17 found
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  1.  18
    Conflict Detection, Dual Processes, and Logical Intuitions: Some Clarifications.Wim De Neys - 2014 - Thinking and Reasoning 20 (2):169-187.
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  2.  21
    Conflict Monitoring in Dual Process Theories of Thinking.Wim De Neys & Tamara Glumicic - 2008 - Cognition 106 (3):1248-1299.
  3.  44
    The 'Whys' and 'Whens' of Individual Differences in Thinking Biases.Wim De Neys & Jean-François Bonnefon - 2013 - Trends in Cognitive Sciences 17 (4):172-178.
  4.  13
    Evolutionary Modules and Bayesian Facilitation: The Role of General Cognitive Resources.Elise Lesage, Gorka Navarrete & Wim De Neys - 2012 - Thinking and Reasoning 19 (1):27 - 53.
    (2013). Evolutionary modules and Bayesian facilitation: The role of general cognitive resources. Thinking & Reasoning: Vol. 19, No. 1, pp. 27-53. doi: 10.1080/13546783.2012.713177.
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  5.  16
    Face-Ism and Kernels of Truth in Facial Inferences.Jean-François Bonnefon, Astrid Hopfensitz & Wim De Neys - 2015 - Trends in Cognitive Sciences 19 (8):421-422.
  6.  7
    Belief Inhibition During Thinking: Not Always Winning but at Least Taking Part.Wim De Neys & Samuel Franssens - 2009 - Cognition 113 (1):45-61.
  7.  10
    The Modular Nature of Trustworthiness Detection.Jean-François Bonnefon, Astrid Hopfensitz & Wim De Neys - 2013 - Journal of Experimental Psychology: General 142 (1):143.
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  8.  34
    The Effortless Nature of Conflict Detection During Thinking.Wim de Neys & Samuel Franssens - 2011 - Thinking and Reasoning 15 (2):105-128.
    Dual process theories conceive human thinking as an interplay between heuristic processes that operate automatically and analytic processes that demand cognitive effort. The interaction between these two types of processes is poorly understood. De Neys and Glumicic (2008) recently found that most of the time heuristic processes are successfully monitored. This monitoring, however, would not demand as many cognitive resources as the analytic thinking that is needed to solve reasoning problems. In the present study we tested the crucial assumption about (...)
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  9.  11
    Beyond Response Output: More Logical Than We Think.Wim De Neys - 2009 - Behavioral and Brain Sciences 32 (1):87-88.
    Oaksford & Chater (O&C) rely on a data fitting approach to show that a Bayesian model captures the core reasoning data better than its logicist rivals. The problem is that O&C's modeling has focused exclusively on response output data. I argue that this exclusive focus is biasing their conclusions. Recent studies that focused on the processes that resulted in the response selection are more positive for the role of logic.
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  10.  18
    Working Memory and Everyday Conditional Reasoning: Retrieval and Inhibition of Stored Counterexamples.Wim De Neys, Walter Schaeken & Géry D'Ydewalle - 2005 - Thinking and Reasoning 11 (4):349-381.
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  11. Counterexample Retrieval and Inhibition During Conditional Reasoning: Direct Evidence From Memory Probing.Wim De Neys - 2010 - In Mike Oaksford & Nick Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thinking. Oxford University Press.
     
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  12.  27
    Working Memory and Counterexample Retrieval for Causal Conditionals.Wim De Neys, Walter Schaeken & Géry D'Ydewalle - 2005 - Thinking and Reasoning 11 (2):123-150.
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  13.  9
    Working Memory and Everyday Conditional Reasoning: Retrieval and Inhibition of Stored Counterexamples.Wim de Neys, Walter Schaeken & G. - 2005 - Thinking and Reasoning 11 (4):349 – 381.
    Two experiments examined the contribution of working memory (WM) to the retrieval and inhibition of background knowledge about counterexamples (alternatives and disablers, Cummins, 1995) during conditional reasoning. Experiment 1 presented a conditional reasoning task with everyday, causal conditionals to a group of people with high and low WM spans. High spans rejected the logically invalid AC and DA inferences to a greater extent than low spans, whereas low spans accepted the logically valid MP and MT inferences less frequently than high (...)
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  14.  16
    The Grim Reasoner: Analytical Reasoning Under Mortality Salience.Bastien Trémolière, Wim De Neys & Jean-François Bonnefon - 2013 - Thinking and Reasoning 20 (3):333-351.
  15.  17
    Nested Sets and Base-Rate Neglect: Two Types of Reasoning?Wim De Neys - 2007 - Behavioral and Brain Sciences 30 (3):260-261.
    Barbey & Sloman (B&S) claim that frequency formats and other task manipulations induce people to substitute associative thinking for rule-based thinking about nested sets. My critique focuses on the substitution assumption. B&S demonstrate that nested sets are important to solve base-rate problems but they do not show that thinking about these nested sets relies on a different type of reasoning.
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  16.  14
    Working Memory and Counterexample Retrieval for Causal Conditionals.Wim de Neys, Walter Schaeken & G. - 2005 - Thinking and Reasoning 11 (2):123 – 150.
    The present study is part of recent attempts to specify the characteristics of the counterexample retrieval process during causal conditional reasoning. The study tried to pinpoint whether the retrieval of stored counterexamples (alternative causes and disabling conditions) for a causal conditional is completely automatic in nature or whether the search process also demands executive working memory (WM) resources. In Experiment 1, participants were presented with a counterexample generation task and a measure of WM capacity. We found a positive relation between (...)
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  17.  5
    The Freak in All of Us: Logical Truth Seeking Without Argumentation.Wim De Neys - 2011 - Behavioral and Brain Sciences 34 (2):75-76.
    Mercier and Sperber (M&S) sketch a bleak picture of logical reasoning in classic, nonargumentative tasks. I argue that recent processing data indicate that despite people's poor performance they at least seek to adhere to traditional logical norms in these tasks. This implies that classic reasoning tasks are less artificialthan M&S's framework suggests.
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