs are accepted. I defend the practice by presenting a property I call ‘transferability’, which probabilistic proofs lack and acceptable proofs have. I also consider what this (...)
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  44. A probabilistic framework for analysing the compositionality of conceptual combinations.Peter Bruza, Kirsty Kitto, Brentyn Ramm & Laurianne Sitbon - 2015 - Journal of Mathematical Psychology 67:26-38.
    Conceptual combination performs a fundamental role in creating the broad range of compound phrases utilised in everyday language. This article provides a novel probabilistic framework for assessing whether the semantics of conceptual combinations are compositional, and so can be considered as a function of the semantics of the constituent concepts, or not. While the systematicity and productivity of language provide a strong argument in favor of assuming compositionality, this very assumption is still regularly questioned in both cognitive science and philosophy. (...)
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  45. A Probabilistic Analysis of Causation.Luke Glynn - 2011 - British Journal for the Philosophy of Science 62 (2):343-392.
    The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that (...)
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  46. Visualizing Probabilistic Proof.Enrique Guerra-Pujol - 2014 - Washington University Jurisprudence Review 7 (1):39-75.
    The author revisits the Blue Bus Problem, a famous thought-experiment in law involving probabilistic proof, and presents simple Bayesian solutions to different versions of the blue bus problem. In addition, the author expresses his solutions in standard and visual formats, i.e. in terms of probabilities and natural frequencies.
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  47. 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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  48. The Legal Self: Executive processes and legal theory.William Hirstein & Katrina Sifferd - 2011 - Consciousness and Cognition 20 (1):151-176.
    When laws or legal principles mention mental states such as intentions to form a contract, knowledge of risk, or purposely causing a death, what parts of the brain are they speaking about? We argue here that these principles are tacitly directed at our prefrontal executive processes. Our current best theories of consciousness portray it as a workspace in which executive processes operate, but what is important to the law is what is done with the workspace content rather than the (...)
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  49. Calibrating Generative Models: The Probabilistic Chomsky-Schützenberger Hierarchy.Thomas Icard - 2020 - Journal of Mathematical Psychology 95.
    A probabilistic Chomsky–Schützenberger hierarchy of grammars is introduced and studied, with the aim of understanding the expressive power of generative models. We offer characterizations of the distributions definable at each level of the hierarchy, including probabilistic regular, context-free, (linear) indexed, context-sensitive, and unrestricted grammars, each corresponding to familiar probabilistic machine classes. Special attention is given to distributions on (unary notations for) positive integers. Unlike in the classical case where the "semi-linear" languages all collapse into the regular languages, using analytic tools (...)
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  50. Problems for pure probabilism about promotion (and a disjunctive alternative).Nathaniel Sharadin - 2015 - Philosophical Studies 172 (5):1371-1386.
    Humean promotionalists about reasons think that whether there is a reason for an agent to ϕ depends on whether her ϕ-ing promotes the satisfaction of at least one of her desires. Several authors have recently defended probabilistic accounts of promotion, according to which an agent’s ϕ-ing promotes the satisfaction of one of her desires just in case her ϕ-ing makes the satisfaction of that desire more probable relative to some baseline. In this paper I do three things. First, I formalize (...)
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