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  1. Throwing out the baby with the bathwater? Let's not overstate the overselling of the base rate fallacy.Cynthia J. Thomsen & Eugene Borgida - 1996 - Behavioral and Brain Sciences 19 (1):39-40.
    Koehler's summary and critique of research on the base rate fallacy is cogent and persuasive. However, he may have overstated the case, and his suggestions for future research may be too restrictive. We agree that methodological approaches to this topic should be broadened, but we argue that experimental laboratory research and the Bayesian normative standard are useful and should not be abandoned.
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  • Base rates do not constrain nonprobability judgments.Paul D. Windschitl & Gary L. Wells - 1996 - Behavioral and Brain Sciences 19 (1):40-41.
    Base rates have no necessary relation to judgments that are not themselves probabilities. There is no logical imperative, for instance, that behavioral base rates must affect causal attributions or that base rate information should affect judgments of legal liability. Decision theorists should be cautious in arguing that base rates place normative constraints on judgments of anything other than posterior probabilities.
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  • Probabilistic fallacies.Henry E. Kyburg - 1996 - Behavioral and Brain Sciences 19 (1):31-31.
    Two distinct issues are sometimes confused in the base rate literature: Why do people make logical mistakes in the assessment of probabilities? and why do subjects not use base rates the way experimenters do? The latter problem may often reflect differences in an implicit reference class rather than a disinclination to update a base rate by Bayes' theorem. Also important are considerations concerning the interaction of several potentially relevant base rates.
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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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  • 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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  • 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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  • P(D/H), P(D/˜H), and base rate consideration.Yechiel Klar - 1996 - Behavioral and Brain Sciences 19 (1):26-27.
    Failure to consider base rate is regarded as potentially hazardous, mainly because its consideration is assumed to be determined solely by P(H/D), the probability of the individuating data if the hypothesis is true, and not at all by P(D/˜H), the probability if the hypothesis is false. However, when P(D/˜H) is unconfounded from P(D/H), it turns out to be the stronger determinant of base rate consideration.
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  • Critical and natural sensitivity to base rates.Gernot D. Kleiter - 1996 - Behavioral and Brain Sciences 19 (1):27-29.
    This commentary discusses three points: (1) The implications of the fact that it is rational to ignore base rates if probabilities are estimated by frequencies from samples without missing data (natural sampling); (2) second order probabilities distributions are a plausible way to model imprecise probabilities; and (3) Bayesian networks represent a normative reference for multi-cue models of probabilistic inference.
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  • Base rates in the applied domain of accounting.Lisa Koonce - 1996 - Behavioral and Brain Sciences 19 (1):29-30.
    Koehler's call for a reanalysis of the base rate fallacy is particularly important in the applied domain of accounting, since base rate data appear to be an important input for many accounting tasks. In this commentary I discuss the use of base rates in accounting and explain why more flexible standards of performance are important when judging the use of base rates.
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  • Studying the use of base rates: Normal science or shifting paradigm?Joachim Krueger - 1996 - Behavioral and Brain Sciences 19 (1):30-30.
    The underutilization of base rates is a consistent finding. The strong claim that base rates are ignored has been rejected and this needs no further emphasis. Following the path of “normal science,” research examines the conditions predicting changes in the degree of underutilization. A scientific revolution that might dethrone the heuristics and biases paradigm is not in sight.
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  • Base rates, stereotypes, and judgmental accuracy.David C. Funder - 1996 - Behavioral and Brain Sciences 19 (1):22-23.
    The base rate literature has an opposite twin in the social psychological literature on stereotypes, which concludes that people use their preexisting beliefs about probabilistic category attributes too much, rather than not enough. This ironic discrepancy arises because beliefs about category attributes enhance accuracy when the beliefs are accurate and diminish accuracy when they are not. To determine the accuracy of base rate/stereotype beliefs requires research that addresses specific content.
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  • Why do frequency formats improve Bayesian reasoning? Cognitive algorithms work on information, which needs representation.Gerd Gigerenzer - 1996 - Behavioral and Brain Sciences 19 (1):23-24.
    In contrast to traditional research on base-rate neglect, an ecologically-oriented research program would analyze the correspondence between cognitive algorithms and the nature of information in the environment. Bayesian computations turn out to be simpler when information is represented in frequency formats as opposed to the probability formats used in previous research. Frequency formats often enable even uninstructed subjects to perform Bayesian reasoning.
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  • Physicians neglect base rates, and it matters.Robert M. Hamm - 1996 - Behavioral and Brain Sciences 19 (1):25-26.
    A recent study showed physicians' reasoning about a realistic case to be ignorant of base rate. It also showed physicians interpreting information pertinent to base rate differently, depending on whether it was presented early or late in the case. Although these adult reasoners might do better if given hints through talk of relative frequencies, this would not prove that they had no problem of base rate neglect.
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  • The base rate controversy: Is the glass half-full or half-empty?Gideon Keren & Lambert J. Thijs - 1996 - Behavioral and Brain Sciences 19 (1):26-26.
    Setting the two hypotheses of complete neglect and full use of base rates against each other is inappropriate. The proper question concerns the degree to which base rates are used (or neglected), and under what conditions. We outline alternative approaches and recommend regression analysis. Koehler's conclusion that we have been oversold on the base rate fallacy seems to be premature.
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  • The need for a theory of evidential weight.L. Jonathan Cohen - 1996 - Behavioral and Brain Sciences 19 (1):18-19.
    There is a familiar risk of antinomy if fromxisEand p(xisH/xisE) =rit is permissible to infer p(xisH) =r, and what Carnap (1950) called “The requirement of total evidence” will not prevent such antinomies satisfactorily. What is needed instead is a properly developed theory of evidential weight.
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  • Are base rates a natural category of information?Terry Connolly - 1996 - Behavioral and Brain Sciences 19 (1):19-20.
    The base rate fallacy is directly dependent on a particular judgment paradigm in which information may be unambiguously designated as either “base rate” or “individuating,” and in which subjects make two-stage sequential judgments. The paradigm may be a poor match for real world settings, and the fallacy may thus be undefined for natural ecologies of judgment.
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  • The purpose of experiments: Ecological validity versus comparing hypotheses.Robyn M. Dawes - 1996 - Behavioral and Brain Sciences 19 (1):20-20.
    As illustrated by research Koehler himself cites (Dawes et al. 1993), the purpose of experiments is to choose between contrasting explanations of past observations – rather than to seek statistical generalizations about the prevalence of effects. True external validity results not from sampling various problems that are representative of “real world” decision making, but from reproducing an effect in the laboratory with minimal contamination (including from real world factors).
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  • Base rates, experience, and the big picture.Stephen E. Edgell, Robert M. Roe & Clayton H. Dodd - 1996 - Behavioral and Brain Sciences 19 (1):21-21.
    The important question is how people process probabilistic information, not whether they process it in accordance with a normative model that we never should have expected them to be capable of following. Experience is not the cure, as widely thought, to problems with utilizing base rate information.
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  • How to reconsider the base rate fallacy without forgetting the concept of systematic processing.Pablo Fernandez-Berrocal, Julian Almaraz & Susana Segura - 1996 - Behavioral and Brain Sciences 19 (1):21-22.
    Abstract(1) There is enough contradictory evidence regarding the role of base rates in category learning to confirm the nonexistence of biases in such learning. (2) It is not always possible to activate statistical reasoning through frequentist representation. (3) It is necessary to use the concept of systematic processing in reconsidering the published work on biases.
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  • Cognitive algebra versus representativeness heuristic.Norman H. Anderson - 1996 - Behavioral and Brain Sciences 19 (1):17-17.
    Cognitive algebra strongly disproved the representativeness heuristic almost before it was published; and therewith it also disproved the base rate fallacy. Cognitive algebra provides a theoretical foundation for judgment-decision theory through its joint solution to the two fundamental problems – true measurement of subjective values, and cognitive rules for integration of multiple determinants.
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  • The implications of Koehler's approach for fact finding.Craig R. Callen - 1996 - Behavioral and Brain Sciences 19 (1):18-18.
    Koehler's work will assist the effort to understand legal fact finding. It leaves two questions somewhat open: (i) the extent to which empirical research can measure correctness of fact-finding, a function that involves the resolution of normative questions and (ii) the standards judges should use in the absence of the research he advocates.
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  • Irrationality Re-Examined: A Few Comments on the Conjunction Fallacy.Michael Aristidou - 2013 - Open Journal of Philosophy 3 (2):329-336.
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  • A Consequence of Principle.William Flynn - 2001 - Education and Culture 17 (2):4.
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  • How Does the Mind Work? Insights from Biology.Gary Marcus - 2009 - Topics in Cognitive Science 1 (1):145-172.
    Cognitive scientists must understand not just what the mind does, but how it does what it does. In this paper, I consider four aspects of cognitive architecture: how the mind develops, the extent to which it is or is not modular, the extent to which it is or is not optimal, and the extent to which it should or should not be considered a symbol‐manipulating device (as opposed to, say, an eliminative connectionist network). In each case, I argue that insights (...)
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  • Emotions in economic action and interaction.Nina Bandelj - 2009 - Theory and Society 38 (4):347-366.
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  • It’s not fair! Or is it? The promise and the tyranny of evidence-based performance assessment.Elizabeth Bogdan-Lovis, Leonard Fleck & Henry C. Barry - 2012 - Theoretical Medicine and Bioethics 33 (4):293-311.
    Evidence-based medicine (EBM), by its ability to decrease irrational variations in health care, was expected to improve healthcare quality and outcomes. The utility of EBM principles evolved from individual clinical decision-making to wider foundational clinical practice guideline applications, cost containment measures, and clinical quality performance measures. At this evolutionary juncture one can ask the following questions. Given the time-limited exigencies of daily clinical practice, is it tenable for clinicians to follow guidelines? Whose or what interests are served by applying performance (...)
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  • Polanyi's tacit knowing and the relevance of epistemology to clinical medicine.Stephen G. Henry - 2010 - Journal of Evaluation in Clinical Practice 16 (2):292-297.
    Most clinicians take for granted a simple, reductionist understanding of medical knowledge that is at odds with how they actually practice medicine; routine medical decisions incorporate more complicated kinds of information than most standard accounts of medical reasoning suggest. A better understanding of the structure and function of knowledge in medicine can lead to practical improvements in clinical medicine. This understanding requires some familiarity with epistemology, the study of knowledge and its structure, in medicine. Michael Polanyi's theory of tacit knowing (...)
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  • Perception of Interannual Covariation and Strategies for Risk Reduction among Mikea of Madagascar.Bram Tucker - 2007 - Human Nature 18 (2):162-180.
    This paper begins with the hypothesis that Mikea, participants in a mixed foraging–fishing–farming–herding economy of southwestern Madagascar, may attempt to reduce interannual variance in food supply caused by unpredictable rainfall by following a simple rule-of-thumb: Practice an even mix of activities that covary positively with rainfall and activities that covary negatively with rainfall. Results from a historical matrix participatory exercise confirm that Mikea perceive that foraging and farming outcomes covary positively or negatively with rainfall. This paper further considers whether Mikea (...)
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  • Social Context in HCl: A New Framework for Mental Models, Cooperation, and Communication.Giuseppe Mantovani - 1996 - Cognitive Science 20 (2):237-269.
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  • On Spearman's “problem of correlation”.John B. Carroll - 1985 - Behavioral and Brain Sciences 8 (1):7-7.
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  • Quinity, isotropy, and Wagnerian rapture.Georges Rey - 1985 - Behavioral and Brain Sciences 8 (1):27-28.
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  • Module or muddle?Janet Dean Fodor - 1985 - Behavioral and Brain Sciences 8 (1):7-9.
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  • Too little and latent.John Morton - 1985 - Behavioral and Brain Sciences 8 (1):26-27.
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  • Encapsulation and expectation.Roger Schank & Larry Hunter - 1985 - Behavioral and Brain Sciences 8 (1):29-30.
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  • Organic insight into mental organs.Barry Schwartz - 1985 - Behavioral and Brain Sciences 8 (1):30-31.
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  • Combe's crucible and the music of the modules.John C. Marshall - 1985 - Behavioral and Brain Sciences 8 (1):23-24.
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  • The centrality of modules.Howard Gardner - 1985 - Behavioral and Brain Sciences 8 (1):12-14.
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  • Vertically unparalleled.Ignatius G. Mattingly & Alvin M. Liberman - 1985 - Behavioral and Brain Sciences 8 (1):24-26.
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  • Lexicon as module.Mark S. Seidenberg - 1985 - Behavioral and Brain Sciences 8 (1):31-32.
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  • Reply module.Jerry A. Fodor - 1985 - Behavioral and Brain Sciences 8 (1):33-42.
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  • Modularity: Contextual interactions and the tractability of nonmodular systems.Sam Glucksberg - 1985 - Behavioral and Brain Sciences 8 (1):14-15.
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  • Evidence for and against modularity.Earl Hunt - 1985 - Behavioral and Brain Sciences 8 (1):19-20.
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  • The modularity of behavior.Peter R. Killeen - 1985 - Behavioral and Brain Sciences 8 (1):22-23.
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  • Fodor's holism.Clark Glymour - 1985 - Behavioral and Brain Sciences 8 (1):15-16.
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  • A modular sense of place?C. R. Gallistel & Ken Cheng - 1985 - Behavioral and Brain Sciences 8 (1):11-12.
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  • Parallel processing explains modular informational encapsulation.Marcel Kinsbourne - 1985 - Behavioral and Brain Sciences 8 (1):23-23.
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  • Faculties, modules, and computers.Daniel N. Robinson - 1985 - Behavioral and Brain Sciences 8 (1):28-29.
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  • What constitutes a module?Peter W. Jusczyk & Asher Cohen - 1985 - Behavioral and Brain Sciences 8 (1):20-21.
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  • The mind as a Necker Cube.Jerome Kagan - 1985 - Behavioral and Brain Sciences 8 (1):21-22.
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  • Controlled versus automatic processing.Robert J. Sternberg - 1985 - Behavioral and Brain Sciences 8 (1):32-33.
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