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  1. Toward a Reasons-First View of Normative Background Conditions.Andrés G. Garcia & Jakob Green Werkmäster - forthcoming - Philosophia:1-12.
    Background conditions are thought to explain how objects can have value in virtue of certain features and how reasons can consist in certain facts. The following paper provides an account of what background conditions are and what effect they have on normative features. It defends the idea that if values depend on reasons, then there is nothing really surprising or mysterious about the presence of background conditions in normative explanations. Background conditions turn out to be a natural and predictable result (...)
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  • Varieties of Inference?Anna-Sara Malmgren - 2018 - Philosophical Issues 28 (1):221-254.
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  • Weighing Up Physical Causes: Effects of Culture, Linguistic Cues and Content.Sieghard Beller, Jie Song & Andrea Bender - 2009 - Journal of Cognition and Culture 9 (3-4):347-365.
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  • Distinguishing Between Causes and Enabling Conditions—Through Mental Models or Linguistic Cues?Gregory Kuhnmünch & Sieghard Beller - 2005 - Cognitive Science 29 (6):1077-1090.
  • Common-Sense Causation in the Law.Andrew Summers - 2018 - Oxford Journal of Legal Studies 38 (4):793-821.
    Judges often invoke ‘common sense’ when deciding questions of legal causation. I draw on empirical evidence to refine the common-sense theory of legal causation developed by Hart and Honoré in Causation in the Law. I show that the two main common-sense principles that Hart and Honoré identified are empirically well founded; I also show how experimental research into causal selection can be used to specify these principles with greater precision than before. This exploratory approach can provide legal scholars with a (...)
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  • Bayesian Generic Priors for Causal Learning.Hongjing Lu, Alan L. Yuille, Mimi Liljeholm, Patricia W. Cheng & Keith J. Holyoak - 2008 - Psychological Review 115 (4):955-984.
  • Covariation in Natural Causal Induction.Patricia W. Cheng & Laura R. Novick - 1992 - Psychological Review 99 (2):365-382.
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  • For Want of a Nail: How Absences Cause Events.Phillip Wolff, Aron K. Barbey & Matthew Hausknecht - 2010 - Journal of Experimental Psychology: General 139 (2):191-221.
  • Judgment Dissociation Theory: An Analysis of Differences in Causal, Counterfactual and Covariational Reasoning.David R. Mandel - 2003 - Journal of Experimental Psychology: General 132 (3):419.
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  • Naive Causality: A Mental Model Theory of Causal Meaning and Reasoning.Eugenia Goldvarg & P. N. Johnson-Laird - 2001 - Cognitive Science 25 (4):565-610.
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  • Children's Use of Counterfactual Thinking in Causal Reasoning.Paul L. Harris, Tim German & Patrick Mills - 1996 - Cognition 61 (3):233-259.
  • Dynamics and the Perception of Causal Events.Phillip Wolff - 2006 - Understanding Events.
    We use our knowledge of causal relationships to imagine possible events. We also use these relationships to look deep into the past and infer events that were not witnessed or to infer what can not be directly seen in the present. Knowledge of causal relationships allows us to go beyond the here and now. This chapter introduces a new theoretical framework for how this very basic concept might be mentally represented. It proposes an epistemological theory of causation — that is, (...)
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  • Precis Of.D. M. Wegner - 2004 - Behavioral and Brain Sciences 27.
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  • The Good, the Bad, and the Timely: How Temporal Order and Moral Judgment Influence Causal Selection.Kevin Reuter, Lara Kirfel, Raphael van Riel & Luca Barlassina - 2014 - Frontiers in Psychology 5:1-10.
    Causal selection is the cognitive process through which one or more elements in a complex causal structure are singled out as actual causes of a certain effect. In this paper, we report on an experiment in which we investigated the role of moral and temporal factors in causal selection. Our results are as follows. First, when presented with a temporal chain in which two human agents perform the same action one after the other, subjects tend to judge the later agent (...)
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  • The Role of Covariation Versus Mechanism Information in Causal Attribution.Woo-Kyoung Ahn, Charles W. Kalish, Douglas L. Medin & Susan A. Gelman - 1995 - Cognition 54 (3):299-352.
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  • Representing Causation.Phillip Wolff - 2007 - Journal of Experimental Psychology: General 136 (1):82-111.
    The dynamics model, which is based on Talmy’s (1988) theory of force dynamics, characterizes causation as a pattern of forces and a position vector. In contrast to counterfactual and probabilistic models, the dynamics model naturally distinguishes between different cause-related concepts and explains the induction of causal relationships from single observations. Support for the model is provided in experiments in which participants categorized 3D animations of realistically rendered objects with trajectories that were wholly determined by the force vectors entered into a (...)
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  • Direct Causation in the Linguistic Coding and Individuation of Causal Events.Phillip Wolff - 2003 - Cognition 88 (1):1-48.
  • Constraints and Nonconstraints in Causal Learning: Reply to White and to Luhmann and Ahn.Patricia W. Cheng & Laura R. Novick - 2005 - Psychological Review 112 (3):694-706.
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  • Mental Health Clinicians' Beliefs About the Biological, Psychological, and Environmental Bases of Mental Disorders.Woo-Kyoung Ahn, Caroline C. Proctor & Elizabeth H. Flanagan - 2009 - Cognitive Science 33 (2):147-182.
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  • The Meaning of Cause and Prevent: The Role of Causal Mechanism.Clare R. Walsh & Steven A. Sloman - 2011 - Mind and Language 26 (1):21-52.
    How do people understand questions about cause and prevent? Some theories propose that people affirm that A causes B if A's occurrence makes a difference to B's occurrence in one way or another. Other theories propose that A causes B if some quantity or symbol gets passed in some way from A to B. The aim of our studies is to compare these theories' ability to explain judgements of causation and prevention. We describe six experiments that compare judgements for causal (...)
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  • Categorization as Causal Reasoning⋆.Bob Rehder - 2003 - Cognitive Science 27 (5):709-748.
    A theory of categorization is presented in which knowledge of causal relationships between category features is represented in terms of asymmetric and probabilistic causal mechanisms. According to causal‐model theory, objects are classified as category members to the extent they are likely to have been generated or produced by those mechanisms. The empirical results confirmed that participants rated exemplars good category members to the extent their features manifested the expectations that causal knowledge induces, such as correlations between feature pairs that are (...)
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  • Theories of Reasoning and the Computational Explanation of Everyday Inference.Mike Oaksford & Nick Chater - 1995 - Thinking and Reasoning 1 (2):121 – 152.
  • Mental Models and Causal Explanation: Judgements of Probable Cause and Explanatory Relevance.Denis J. Hilton - 1996 - Thinking and Reasoning 2 (4):273 – 308.
    Good explanations are not only true or probably true, but are also relevant to a causal question. Current models of causal explanation either only address the question of the truth of an explanation, or do not distinguish the probability of an explanation from its relevance. The tasks of scenario construction and conversational explanation are distinguished, which in turn shows how scenarios can interact with conversational principles to determine the truth and relevance of explanations. The proposed model distinguishes causal discounting from (...)
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  • How Prescriptive Norms Influence Causal Inferences.Jana Samland & Michael R. Waldmann - 2016 - Cognition 156:164-176.
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  • The Effect of Controllability and Causality on Counterfactual Thinking.Caren A. Frosch, Suzanne M. Egan & Emily N. Hancock - 2015 - Thinking and Reasoning 21 (3):317-340.
    Previous research on counterfactual thoughts about prevention suggests that people tend to focus on enabling rather than causing events and controllable rather than uncontrollable events. Two experiments explore whether counterfactual thinking about enablers is distinct from counterfactual thinking about controllable events. We presented participants with scenarios in which a cause and an enabler contributed to a negative outcome. We systematically manipulated the controllability of the cause and the enabler and asked participants to generate counterfactuals. The results indicate that when only (...)
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  • Reasoning From Inconsistency to Consistency.P. N. Johnson-Laird, Vittorio Girotto & Paolo Legrenzi - 2004 - Psychological Review 111 (3):640-661.
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