Search results for 'counterfactual reasoning' (try it on Scholar)

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  1. Noel Hendrickson (2012). Counterfactual Reasoning and the Problem of Selecting Antecedent Scenarios. Synthese 185 (3):365-386.score: 90.0
    A recent group of social scientists have argued that counterfactual questions play an essential role in their disciplines, and that it is possible to have rigorous methods to investigate them. Unfortunately, there has been little (if any) interaction between these social scientists and the philosophers who have long held that rigorous counterfactual reasoning is possible. In this paper, I hope to encourage some fresh thinking on both sides by creating new connections between them. I describe what I (...)
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  2. Brian Leahy, Eva Rafetseder & Josef Perner (forthcoming). Basic Conditional Reasoning: How Children Mimic Counterfactual Reasoning. Studia Logica:1-18.score: 90.0
    Children approach counterfactual questions about stories with a reasoning strategy that falls short of adults’ Counterfactual Reasoning (CFR). It was dubbed “Basic Conditional Reasoning” (BCR) in Rafetseder et al. (Child Dev 81(1):376–389, 2010). In this paper we provide a characterisation of the differences between BCR and CFR using a distinction between permanent and nonpermanent features of stories and Lewis/Stalnaker counterfactual logic. The critical difference pertains to how consistency between a story and a conditional antecedent (...)
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  3. Lance J. Rips & Brian J. Edwards (2013). Inference and Explanation in Counterfactual Reasoning. Cognitive Science 37 (6):1107-1135.score: 72.0
    This article reports results from two studies of how people answer counterfactual questions about simple machines. Participants learned about devices that have a specific configuration of components, and they answered questions of the form “If component X had not operated [failed], would component Y have operated?” The data from these studies indicate that participants were sensitive to the way in which the antecedent state is described—whether component X “had not operated” or “had failed.” Answers also depended on whether the (...)
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  4. Josef Perner & Eva Rafetseder (2011). Is Reasoning From Counterfactual Antecedents Evidence for Counterfactual Reasoning? Thinking and Reasoning 16 (2):131-155.score: 63.0
    In most developmental studies the only error children could make on counterfactual tasks was to answer with the current state of affairs. It was concluded that children who did not show this error are able to reason counterfactually. However, children might have avoided this error by using basic conditional reasoning (Rafetseder, Cristi-Vargas, & Perner, 2010). Basic conditional reasoning takes background assumptions represented as conditionals about how the world works. If an antecedent of one of these conditionals is (...)
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  5. Keith D. Markman, Ronald A. Elizaga, Jennifer J. Ratcliff & Matthew N. McMullen (2007). The Interplay Between Counterfactual Reasoning and Feedback Dynamics in Producing Inferences About the Self. Thinking and Reasoning 13 (2):188 – 206.score: 63.0
    Counterfactual reasoning research typically demonstrates contrast effects—nearly winning evokes frustration, whereas nearly losing evokes exhilaration. The present work, however, describes conditions under which assimilative responses (i.e., when judgements are pulled towards a comparison standard) also occur. Participants solved analogies and learned that they had either nearly attained a target score or nearly failed to attain it. Participants in the no trajectory condition received this feedback in the absence of any prior feedback, whereas those in the trajectory condition received (...)
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  6. Mats Johansson & Linus Broström (2011). Counterfactual Reasoning in Surrogate Decision Making – Another Look. Bioethics 25 (5):244-249.score: 62.0
    Incompetent patients need to have someone else make decisions on their behalf. According to the Substituted Judgment Standard the surrogate decision maker ought to make the decision that the patient would have made, had he or she been competent. Objections have been raised against this traditional construal of the standard on the grounds that it involves flawed counterfactual reasoning, and amendments have been suggested within the framework of possible worlds semantics. The paper shows that while this approach may (...)
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  7. Alan Hájek, Counterfactual Reasoning (Philosophical Aspects)—Quantitative.score: 60.0
    Counterfactuals are a species of conditionals. They are propositions or sentences, expressed by or equivalent to subjunctive conditionals of the form 'if it were the case that A, then it would be the case that B', or 'if it had been the case that A, then it would have been the case that B'; A is called the antecedent, and B the consequent. Counterfactual reasoning typically involves the entertaining of hypothetical states of affairs: the antecedent is believed or (...)
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  8. Morteza Dehghani, Rumen Iliev & Stefan Kaufmann (2012). Causal Explanation and Fact Mutability in Counterfactual Reasoning. Mind and Language 27 (1):55-85.score: 57.0
    Recent work on the interpretation of counterfactual conditionals has paid much attention to the role of causal independencies. One influential idea from the theory of Causal Bayesian Networks is that counterfactual assumptions are made by intervention on variables, leaving all of their causal non-descendants unaffected. But intervention is not applicable across the board. For instance, backtracking counterfactuals, which involve reasoning from effects to causes, cannot proceed by intervention in the strict sense, for otherwise they would be equivalent (...)
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  9. Vincent Spade Paul (1982). Three Theories Ofobligationes:Burley, Kilvington and Swyneshed on Counterfactual Reasoning. History and Philosophy of Logic 3 (1):1-32.score: 57.0
    This paper defends the thesis that the mediaeval genre of logical treatises De obligatiombus contained a theoretical account of counterfacutal reasoning, perhaps the first such account in the history of philosophy. This interpretation helps to explain some of the theoretical disputes in the obligationes literature in the first half of the fourteenth century. Section 1 is introductory. Section 2 presents Walter Burley's theory, while section 3 argues for the counterfactual interpretation of obligationes and section 4 discusses difficulties with (...)
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  10. Jonathan Phillips & Liane Young (2011). Apparent Paradoxes in Moral Reasoning; Or How You Forced Him to Do It, Even Though He Wasn’T Forced to Do It. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society:138-143.score: 54.0
    The importance of situational constraint for moral evaluations is widely accepted in philosophy, psychology, and the law. However, recent work suggests that this relationship is actually bidirectional: moral evaluations can also influence our judgments of situational constraint. For example, if an agent is thought to have acted immorally rather than morally, that agent is often judged to have acted with greater freedom and under less situational constraint. Moreover, when considering interpersonal situations, we judge that an agent who forces another to (...)
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  11. Ana Cristina Quelhas & Ruth Byrne (2003). Reasoning with Deontic and Counterfactual Conditionals. Thinking and Reasoning 9 (1):43 – 65.score: 51.0
    We report two new phenomena of deontic reasoning: (1) For conditionals with deontic content such as, "If the nurse cleaned up the blood then she must have worn rubber gloves", reasoners make more modus tollens inferences (from "she did not wear rubber gloves" to "she did not clean up the blood") compared to conditionals with epistemic content. (2) For conditionals in the subjunctive mood with deontic content, such as, "If the nurse had cleaned up the blood then she must (...)
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  12. Teresa McCormack, Stephen Andrew Butterfill, Christoph Hoerl & Patrick Burns (2009). Cue Competition Effects and Young Children's Causal and Counterfactual Inferences. Developmental Psychology 45 (6):1563-1575.score: 51.0
    The authors examined cue competition effects in young children using the blicket detector paradigm, in which objects are placed either singly or in pairs on a novel machine and children must judge which objects have the causal power to make the machine work. Cue competition effects were found in a 5- to 6-year-old group but not in a 4-year-old group. Equivalent levels of forward and backward blocking were found in the former group. Children's counterfactual judgments were subsequently examined by (...)
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  13. Sarah R. Beck, Daniel P. Weisberg, Patrick Burns & Kevin J. Riggs (2013). Conditional Reasoning and Emotional Experience: A Review of the Development of Counterfactual Thinking. [REVIEW] Studia Logica:1-17.score: 50.0
    What do human beings use conditional reasoning for? A psychological consequence of counterfactual conditional reasoning is emotional experience, in particular, regret and relief. Adults’ thoughts about what might have been influence their evaluations of reality. We discuss recent psychological experiments that chart the relationship between children’s ability to engage in conditional reasoning and their experience of counterfactual emotions. Relative to conditional reasoning, counterfactual emotions are late developing. This suggests that children need not only (...)
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  14. Deena S. Weisberg & Alison Gopnik (2013). Pretense, Counterfactuals, and Bayesian Causal Models: Why What Is Not Real Really Matters. Cognitive Science 37 (7):1368-1381.score: 48.0
    Young children spend a large portion of their time pretending about non-real situations. Why? We answer this question by using the framework of Bayesian causal models to argue that pretending and counterfactual reasoning engage the same component cognitive abilities: disengaging with current reality, making inferences about an alternative representation of reality, and keeping this representation separate from reality. In turn, according to causal models accounts, counterfactual reasoning is a crucial tool that children need to plan for (...)
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  15. Malcolm R. Forster (1986). Counterfactual Reasoning in the Bell-Epr Paradox. Philosophy of Science 53 (1):133-144.score: 48.0
    Skyrms's formulation of the argument against stochastic hidden variables in quantum mechanics using conditionals with chance consequences suffers from an ambiguity in its "conservation" assumption. The strong version, which Skyrms needs, packs in a "no-rapport" assumption in addition to the weaker statement of the "experimental facts." On the positive side, I argue that Skyrms's proof has two unnoted virtues (not shared by previous proofs): (1) it shows that certain difficulties that arise for deterministic hidden variable theories that exploit a nonclassical (...)
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  16. James Woodward (2011). Psychological Studies of Causal and Counterfactual Reasoning. In Christoph Hoerl, Teresa McCormack & Sarah R. Beck (eds.), Understanding Counterfactuals, Understanding Causation. Oxford University Press. 16.score: 46.0
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  17. Robert Stalnaker (1996). Knowledge, Belief and Counterfactual Reasoning in Games. Economics and Philosophy 12 (02):133-.score: 45.0
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  18. Karolina Krzyżanowska (2013). Belief Ascription and the Ramsey Test. Synthese 190 (1):21-36.score: 45.0
    In this paper, I analyse a finding by Riggs and colleagues that there is a close connection between people’s ability to reason with counterfactual conditionals and their capacity to attribute false beliefs to others. The result indicates that both processes may be governed by one cognitive mechanism, though false belief attribution seems to be slightly more cognitively demanding. Given that the common denominator for both processes is suggested to be a form of the Ramsey test, I investigate whether Stalnaker’s (...)
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  19. Tim De Mey (2005). Remodeling the Past. Foundations of Science 10 (1):47-66.score: 45.0
    In some of the papers in which she develops and defends the mental modelview of thought experiments in physics, Nersessian expresses the belief that her account has implications for thought experiments in other domains as well. In this paper, I argue, firstly, that counterfactual reasoning has a legitimate place in historical inquiry, and secondly, that the mental model view can account for such "alternative histories". I proceed as follows. Firstly, I review the main accounts of thought experiments in (...)
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  20. Linton Wang & Wei-Fen Ma (2014). Comparative Syllogism and Counterfactual Knowledge. Synthese 191 (6):1327-1348.score: 45.0
    Comparative syllogism is a type of scientific reasoning widely used, explicitly or implicitly, for inferences from observations to conclusions about effectiveness, but its philosophical significance has not been fully elaborated or appreciated. In its simplest form, the comparative syllogism derives a conclusion about the effectiveness of a factor (e.g. a treatment or an exposure) on a certain property via an experiment design using a test (experimental) group and a comparison (control) group. Our objective is to show that the comparative (...)
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  21. Abner Shimony & Howard Stein (2003). On Quantum Non-Locality, Special Relativity, and Counterfactual Reasoning. In. In A. Ashtekar (ed.), Revisiting the Foundations of Relativistic Physics. 499--521.score: 45.0
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  22. Cristina Bicchieri, Richard Jeffrey & Brian Skyrms (1999). Knowledge, Belief, and Counterfactual Reasoning in Games. In Cristina Bicchieri, Richard C. Jeffrey & Brian Skyrms (eds.), The Logic of Strategy. Oxford University Press.score: 45.0
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  23. Ruth Mj Byrne & Alessandra Tasso (1994). Counterfactual Reasoning: Inferences From Hypothetical Conditionals. In Ashwin Ram & Kurt Eiselt (eds.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society. Erlbaum.score: 45.0
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  24. Roberta Ferrario (2001). Counterfactual Reasoning. In. In P. Bouquet V. Akman (ed.), Modeling and Using Context. Springer. 170--183.score: 45.0
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  25. Eva Rafetseder & Josef Perner (2012). When the Alternative Would Have Been Better: Counterfactual Reasoning and the Emergence of Regret. Cognition and Emotion 26 (5):800-819.score: 45.0
  26. Jiji Zhang (2013). A Lewisian Logic of Causal Counterfactuals. Minds and Machines 23 (1):77-93.score: 42.0
    In the artificial intelligence literature a promising approach to counterfactual reasoning is to interpret counterfactual conditionals based on causal models. Different logics of such causal counterfactuals have been developed with respect to different classes of causal models. In this paper I characterize the class of causal models that are Lewisian in the sense that they validate the principles in Lewis’s well-known logic of counterfactuals. I then develop a system sound and complete with respect to this class. The (...)
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  27. A. Spellman Barbara, P. Kincannon Alexandra & J. Stose Stephen (2005). The Relation Between Counterfactual and Causal Reasoning. In David R. Mandel, Denis J. Hilton & Patrizia Catellani (eds.), The Psychology of Counterfactual Thinking. Routledge.score: 39.0
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  28. Barbara A. Spellman, Alexandra P. Kincannon & Stephen J. Stose (2005). The Relation Between Counterfactual and Causal Reasoning. In David R. Mandel, Denis J. Hilton & Patrizia Catellani (eds.), The Psychology of Counterfactual Thinking. Routledge. 28--43.score: 39.0
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  29. J. Perner & E. Rafetseder (2011). Counterfactual and Other Forms of Conditional Reasoning: Children Lost in the Nearest Possible World. In Christoph Hoerl, Teresa McCormack & Sarah R. Beck (eds.), Understanding Counterfactuals, Understanding Causation. Oxford University Press.score: 37.0
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  30. Barbara A. Spellman & Dieynaba G. Ndiaye (2007). On the Relation Between Counterfactual and Causal Reasoning. Behavioral and Brain Sciences 30 (5-6):466-467.score: 37.0
    We critique the distinction Byrne makes between strong causes and enabling conditions, and its implications, on both theoretical and empirical grounds. First, we believe that the difference is psychological, not logical. Second, we disagree that there is a strict Third, we disagree that it is easier for people to generate causes than counterfactuals.
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  31. Paul L. Harris, Tim German & Patrick Mills (1996). Children's Use of Counterfactual Thinking in Causal Reasoning. Cognition 61 (3):233-259.score: 36.0
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  32. David R. Mandel (2003). Judgment Dissociation Theory: An Analysis of Differences in Causal, Counterfactual and Covariational Reasoning. Journal of Experimental Psychology: General 132 (3):419.score: 36.0
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  33. Caren A. Frosch, Teresa McCormack, David A. Lagnado & Patrick Burns (2012). Are Causal Structure and Intervention Judgments Inextricably Linked? A Developmental Study. Cognitive Science 36 (2):261-285.score: 33.0
    The application of the formal framework of causal Bayesian Networks to children’s causal learning provides the motivation to examine the link between judgments about the causal structure of a system, and the ability to make inferences about interventions on components of the system. Three experiments examined whether children are able to make correct inferences about interventions on different causal structures. The first two experiments examined whether children’s causal structure and intervention judgments were consistent with one another. In Experiment 1, children (...)
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  34. Bence Nanay (2010). Neither Moralists, nor Scientists: We Are Counterfactually Reasoning Animals. Behavioral and Brain Sciences 33 (4):347-348.score: 33.0
    We are neither scientists nor moralists. Our mental capacities (such as attributing intentionality) are neither akin to the scientist's exact reasoning, nor are they (Knobe's target article, sect. 2.2, last para.). They are more similar to all those simple capacities that humans and animals are equally capable of, but with enhanced sensitivity to counterfactual situations: of what could have been.
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  35. Bence Nanay (2010). Neither Scientists, nor Moralists: We Are Counterfactually Reasoning Animals. Behavioral and Brain Sciences.score: 33.0
    We are neither scientists nor moralists. Our mental capacities (like attributing intentionality) are neither akin to the scientist’s exact reasoning, nor are they “suffused through and through with moral considerations”. They are more similar to all those simple capacities that humans and animals are equally capable of, but with enhanced sensitivity to counterfactual situations: of what could have been.
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  36. Gabriele Contessa (2006). On the Supposed Temporal Asymmetry of Counterfactual Dependence; Or: It Wouldn't Have Taken a Miracle! Dialectica 60 (4):461–473.score: 30.0
    The thesis that a temporal asymmetry of counterfactual dependence characterizes our world plays a central role in Lewis’s philosophy, as. among other things, it underpins one of Lewis most renowned theses—that causation can be analyzed in terms of counterfactual dependence. To maintain that a temporal asymmetry of counterfactual dependence characterizes our world, Lewis committed himself to two other theses. The first is that the closest possible worlds at which the antecedent of a counterfactual conditional is true (...)
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  37. Judea Pearl (2013). Structural Counterfactuals: A Brief Introduction. Cognitive Science 37 (6):977-985.score: 30.0
    Recent advances in causal reasoning have given rise to a computational model that emulates the process by which humans generate, evaluate, and distinguish counterfactual sentences. Contrasted with the “possible worlds” account of counterfactuals, this “structural” model enjoys the advantages of representational economy, algorithmic simplicity, and conceptual clarity. This introduction traces the emergence of the structural model and gives a panoramic view of several applications where counterfactual reasoning has benefited problem areas in the empirical sciences.
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  38. Roger Stanev (2012). Modelling and Simulating Early Stopping of RCTs: A Case Study of Early Stop Due to Harm. Journal of Experimental and Theoretical Artificial Intelligence 24 (4):513-526.score: 30.0
    Despite efforts from regulatory agencies (e.g. NIH, FDA), recent systematic reviews of randomised controlled trials (RCTs) show that top medical journals continue to publish trials without requiring authors to report details for readers to evaluate early stopping decisions carefully. This article presents a systematic way of modelling and simulating interim monitoring decisions of RCTs. By taking an approach that is both general and rigorous, the proposed framework models and evaluates early stopping decisions of RCTs based on a clear and consistent (...)
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  39. Bruce Christianson (2013). Living in an Impossible World: Real-Izing the Consequences of Intransitive Trust. [REVIEW] Philosophy and Technology 26 (4):411-429.score: 30.0
    Many accounts of online trust are based upon mechanisms for building reputation. Trust is portrayed as desirable, and handing off trust is easier if trust is modelled to be transitive. But in the analysis of cyber-security protocols, trust is usually used as a substitute for certain knowledge: it follows that if there is no residual risk, then there is no need for trust. On this grimmer understanding, the less that users are required to trust, the better. Involuntary transitivity of trust (...)
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  40. Jonathan Eric Adler & Lance J. Rips (eds.) (2008). Reasoning: Studies of Human Inference and its Foundations. Cambridge University Press.score: 27.0
    This interdisciplinary work is a collection of major essays on reasoning: deductive, inductive, abductive, belief revision, defeasible (non-monotonic), cross cultural, conversational, and argumentative. They are each oriented toward contemporary empirical studies. The book focuses on foundational issues, including paradoxes, fallacies, and debates about the nature of rationality, the traditional modes of reasoning, as well as counterfactual and causal reasoning. It also includes chapters on the interface between reasoning and other forms of thought. In general, this (...)
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  41. Christoph Hoerl, Teresa McCormack & Sarah R. Beck (eds.) (2011). Understanding Counterfactuals, Understanding Causation. Oxford University Press.score: 27.0
    How are causal judgements such as 'The ice on the road caused the traffic accident' connected with counterfactual judgements such as 'If there had not been any ice on the road, the traffic accident would not have happened'? This volume throws new light on this question by uniting, for the first time, psychological and philosophical approaches to causation and counterfactuals. Traditionally, philosophers have primarily been interested in connections between causal and counterfactual claims on the level of meaning or (...)
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  42. Matthias Unterhuber & Gerhard Schurz (forthcoming). Logic and Probability: Reasoning in Uncertain Environments – Introduction to the Special Issue. Studia Logica:1-9.score: 26.0
    The current special issue focuses on logical and probabilistic approaches to reasoning in uncertain environments, both from a formal, conceptual and argumentative perspective as well as an empirical point of view. In the present introduction we give an overview of the types of problems addressed by the individual contributions of the special issue, based on fundamental distinctions employed in this area. We furthermore describe some of the general features of the special issue.
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  43. Jonathan Waskan (2011). Mechanistic Explanation at the Limit. Synthese 183 (3):389-408.score: 24.0
    Resurgent interest in both mechanistic and counterfactual theories of explanation has led to a fair amount of discussion regarding the relative merits of these two approaches. James Woodward is currently the pre-eminent counterfactual theorist, and he criticizes the mechanists on the following grounds: Unless mechanists about explanation invoke counterfactuals, they cannot make sense of claims about causal interactions between mechanism parts or of causal explanations put forward absent knowledge of productive mechanisms. He claims that these shortfalls can be (...)
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  44. W. M. De Muynck, W. De Baere & H. Martens (1994). Interpretations of Quantum Mechanics, Joint Measurement of Incompatible Observables, and Counterfactual Definiteness. Foundations of Physics 24 (12):1589-1664.score: 24.0
    The validity of the conclusion to the nonlocality of quantum mechanics, accepted widely today as the only reasonable solution to the EPR and Bell issues, is questioned and criticized. Arguments are presented which remove the compelling character of this conclusion and make clear that it is not the most obvious solution. Alternative solutions are developed which are free of the contradictions related with the nonlocality conclusion. Firstly, the dependence on the adopted interpretation is shown, with the conclusion that the alleged (...)
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  45. John Best (2005). Recognition of Proofs in Conditional Reasoning. Thinking and Reasoning 11 (4):326 – 348.score: 24.0
    Relatively little is known about those who consistently produce the valid response to Modus Tollens (MT) problems. In two studies, people who responded correctly to MT problems indicated how “convinced” they were by proofs of conditional reasoning conclusions. The first experiment showed that MT competent reasoners found accurate proofs of MT reasoning more convincing than similar “proofs” of invalid reasoning. Similarly, there was a tendency for MT competent reasoners to find an initial counterfactual supposition more convincing (...)
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  46. Lance J. Rips (2010). Two Causal Theories of Counterfactual Conditionals. Cognitive Science 34 (2):175-221.score: 24.0
    Bayes nets are formal representations of causal systems that many psychologists have claimed as plausible mental representations. One purported advantage of Bayes nets is that they may provide a theory of counterfactual conditionals, such as If Calvin had been at the party, Miriam would have left early. This article compares two proposed Bayes net theories as models of people's understanding of counterfactuals. Experiments 1-3 show that neither theory makes correct predictions about backtracking counterfactuals (in which the event of the (...)
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  47. Jens Andreas Terum & Frode Svartdal (2012). Judgements Vs Affective Evaluations of Counterfactual Outcomes. Thinking and Reasoning 19 (1):78 - 95.score: 24.0
    (2013). Judgements vs affective evaluations of counterfactual outcomes. Thinking & Reasoning: Vol. 19, No. 1, pp. 78-95. doi: 10.1080/13546783.2012.739098.
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  48. David R. Mandel, Denis J. Hilton & Patrizia Catellani (eds.) (2005). The Psychology of Counterfactual Thinking. Routledge.score: 23.0
    It is human nature to wonder how things might have turned out differently--either for the better or for the worse. For the past two decades psychologists have been intrigued by this phenomenon, which they call counterfactual thinking. Specifically, researchers have sought to answer the "big" questions: Why do people have such a strong propensity to generate counterfactuals, and what functions does counterfactual thinking serve? What are the determinants of counterfactual thinking, and what are its adaptive and psychological (...)
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  49. Matthias Unterhuber (2013). Possible Worlds Semantics for Indicative and Counterfactual Conditionals? A Formal Philosophical Inquiry Into Chellas-Segerberg Semantics. Ontos (now De Gruyter).score: 23.0
    Conditional structures lie at the heart of the sciences, humanities, and everyday reasoning. It is hence not surprising that conditional logics – logics specifically designed to account for natural language conditionals – are an active and interdisciplinary area. The present book gives a formal and a philosophical account of indicative and counterfactual conditionals in terms of Chellas-Segerberg semantics. For that purpose a range of topics are discussed such as Bennett’s arguments against truth value based semantics for indicative conditionals.
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  50. Ilya Shpitser (2013). Counterfactual Graphical Models for Longitudinal Mediation Analysis With Unobserved Confounding. Cognitive Science 37 (6):1011-1035.score: 23.0
    Questions concerning mediated causal effects are of great interest in psychology, cognitive science, medicine, social science, public health, and many other disciplines. For instance, about 60% of recent papers published in leading journals in social psychology contain at least one mediation test (Rucker, Preacher, Tormala, & Petty, 2011). Standard parametric approaches to mediation analysis employ regression models, and either the “difference method” (Judd & Kenny, 1981), more common in epidemiology, or the “product method” (Baron & Kenny, 1986), more common in (...)
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