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  1. 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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  • Sets, Net Effects, Causal Mechanisms, Subpopulations, and Understanding: A Comment on Mahoney.Stephen Turner - 2023 - Philosophy of the Social Sciences 53 (5):424-438.
    This comment discusses the suggestions made in Mahoney’s “Constructivist Set-Theoretic Analysis: An Alternative to Essentialist Social Science” (2023). Mahoney presents an approach to cases of intersectionality or confounding which produce causal results unlike those that result from traditional net effects causal modeling. He presents it as an alternative to “essentialism,” which he describes as a cognitive error. These alternatives have the same problems as those he attributes to net effects analysis, with one exception: the method does allow for the identification (...)
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  • On the determinants of the conjunction fallacy: Probability versus inductive confirmation.Katya Tentori, Vincenzo Crupi & Selena Russo - 2013 - Journal of Experimental Psychology: General 142 (1):235.
  • Source Reliability and the Conjunction Fallacy.Andreas Jarvstad & Ulrike Hahn - 2011 - Cognitive Science 35 (4):682-711.
    Information generally comes from less than fully reliable sources. Rationality, it seems, requires that one take source reliability into account when reasoning on the basis of such information. Recently, Bovens and Hartmann (2003) proposed an account of the conjunction fallacy based on this idea. They show that, when statements in conjunction fallacy scenarios are perceived as coming from such sources, probability theory prescribes that the “fallacy” be committed in certain situations. Here, the empirical validity of their model was assessed. The (...)
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  • Being Realist about Bayes, and the Predictive Processing Theory of Mind.Matteo Colombo, Lee Elkin & Stephan Hartmann - 2021 - British Journal for the Philosophy of Science 72 (1):185-220.
    Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have adopted a realist attitude towards the results of Bayesian cognitive science. In this paper, we argue that this realist attitude is unwarranted. The Bayesian research program in cognitive science does not possess special epistemic virtues over alternative approaches for explaining mental phenomena involving uncertainty. In particular, the Bayesian approach is not simpler, more unifying, or more rational than alternatives. It is also contentious that the Bayesian approach (...)
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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.
    Human agents happen to judge that a conjunction of two terms is more probable than one of the terms, in contradiction with the rules of classical probabilities—this is the conjunction fallacy. One of the most discussed accounts of this fallacy is currently the quantum-like explanation, which relies on models exploiting the mathematics of quantum mechanics. The aim of this paper is to investigate the empirical adequacy of major quantum-like models which represent beliefs with quantum states. We first argue that they (...)
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  • Bayesian Epistemology.Stephan Hartmann & Jan Sprenger - 2010 - In Duncan Pritchard & Sven Bernecker (eds.), The Routledge Companion to Epistemology. London: Routledge. pp. 609-620.
    Bayesian epistemology addresses epistemological problems with the help of the mathematical theory of probability. It turns out that the probability calculus is especially suited to represent degrees of belief (credences) and to deal with questions of belief change, confirmation, evidence, justification, and coherence. Compared to the informal discussions in traditional epistemology, Bayesian epis- temology allows for a more precise and fine-grained analysis which takes the gradual aspects of these central epistemological notions into account. Bayesian epistemology therefore complements traditional epistemology; it (...)
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