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  1. How to Confirm the Disconfirmed. On Conjunction Fallacies and Robust Confirmation.David Atkinson, Jeanne Peijnenburg & Theo Kuipers - unknown
    Can some evidence confirm a conjunction of two hypotheses more than it confirms either of the hypotheses separately? We show that it can, moreover under conditions that are the same for nine different measures of confirmation. Further we demonstrate that it is even possible for the conjunction of two disconfirmed hypotheses to be confirmed by the same evidence.
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  • How the Conjunction Fallacy is Tied to Probabilistic Confirmation: Some Remarks on Schupbach (2009).Katya Tentori & Vincenzo Crupi - 2012 - Synthese 184 (1):3-12.
    Crupi et al. (Think Reason 14:182–199, 2008) have recently advocated and partially worked out an account of the conjunction fallacy phenomenon based on the Bayesian notion of confirmation. In response, Schupbach (2009) presented a critical discussion as following from some novel experimental results. After providing a brief restatement and clarification of the meaning and scope of our original proposal, we will outline Schupbach’s results and discuss his interpretation thereof arguing that they do not actually undermine our point of view if (...)
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  • The Degree of Epistemic Justification and the Conjunction Fallacy.Tomoji Shogenji - 2012 - Synthese 184 (1):29-48.
    This paper describes a formal measure of epistemic justification motivated by the dual goal of cognition, which is to increase true beliefs and reduce false beliefs. From this perspective the degree of epistemic justification should not be the conditional probability of the proposition given the evidence, as it is commonly thought. It should be determined instead by the combination of the conditional probability and the prior probability. This is also true of the degree of incremental confirmation, and I argue that (...)
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  • Why Quantum Probability Does Not Explain the Conjunction Fallacy.Katya Tentori & Vincenzo Crupi - 2013 - Behavioral and Brain Sciences 36 (3):308-310.
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  • Is the Conjunction Fallacy Tied to Probabilistic Confirmation?Jonah N. Schupbach - 2012 - Synthese 184 (1):13-27.
    Crupi et al. (2008) offer a confirmation-theoretic, Bayesian account of the conjunction fallacy—an error in reasoning that occurs when subjects judge that Pr( h 1 & h 2 | e ) > Pr( h 1 | e ). They introduce three formal conditions that are satisfied by classical conjunction fallacy cases, and they show that these same conditions imply that h 1 & h 2 is confirmed by e to a greater extent than is h 1 alone. Consequently, they suggest (...)
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  • Walter the Banker: The Conjunction Fallacy Reconsidered. [REVIEW]Stephan Hartmann & Wouter Meijs - 2012 - Synthese 184 (1):73-87.
    In a famous experiment by Tversky and Kahneman (Psychol Rev 90:293–315, 1983), featuring Linda the bank teller, the participants assign a higher probability to a conjunction of propositions than to one of the conjuncts, thereby seemingly committing a probabilistic fallacy. In this paper, we discuss a slightly different example featuring someone named Walter, who also happens to work at a bank, and argue that, in this example, it is rational to assign a higher probability to the conjunction of suitably chosen (...)
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  • Formal and Empirical Methods in Philosophy of Science.Vincenzo Crupi & Stephan Hartmann - 2009 - In Friedrich Stadler et al (ed.), The Present Situation in the Philosophy of Science. Springer. pp. 87--98.
    This essay addresses the methodology of philosophy of science and illustrates how formal and empirical methods can be fruitfully combined. Special emphasis is given to the application of experimental methods to confirmation theory and to recent work on the conjunction fallacy, a key topic in the rationality debate arising from research in cognitive psychology. Several other issue can be studied in this way. In the concluding section, a brief outline is provided of three further examples.
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  • Confirmation, Causation, and Simpson's Paradox.Branden Fitelson - 2017 - Episteme 14 (3):297-309.
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  • Quantum-Like Models Cannot Account for the Conjunction Fallacy.Thomas Boyer-Kassem, Sébastien Duchêne & Eric Guerci - 2016 - Theory and Decision 81 (4):479-510.
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  • Why the Conjunction Effect Is Rarely a Fallacy: How Learning Influences Uncertainty and the Conjunction Rule.Phil Maguire, Philippe Moser, Rebecca Maguire & Mark T. Keane - 2018 - Frontiers in Psychology 9.
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  • On the Conjunction Fallacy and the Meaning of and , yet Again: A Reply To.Katya Tentori & Vincenzo Crupi - 2012 - Cognition 122 (2):123-134.
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  • Confirmation as Partial Entailment: A Representation Theorem in Inductive Logic.Vincenzo Crupi & Katya Tentori - 2013 - Journal of Applied Logic 11 (4):364-372.
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  • Judging the Probability of Hypotheses Versus the Impact of Evidence: Which Form of Inductive Inference Is More Accurate and Time‐Consistent?Katya Tentori, Nick Chater & Vincenzo Crupi - 2016 - Cognitive Science 40 (3):758-778.
    Inductive reasoning requires exploiting links between evidence and hypotheses. This can be done focusing either on the posterior probability of the hypothesis when updated on the new evidence or on the impact of the new evidence on the credibility of the hypothesis. But are these two cognitive representations equally reliable? This study investigates this question by comparing probability and impact judgments on the same experimental materials. The results indicate that impact judgments are more consistent in time and more accurate than (...)
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  • Shogenji's Measure of Justification and the Inverse Conjunction Fallacy.Martin Jönsson & Elias Assarsson - 2013 - Synthese 190 (15):3075-3085.
    This paper takes issue with a recent proposal due to Shogenji (Synthese 184:29–48, 2012). In his paper, Shogenji introduces J, a normatively motivated formal measure of justification (and of confirmation), and then proceeds to recruit it descriptively in an explanation of the conjunction fallacy. We argue that this explanation is undermined by the fact that it cannot be extended in any natural way to the inverse conjunction fallacy, a more recently discovered, closely related fallacy. We point out that since the (...)
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  • Can Probability Theory Explain Why Closure is Both Intuitive and Prone to Counterexamples?Marcello Di Bello - 2018 - Philosophical Studies 175 (9):2145-2168.
    Epistemic closure under known implication is the principle that knowledge of \ and knowledge of \, together, imply knowledge of \. This principle is intuitive, yet several putative counterexamples have been formulated against it. This paper addresses the question, why is epistemic closure both intuitive and prone to counterexamples? In particular, the paper examines whether probability theory can offer an answer to this question based on four strategies. The first probability-based strategy rests on the accumulation of risks. The problem with (...)
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  • Robustness Analysis as Explanatory Reasoning.Jonah N. Schupbach - 2016 - British Journal for the Philosophy of Science:axw008.
    When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be robust. This paper investigates the logic of such "robustness analysis" [RA]. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a (...)
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  • Skepticism and Epistemic Closure: Two Bayesian Accounts.Luca Moretti & Tomoji Shogenji - 2017 - International Journal for the Study of Skepticism 7 (1):1-25.
    This paper considers two novel Bayesian responses to a well-known skeptical paradox. The paradox consists of three intuitions: first, given appropriate sense experience, we have justification for accepting the relevant proposition about the external world; second, we have justification for expanding the body of accepted propositions through known entailment; third, we do not have justification for accepting that we are not disembodied souls in an immaterial world deceived by an evil demon. The first response we consider rejects the third intuition (...)
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  • Competing Accounts of Contrastive Coherence.Michael Schippers - 2016 - Synthese 193 (10).
    The proposition that Tweety is a bird coheres better with the proposition that Tweety has wings than with the proposition that Tweety cannot fly. This relationship of contrastive coherence is the focus of the present paper. Based on recent work in formal epistemology we consider various possibilities to model this relationship by means of probability theory. In a second step we consider different applications of these models. Among others, we offer a coherentist interpretation of the conjunction fallacy.
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  • The New Tweety Puzzle: Arguments Against Monistic Bayesian Approaches in Epistemology and Cognitive Science.Matthias Unterhuber & Gerhard Schurz - 2013 - Synthese 190 (8):1407-1435.
    In this paper we discuss the new Tweety puzzle. The original Tweety puzzle was addressed by approaches in non-monotonic logic, which aim to adequately represent the Tweety case, namely that Tweety is a penguin and, thus, an exceptional bird, which cannot fly, although in general birds can fly. The new Tweety puzzle is intended as a challenge for probabilistic theories of epistemic states. In the first part of the paper we argue against monistic Bayesians, who assume that epistemic states can (...)
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  • A Problem for Confirmation Theoretic Accounts of the Conjunction Fallacy.Martin Jönsson & Elias Assarsson - 2016 - Philosophical Studies 173 (2):437-449.
    This paper raises a principled objection against the idea that Bayesian confirmation theory can be used to explain the conjunction fallacy. The paper demonstrates that confirmation-based explanations are limited in scope and can only be applied to cases of the fallacy of a certain restricted kind. In particular; confirmation-based explanations cannot account for the inverse conjunction fallacy, a more recently discovered form of the conjunction fallacy. Once the problem has been set out, the paper explores four different ways for the (...)
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  • Source Reliability and the Conjunction Fallacy.Andreas Jarvstad & Ulrike Hahn - 2011 - Cognitive Science 35 (4):682-711.
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  • A Case of Confusing Probability and Confirmation.Jeanne Peijnenburg - 2012 - Synthese 184 (1):101-107.
    Tom Stoneham put forward an argument purporting to show that coherentists are, under certain conditions, committed to the conjunction fallacy. Stoneham considers this argument a reductio ad absurdum of any coherence theory of justification. I argue that Stoneham neglects the distinction between degrees of confirmation and degrees of probability. Once the distinction is in place, it becomes clear that no conjunction fallacy has been committed.
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  • Linguistic Convergence in Verbs for Belief-Forming Processes.Martin L. Jönsson - 2015 - Philosophical Psychology 28 (1):114-138.
    This paper has two goals. First, it aims to investigate the empirical assumptions of a recent proposal due to Olsson (forthcoming), according to which the generality problem for process-reliabilism can be approached by recruiting patterns and models from the basic-level research in cognitive psychology. Second, the paper attempts to generalize findings in the basic-level literature pertaining to concrete nouns to the abstract verbs that denote belief-forming processes. I will demonstrate that verbs for belief-forming processes exhibit the kind of linguistic convergence (...)
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  • Towards a Pattern-Based Logic of Probability Judgements and Logical Inclusion “Fallacies”.Momme von Sydow - 2016 - Thinking and Reasoning 22 (3):297-335.
    ABSTRACTProbability judgements entail a conjunction fallacy if a conjunction is estimated to be more probable than one of its conjuncts. In the context of predication of alternative logical hypothesis, Bayesian logic provides a formalisation of pattern probabilities that renders a class of pattern-based CFs rational. BL predicts a complete system of other logical inclusion fallacies. A first test of this prediction is investigated here, using transparent tasks with clear set inclusions, varying in observed frequencies only. Experiment 1 uses data where (...)
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