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  1. Mental models and the tractability of everyday reasoning.Mike Oaksford - 1993 - Behavioral and Brain Sciences 16 (2):360-361.
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  • A rational analysis of the selection task as optimal data selection.Mike Oaksford & Nick Chater - 1994 - Psychological Review 101 (4):608-631.
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  • Psychology, statistics, and analytical epistemology.Richard E. Nisbett & Paul Thagard - 1983 - Behavioral and Brain Sciences 6 (2):257-258.
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  • Peter Wason (1924-2003).Stephen Newstead - 2003 - Thinking and Reasoning 9 (3):177-184.
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  • Do mental models provide an adequate account of syllogistic reasoning performance?Stephen E. Newstead - 1993 - Behavioral and Brain Sciences 16 (2):359-360.
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  • Naïve optimality: Subjects' heuristics can be better motivated than experimenters' optimal models.Jonathan D. Nelson - 2009 - Behavioral and Brain Sciences 32 (1):94-95.
    Is human cognition best described by optimal models, or by adaptive but suboptimal heuristic strategies? It is frequently hard to identify which theoretical model is normatively best justified. In the context of information search, naoptimal” models.
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  • Can philosophy resolve empirical issues?Clifford R. Mynatt, Ryan D. Tweney & Michael E. Doherty - 1983 - Behavioral and Brain Sciences 6 (3):506.
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  • Sample-size salience and statistical inference.John Murray, Marie Iding, Hilary Farris & Russ Revlin - 1987 - Bulletin of the Psychonomic Society 25 (5):367-369.
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  • On the nature of the conjunction fallacy.Rodrigo Moro - 2009 - Synthese 171 (1):1 - 24.
    In a seminal work, Tversky and Kahneman showed that in some contexts people tend to believe that a conjunction of events (e.g., Linda is a bank teller and is active in the feminist movement) is more likely to occur than one of the conjuncts (e.g., Linda is a bank teller). This belief violates the conjunction rule in probability theory. Tversky and Kahneman called this phenomenon the “conjunction fallacy”. Since the discovery of the phenomenon in 1983, researchers in psychology and philosophy (...)
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  • Does consequentialism pay?Adam Morton - 1994 - Behavioral and Brain Sciences 17 (1):24-24.
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  • The infinite regress of optimization.Philippe Mongin - 1991 - Behavioral and Brain Sciences 14 (2):229-230.
    A comment on Paul Schoemaker's target article in Behavioral and Brain Sciences, 14 (1991), p. 205-215, "The Quest for Optimality: A Positive Heuristic of Science?" (https://doi.org/10.1017/S0140525X00066140). This comment argues that the optimizing model of decision leads to an infinite regress, once internal costs of decision (i.e., information and computation costs) are duly taken into account.
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  • False memories of the future: A critique of the applications of probabilistic reasoning to the study of cognitive processes.Mihnea Moldoveanu & Ellen Langer - 2002 - Psychological Review 109 (2):358-375.
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  • Should reason be fragmented?Nenad Miščević - 1996 - International Studies in the Philosophy of Science 10 (1):23-36.
    Cognitive relativists‐pragmatists (Stich, Churchland) claim that human cognitive strategies, lacking a common goal, are in addition divergent to the point of incommensurability. They appeal to the study of reasoning heuristics for evidence on cognitive diversity and incorrigibility. It is here argued that no such evidence is offered by the research, which, on the contrary (1) presents heuristics as uniform across great variations; (2) offers advice for correcting and improving human reasoning; and (3) very often postulates a uniformity of core logical (...)
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  • Two dynamic criteria for validating claims of optimality.Geoffrey F. Miller - 1991 - Behavioral and Brain Sciences 14 (2):228-229.
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  • Dennett's rational animals: And how behavorism overlooked them.Ruth Garrett Millikan - 1983 - Behavioral and Brain Sciences 6 (3):372-373.
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  • Contrapositivism; or, The only evidence worth paying for is contained in the negatives.David Miller - 1983 - Behavioral and Brain Sciences 6 (2):256-257.
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  • Complexity and optimality.Dauglas A. Miller & Steven W. Zucker - 1991 - Behavioral and Brain Sciences 14 (2):227-228.
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  • Parlez-vous baboon, Bwana Sherlock?E. W. Menzel - 1983 - Behavioral and Brain Sciences 6 (3):371-372.
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  • Conservatism revisited: Base rates, prior probabilities, and averaging strategies.Nancy Paule Melone & Timothy W. McGuire - 1996 - Behavioral and Brain Sciences 19 (1):36-37.
    Consistent with Koehler's position, we propose a generalization of the base rate fallacy and earlier conservatism literatures. In studies using both traditional tasks and new tasks based on ecologically valid base rates, our subjects typically underweight individuating information at least as much as they underweight base rates. The implications of cue consistency for averaging heuristics are discussed.
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  • How are base rates used? Interactive and group effects.Peter J. McLeod & Margo Watt - 1996 - Behavioral and Brain Sciences 19 (1):35-36.
    Koehler is right that base rate information is used, to various degrees, both in laboratory tasks and in everyday life. However, it is not time to turn our backs on laboratory tasks and focus solely on ecologically valid decision making. Tightly controlled experimental data are still needed to understandhowbase rate information is used, and how this varies among groups.
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  • Which reference class is evoked?Craig R. M. McKenzie & Jack B. Soll - 1996 - Behavioral and Brain Sciences 19 (1):34-35.
    Any instance (i.e., event, behavior, trait) belongs to infinitely many reference classes, hence there are infinitely many base rates from which to choose. People clearly do not entertain all possible reference classes, however, so something must be limiting the search space. We suggest some possible mechanisms that determine which reference class is evoked for the purpose of judgment and decision.
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  • Intentions as goads.David McFarland - 1983 - Behavioral and Brain Sciences 6 (3):369-370.
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  • Optimization and connectionism are two different things.Drew McDermott - 1989 - Behavioral and Brain Sciences 12 (3):483-484.
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  • First things first: What is a base rate?Clark McCauley - 1996 - Behavioral and Brain Sciences 19 (1):33-34.
    The fallacy beneath the base rate fallacy is that we know what a base rate is. We talk as if base rates and individuating information were two different kinds of information. From a Bayesian perspective, however, the only difference between base rate and individuating information is – which comes first.
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  • Consequentialism in haste.Roger A. McCain - 1994 - Behavioral and Brain Sciences 17 (1):23-24.
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  • Acceptability, analogy, and the acceptability of analogies.Robert N. McCauley - 1989 - Behavioral and Brain Sciences 12 (3):482-483.
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  • Straining the word “optimal”.James E. Mazur - 1991 - Behavioral and Brain Sciences 14 (2):227-227.
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  • Adaptive rationality and identifiability of psychological processes.Dominic W. Massaro & Daniel Friedman - 1991 - Behavioral and Brain Sciences 14 (3):499-501.
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  • Nuancing should not imply neglecting.Howard Margolis - 1996 - Behavioral and Brain Sciences 19 (1):32-33.
    Koehler is right to argue for more nuanced interpretation of base rate anomalies. These anomalies are best understood in relation to a broader class of cognitive anomalies, which are important for theory and practice. Recognizing a need for more nuanced analysis should not be taken as a license for treating the effects as “explained away.”.
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  • The influence of responsibility and guilt on naive hypothesis-testing.Francesco Mancini & Amelia Gangemi - 2004 - Thinking and Reasoning 10 (3):289-320.
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  • New science for old.Bruce Mangan & Stephen Palmer - 1989 - Behavioral and Brain Sciences 12 (3):480-482.
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  • Models for deontic deduction.K. I. Manktelow - 1993 - Behavioral and Brain Sciences 16 (2):357-357.
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  • Visualizing the possibilities.Bruce J. MacLennan - 1993 - Behavioral and Brain Sciences 16 (2):356-357.
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  • The folk concept of intentional action: Philosophical and experimental issues.Edouard Machery - 2008 - Mind and Language 23 (2):165–189.
    Recent experimental fi ndings by Knobe and others ( Knobe, 2003; Nadelhoffer, 2006b; Nichols and Ulatowski, 2007 ) have been at the center of a controversy about the nature of the folk concept of intentional action. I argue that the signifi cance of these fi ndings has been overstated. My discussion is two-pronged. First, I contend that barring a consensual theory of conceptual competence, the signifi cance of these experimental fi ndings for the nature of the concept of intentional action (...)
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  • Conditional reasoning and conditional logic.William G. Lycan - 1994 - Philosophical Studies 76 (2-3):223 - 245.
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  • Explanationism, ECHO, and the connectionist paradigm.William G. Lycan - 1989 - Behavioral and Brain Sciences 12 (3):480-480.
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  • Epistemic value.William G. Lycan - 1985 - Synthese 64 (2):137 - 164.
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  • Gestalt theory, formal models and mathematical modeling.Abraham S. Luchins & Edith H. Luchins - 1993 - Behavioral and Brain Sciences 16 (2):355-356.
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  • Temporalidad Y relaciones de inclusión: El procesamiento de la regla condicional en la tarea de selección Y sus dificultades.Miguel López Astorga - 2011 - Alpha (Osorno) 32:215-234.
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  • Normative theories of rationality: Occam's razor, Procrustes' bed?Lola L. Lopes - 1983 - Behavioral and Brain Sciences 6 (2):255-256.
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  • Resiliency, robustness and rationality of probability judgements.James Logue - 1997 - International Studies in the Philosophy of Science 11 (1):21 – 34.
    This paper addresses and rejects claims that one can demonstrate experimentally that most untutored subjects are systematically and incurably irrational in their probability judgements and in some deductive reasoning tasks. From within a strongly subjectivist theory of probability, it develops the notions of resiliency —a measure of stability of judgements—and robustness —a measure of expected stability. It then becomes possible to understand subjects' behaviour in the Wason selection task, in examples which have been claimed to involve a 'base-rate fallacy', in (...)
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  • Perspectivism, Deontologism and Epistemic Poverty.Robert Lockie - 2016 - Social Epistemology 30 (2):133-149.
    The epistemic poverty objection is commonly levelled by externalists against deontological conceptions of epistemic justification. This is that an “oughts” based account of epistemic justification together with “ought” implies “can” must lead us to hold to be justified, epistemic agents who are objectively not truth-conducive cognizers. The epistemic poverty objection has led to a common response from deontologists, namely to embrace accounts of bounded rationality—subjective, practical or regulative accounts rather than objective, absolute or theoretical accounts. But the bounds deontological epistemologists (...)
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  • The scope and ingenuity of evolutionary systems.Dan Lloyd - 1983 - Behavioral and Brain Sciences 6 (3):368-369.
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  • Elementary errors about evolution.Richard C. Lewontin - 1983 - Behavioral and Brain Sciences 6 (3):367-368.
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  • Who commits the base rate fallacy?Isaac Levi - 1983 - Behavioral and Brain Sciences 6 (3):502.
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  • The example of psychology: Optimism, not optimality.Daniel S. Levine - 1991 - Behavioral and Brain Sciences 14 (2):225-226.
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  • Jonathan Baron, consequentialism and error theory.Sanford S. Levy - 1994 - Behavioral and Brain Sciences 17 (1):22-23.
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  • Fallacy and controversy about base rates.Isaac Levi - 1996 - Behavioral and Brain Sciences 19 (1):31-32.
    Koehler's target article attempts a balanced view of the relevance of knowledge of base rates to judgments of subjective or credal probability, but he is not sensitive enough to the difference between requiring and permitting the equation of probability judgments with base rates, the interaction between precision of base rate and reference class information, and the possibility of indeterminate probability judgment.
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  • Explanatory coherence in neural networks?Daniel S. Levine - 1989 - Behavioral and Brain Sciences 12 (3):479-479.
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  • Conjunctive bliss.Isaac Levi - 1983 - Behavioral and Brain Sciences 6 (2):254-255.
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