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  1. added 2019-01-09
    The Proportionality of Common Sense Causal Claims.Jennifer McDonald - unknown
    This paper defends strong proportionality against what I take to be its principal objection – that proportionality fails to preserve common sense causal intuitions – by articulating independently plausible constraints on how to represent causal situations. I first assume an interventionist formulation of proportionality, following Woodward. This views proportionality as a relational constraint on variable selection in causal modeling that requires that changes in the cause variable line up with those in the effect variable. I then argue that the principal (...)
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  2. added 2019-01-09
    Making a Difference: Essays on the Philosophy of Causation.Helen Beebee, Christopher Hitchcock & Huw Price - 2017 - Oxford: Oxford University Press.
    Making a Difference presents fifteen original essays on causation and counterfactuals by an international team of experts. Collectively, they represent the state of the art on these topics. The essays in this volume are inspired by the life and work of Peter Menzies, who made a difference in the lives of students, colleagues, and friends. Topics covered include: the semantics of counterfactuals, agency theories of causation, the context-sensitivity of causal claims, structural equation models, mechanisms, mental causation, causal exclusion argument, free (...)
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  3. added 2018-11-30
    Evidence or Prejudice? A Reply to Matlock. [REVIEW]Keith Augustine - 2016 - Journal of Parapsychology 80:203-231.
    Before I respond to James G. Matlock’s comments on my coedited volume, The Myth of an Afterlife: The Case against Life After Death (MoA), I would like to thank him for taking the time to review such a large volume—and review it conscientiously—even if we ultimately disagree about its import. I would also like to extend my thanks to Journal of Parapsychology editor John Palmer for inviting this response, as it gives me an opportunity to clarify why many secondary issues (...)
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  4. added 2018-11-13
    Temporally Asymmetric Inference in a Markov Process.Elliott Sober - 1991 - Philosophy of Science 58 (3):398-410.
    A model of a Markov process is presented in which observing the present state of a system is asymmetrically related to inferring the system's future and inferring its past. A likelihood inference about the system's past state, based on observing its present state, is justified no matter what the parameter values in the model happen to be. In contrast, a probability inference of the system's future state, based on observing its present state, requires further information about the parameter values.
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  5. added 2018-05-30
    Newton's Regulae Philosophandi.Zvi Biener - 2018 - In Chris Smeenk & Eric Schliesser (eds.), Oxford Handbook of Isaac Newton. Oxford University Press.
    Newton’s Regulae philosophandi—the rules for reasoning in natural philosophy—are maxims of causal reasoning and induction. This essay reviews their significance for Newton’s method of inquiry, as well as their application to particular propositions within the Principia. Two main claims emerge. First, the rules are not only interrelated, they defend various facets of the same core idea: that nature is simple and orderly by divine decree, and that, consequently, human beings can be justified in inferring universal causes from limited phenomena, if (...)
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  6. added 2018-05-29
    Social Cognition as Causal Inference: Implications for Common Knowledge and Autism.Jakob Hohwy & Colin Palmer - forthcoming - In John Michael & Mattia Gallotti (eds.), Social Objects and Social Cognition. Springer.
    This chapter explores the idea that the need to establish common knowledge is one feature that makes social cognition stand apart in important ways from cognition in general. We develop this idea on the background of the claim that social cognition is nothing but a type of causal inference. We focus on autism as our test-case, and propose that a specific type of problem with common knowledge processing is implicated in challenges to social cognition in autism spectrum disorder (ASD). This (...)
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  7. added 2018-05-29
    Epistemology of Causal Inference in Pharmacology.Jürgen Landes, Barbara Osimani & Roland Poellinger - 2018 - European Journal for Philosophy of Science 8 (1):3-49.
    Philosophical discussions on causal inference in medicine are stuck in dyadic camps, each defending one kind of evidence or method rather than another as best support for causal hypotheses. Whereas Evidence Based Medicine advocates the use of Randomised Controlled Trials and systematic reviews of RCTs as gold standard, philosophers of science emphasise the importance of mechanisms and their distinctive informational contribution to causal inference and assessment. Some have suggested the adoption of a pluralistic approach to causal inference, and an inductive (...)
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  8. added 2018-05-29
    The Higgs Discovery as a Diagnostic Causal Inference.Adrian Wüthrich - 2017 - Synthese 194 (2).
    I reconstruct the discovery of the Higgs boson by the ATLAS collaboration at CERN as the application of a series of inferences from effects to causes. I show to what extent such diagnostic causal inferences can be based on well established knowledge gained in previous experiments. To this extent, causal reasoning can be used to infer the existence of entities, rather than just causal relationships between them. The resulting account relies on the principle of causality, attributes only a heuristic role (...)
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  9. added 2018-05-29
    SAT-Based Causal Discovery Under Weaker Assumptions. Zhalama, Jiji Zhang, Frederick Eberhardt & Wolfgang Mayer - 2017 - In Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI). Association for Uncertainty in Artificial Intelligence (AUAI).
    Using the flexibility of recently developed methods for causal discovery based on Boolean satisfiability solvers, we encode a variety of assumptions that weaken the Faithfulness assumption. The encoding results in a number of SAT-based algorithms whose asymptotic correctness relies on weaker conditions than are standardly assumed. This implementation of a whole set of assumptions in the same platform enables us to systematically explore the effect of weakening the Faithfulness assumption on causal discovery. An important effect, suggested by simulation results, is (...)
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  10. added 2018-05-29
    On the Intersection Property of Conditional Independence and its Application to Causal Discovery.Jonas Peters - 2015 - Journal of Causal Inference 3 (1).
    This work investigates the intersection property of conditional independence. It states that for random variables A,B,C and X we have that X⊥⊥A|B,C and X⊥⊥B|A,C implies X⊥⊥(A,B)|C. Here, “⊥⊥” stands for statistical independence. Under the assumption that the joint distribution has a density that is continuous in A,B and C, we provide necessary and sufficient conditions under which the intersection property holds. The result has direct applications to causal inference: it leads to strictly weaker conditions under which the graphical structure becomes (...)
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  11. added 2018-05-29
    The Limits of Piecemeal Causal Inference.Conor Mayo-Wilson - 2014 - British Journal for the Philosophy of Science 65 (2):213-249.
    In medicine and the social sciences, researchers must frequently integrate the findings of many observational studies, which measure overlapping collections of variables. For instance, learning how to prevent obesity requires combining studies that investigate obesity and diet with others that investigate obesity and exercise. Recently developed causal discovery algorithms provide techniques for integrating many studies, but little is known about what can be learned from such algorithms. This article argues that there are causal facts that one could learn by conducting (...)
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  12. added 2018-05-29
    Causal Discovery and MIMIC Models.Alexander Murray-Watters - 2013 - Dissertation,
    This thesis presents an alternative method for the detection of MIMIC models. Previous methods (such as factor analysis) suffer from a number of significant aws and limitations, which the new method (a causal search algorithm) doesn't suffer. A new algorithm is introduced, followed by a worked-through example of its application. Discussion focuses on some of the limiting assumptions the algorithm currently requires. Finally, recommendations for future work address improvements of the algorithm, as well as its applicability.
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  13. added 2018-05-29
    Identifying Intervention Variables.Michael Baumgartner & Isabelle Drouet - 2013 - European Journal for Philosophy of Science 3 (2):183-205.
    The essential precondition of implementing interventionist techniques of causal reasoning is that particular variables are identified as so-called intervention variables. While the pertinent literature standardly brackets the question how this can be accomplished in concrete contexts of causal discovery, the first part of this paper shows that the interventionist nature of variables cannot, in principle, be established based only on an interventionist notion of causation. The second part then demonstrates that standard observational methods that draw on Bayesian networks identify intervention (...)
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  14. added 2018-05-29
    Causal Inference, Mechanisms, and the Semmelweis Case.Raphael Scholl - 2013 - Studies in History and Philosophy of Science Part A 44 (1):66-76.
    Semmelweis’s discovery of the cause of puerperal fever around the middle of the 19th century counts among the paradigm cases of scientific discovery. For several decades, philosophers of science have used the episode to illustrate, appraise and compare views of proper scientific methodology.Here I argue that the episode can be profitably reexamined in light of two cognate notions: causal reasoning and mechanisms. Semmelweis used several causal reasoning strategies both to support his own and to reject competing hypotheses. However, these strategies (...)
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  15. added 2018-05-29
    From Colliding Billiard Balls to Colluding Desperate Housewives: Causal Bayes Nets as Rational Models of Everyday Causal Reasoning.York Hagmayer & Magda Osman - 2012 - Synthese 189 (S1):17-28.
    Many of our decisions pertain to causal systems. Nevertheless, only recently has it been claimed that people use causal models when making judgments, decisions and predictions, and that causal Bayes nets allow us to formally describe these inferences. Experimental research has been limited to simple, artificial problems, which are unrepresentative of the complex dynamic systems we successfully deal with in everyday life. For instance, in social interactions, we can explain the actions of other's on the fly and we can generalize (...)
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  16. added 2018-05-29
    The Ways of the Wise: Hume's Rules of Causal Reasoning.Deborah Boyle - 2012 - Hume Studies 38 (2):157-182.
    In Hume’s own day, and for nearly two hundred years after that, readers interested in his account of causal reasoning tended to focus on the skeptical implications of that account. For example, in his 1757 View of the Principal Deistical Writers of the Last and Present Century, John Leland characterized Hume as “endeavouring to destroy all reasoning, from causes to effects, or from effects to causes.”1 According to this sort of reading, as Louis Loeb describes it, “there is equal justification (...)
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  17. added 2018-05-29
    Intervention, Causal Reasoning, and the Neurobiology of Mental Disorders: Pharmacological Drugs as Experimental Instruments.Jonathan Y. Tsou - 2012 - Studies in History and Philosophy of Science Part C 43 (2):542-551.
    In psychiatry, pharmacological drugs play an important experimental role in attempts to identify the neurobiological causes of mental disorders. Besides being developed in applied contexts as potential treatments for patients with mental disorders, pharmacological drugs play a crucial role in research contexts as experimental instruments that facilitate the formulation and revision of neurobiological theories of psychopathology. This paper examines the various epistemic functions that pharmacological drugs serve in the discovery, refinement, testing, and elaboration of neurobiological theories of mental disorders. I (...)
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  18. added 2018-05-29
    Inferring Hidden Causal Structure.Tamar Kushnir, Alison Gopnik, Chris Lucas & Laura Schulz - 2010 - Cognitive Science 34 (1):148-160.
    We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a pattern of associations and interventions on a novel causal system. Given minimal training and no feedback, participants in Experiment 1 used causal graph notation to spontaneously draw structures containing one observed cause, one unobserved common cause, and two unobserved independent causes, depending on the pattern of associations and interventions they saw. (...)
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  19. added 2018-05-29
    Causal Discovery and the Problem of Ignorance. An Adaptive Logic Approach.Bert Leuridan - 2009 - Journal of Applied Logic 7 (2):188-205.
    In this paper, I want to substantiate three related claims regarding causal discovery from non-experimental data. Firstly, in scientific practice, the problem of ignorance is ubiquitous, persistent, and far-reaching. Intuitively, the problem of ignorance bears upon the following situation. A set of random variables V is studied but only partly tested for (conditional) independencies; i.e. for some variables A and B it is not known whether they are (conditionally) independent. Secondly, Judea Pearl’s most meritorious and influential algorithm for causal discovery (...)
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  20. added 2018-05-29
    Causal Reasoning with Ancestral Graphical Models.Jiji Zhang - 2008 - Journal of Machine Learning Research 9:1437-1474.
    Causal reasoning is primarily concerned with what would happen to a system under external interventions. In particular, we are often interested in predicting the probability distribution of some random variables that would result if some other variables were forced to take certain values. One prominent approach to tackling this problem is based on causal Bayesian networks, using directed acyclic graphs as causal diagrams to relate post-intervention probabilities to pre-intervention probabilities that are estimable from observational data. However, such causal diagrams are (...)
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  21. added 2018-05-29
    Interventions and Causal Inference.Frederick Eberhardt & Richard Scheines - 2007 - Philosophy of Science 74 (5):981-995.
    The literature on causal discovery has focused on interventions that involve randomly assigning values to a single variable. But such a randomized intervention is not the only possibility, nor is it always optimal. In some cases it is impossible or it would be unethical to perform such an intervention. We provide an account of ‘hard' and ‘soft' interventions and discuss what they can contribute to causal discovery. We also describe how the choice of the optimal intervention(s) depends heavily on the (...)
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  22. added 2018-05-29
    Causal Inference in Quantum Mechanics: A Reassessment.Mauricio Suárez - 2007 - In Federica Russo & Jon Williamson (eds.), Causality and Probability in the Sciences. College Publications. pp. 65-106.
    There has been an intense discussion, albeit largely an implicit one, concerning the inference of causal hypotheses from statistical correlations in quantum mechanics ever since John Bell’s first statement of his notorious theorem in 1966. As is well known, its focus has mainly been the so-called Einstein-Podolsky-Rosen (“EPR”) thought experiment, and the ensuing observed correlations in real EPR like experiments. But although implicitly the discussion goes as far back as Bell’s work, it is only in the last two decades that (...)
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  23. added 2018-05-29
    Adjacency-Faithfulness and Conservative Causal Inference.Joseph Ramsey, Jiji Zhang & Peter Spirtes - 2006 - In R. Dechter & T. Richardson (eds.), Proceedings of the Twenty-Second Conference Conference on Uncertainty in Artificial Intelligence (2006). Arlington, Virginia: AUAI Press. pp. 401-408.
    Most causal discovery algorithms in the literature exploit an assumption usually referred to as the Causal Faithfulness or Stability Condition. In this paper, we highlight two components of the condition used in constraint-based algorithms, which we call “Adjacency-Faithfulness” and “Orientation- Faithfulness.” We point out that assuming Adjacency-Faithfulness is true, it is possible to test the validity of Orientation- Faithfulness. Motivated by this observation, we explore the consequence of making only the Adjacency-Faithfulness assumption. We show that the familiar PC algorithm has (...)
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  24. added 2018-05-29
    Social Mechanisms and Causal Inference.Daniel Steel - 2004 - Philosophy of the Social Sciences 34 (1):55-78.
    Several authors have claimed that mechanisms play a vital role in distinguishing between causation and mere correlation in the social sciences. Such claims are sometimes interpreted to mean that without mechanisms, causal inference in social science is impossible. The author agrees with critics of this proposition but explains how the account of how mechanisms aid causal inference can be interpreted in a way that does not depend on it. Nevertheless, he shows that this more charitable version of the account is (...)
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  25. added 2018-05-29
    Introducing Transcranial Magnetic Stimulation (TMS) and its Property of Causal Inference in Investigating Brain-Function Relationships.D. Schutter, J. van Honk & Jaak Panksepp - 2004 - Synthese 141 (2):155-73.
    Transcranial magnetic stimulation (TMS) is a method capable of transiently modulating neural excitability. Depending on the stimulation parameters information processing in the brain can be either enhanced or disrupted. This way the contribution of different brain areas involved in mental processes can be studied, allowing a functional decomposition of cognitive behavior both in the temporal and spatial domain, hence providing a functional resolution of brain/mind processes. The aim of the present paper is to argue that TMS with its ability to (...)
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  26. added 2018-05-29
    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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  27. added 2018-05-29
    Expertise and Mixture in Automatic Causal Discovery.Joseph Daniel Ramsey - 2001 - Dissertation, University of California, San Diego
    Critics of automatic causal discovery have claimed that Tetrad-style algorithms are inferior to domain experts at discovering causal structure from real scientific data and especially poor when applied to data that is highly mixed, either in a physical sense or in a mixtures of records sense. We compare a domain expert in geological spectroscopy head-to-head with a variety of machine algorithms on the task of predicting mineral class composition from visual to near infrared reflectance spectra. A simplified Tetrad algorithm outperforms (...)
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  28. added 2018-05-27
    Alexander Gebharter: Causal Nets, Interventionism, and Mechanisms. Philosophical Foundations and Applications.Lorenzo Casini - 2018 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 49 (3):481-485.
  29. added 2018-05-15
    Path-Specific Effects.Naftali Weinberger - forthcoming - British Journal for the Philosophy of Science.
    A cause may influence its effect via multiple paths. Paradigmatically (Hesslow [1974]), taking birth control pills both decreases one’s risk of thrombosis by preventing pregnancy and increases it by producing a blood chemical. Building on Pearl ([2001]), I explicate the notion of a path-specific effect. Roughly, a path-specific effect of C on E via path P is the degree to which a change in C would change E were they to be transmitted only via P. Facts about such effects may (...)
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  30. added 2018-05-15
    The Frugal Inference of Causal Relations.Malcolm Forster, Garvesh Raskutti, Reuben Stern & Naftali Weinberger - 2018 - British Journal for the Philosophy of Science 69 (3):821-848.
    Recent approaches to causal modelling rely upon the causal Markov condition, which specifies which probability distributions are compatible with a directed acyclic graph. Further principles are required in order to choose among the large number of DAGs compatible with a given probability distribution. Here we present a principle that we call frugality. This principle tells one to choose the DAG with the fewest causal arrows. We argue that frugality has several desirable properties compared to the other principles that have been (...)
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  31. added 2018-05-15
    Folk Intuitions of Actual Causation: A Two-Pronged Debunking Explanation.David Rose - 2017 - Philosophical Studies 174 (5):1323-1361.
    How do we determine whether some candidate causal factor is an actual cause of some particular outcome? Many philosophers have wanted a view of actual causation which fits with folk intuitions of actual causation and those who wish to depart from folk intuitions of actual causation are often charged with the task of providing a plausible account of just how and where the folk have gone wrong. In this paper, I provide a range of empirical evidence aimed at showing just (...)
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  32. added 2018-05-15
    Moral Psychology, 3 Vols.Walter Sinnott-Armstrong (ed.) - 2008 - MIT Press.
    For much of the twentieth century, philosophy and science went their separate ways. In moral philosophy, fear of the so-called naturalistic fallacy kept moral philosophers from incorporating developments in biology and psychology. Since the 1990s, however, many philosophers have drawn on recent advances in cognitive psychology, brain science, and evolutionary psychology to inform their work. This collaborative trend is especially strong in moral philosophy, and these three volumes bring together some of the most innovative work by both philosophers and psychologists (...)
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  33. added 2018-05-15
    A Theory of Physical Probability.Richard Alexander Johns - 1999 - Dissertation, The University of British Columbia (Canada)
    It is now common to hold that causes do not always determine their effects, and indeed theories of "probabilistic causation" abound. The basic idea of these theories is that C causes E just in case C and E both occur, and the chance of E would have been lower than it is had C not occurred. The problems with these accounts are that the notion of chance remains primitive, and this account of causation does not coincide with the intuitive notion (...)
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  34. added 2018-05-04
    Category Structure Affects the Developmental Trajectory of Children's Inductive Inferences for Both Natural Kinds and Artefacts.Julia R. Badger & Laura R. Shapiro - 2015 - Thinking and Reasoning 21 (2):206-229.
    Inductive reasoning is fundamental to human cognition, yet it remains unclear how we develop this ability and what might influence our inductive choices. We created novel categories in which crucial factors such as domain and category structure were manipulated orthogonally. We trained 403 4–9-year-old children to categorise well-matched natural kind and artefact stimuli with either featural or relational category structure, followed by induction tasks. This wide age range allowed for the first full exploration of the developmental trajectory of inductive reasoning (...)
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  35. added 2018-05-04
    The Dualist’s Dilemma: The High Cost of Reconciling Neuroscience with a Soul.Keith Augustine & Yonatan I. Fishman - 2015 - In Keith Augustine & Michael Martin (eds.), The Myth of an Afterlife: The Case against Life After Death. Rowman & Littlefield. pp. 203-292.
    Tight correlations between mental states and brain states have been observed time and again within the ethology of biologically ingrained animal behaviors, the comparative psychology of animal minds, the evolutionary psychology of mental adaptations, the behavioral genetics of inherited mental traits, the developmental psychology of the maturing mind, the psychopharmacology of mind-altering substances, and cognitive neuroscience more generally. They imply that our mental lives are only made possible because of brain activity—that having a functioning brain is a necessary condition for (...)
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  36. added 2018-05-04
    OAE: The Ontology of Adverse Events.Yongqun He, Sirarat Sarntivijai, Yu Lin, Zuoshuang Xiang, Abra Guo, Shelley Zhang, Desikan Jagannathan, Luca Toldo, Cui Tao & Barry Smith - 2014 - Journal of Biomedical Semantics 5 (29):1-13.
    A medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health. Description: The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data (...)
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  37. added 2018-05-04
    Childrens Inferences About Ambiguous Events-the Effects of Foregrounding and Multiple Clues.Ma Casteel - 1992 - Bulletin of the Psychonomic Society 30 (6):477-477.
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  38. added 2018-04-26
    Causality From Probability.Peter Spirtes, Clark Glymour & Richard Scheines - unknown
    Data analysis that merely fits an empirical covariance matrix or that finds the best least squares linear estimator of a variable is not of itself a reliable guide to judgements about policy, which inevitably involve causal conclusions. The policy implications of empirical data can be completely reversed by alternative hypotheses about the causal relations of variables, and the estimates of a particular causal influence can be radically altered by changes in the assumptions made about other dependencies.2 For these reasons, one (...)
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  39. added 2018-04-26
    Causality and Causal Modelling in the Social Sciences.Federica Russo - unknown
    The anti-causal prophecies of last century have been disproved. Causality is neither a ‘relic of a bygone’ nor ‘another fetish of modern science’; it still occupies a large part of the current debate in philosophy and the sciences. This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant (...)
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  40. added 2018-04-26
    The Development of Counterfactual Reasoning About Doubly-Determined Events.Teresa McCormack, Maggie Ho, Charlene Gribben, Eimear O'Connor & Christoph Hoerl - 2018 - Cognitive Development 45:1-9.
    Previous studies of children’s counterfactual reasoning have focused on scenarios in which a single causal event yielded an outcome. However, there are also cases in which an outcome would have occurred even in the absence of its actual cause, because of the presence of a further potential cause. In this study, 152 children aged 4-9 years reasoned counterfactually about such scenarios, in which there were ‘doubly-determined’ outcomes. The task involved dropping two metal discs down separate runways, each of which was (...)
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  41. added 2018-04-26
    The Origins of Causal Cognition in Early Hominins.Martin Stuart-Fox - 2015 - Biology and Philosophy 30 (2):247-266.
    Studies of primate cognition have conclusively shown that humans and apes share a range of basic cognitive abilities. As a corollary, these same studies have also focussed attention on what makes humans unique, and on when and how specifically human cognitive skills evolved. There is widespread agreement that a major distinguishing feature of the human mind is its capacity for causal reasoning. This paper argues that causal cognition originated with the use made of indirect natural signs by early hominins forced (...)
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  42. added 2018-04-26
    Normative Theory and Descriptive Psychology in Understanding Causal Reasoning: The Role of Interventions and Invariance.James Woodward - unknown
    This paper, like its companion explores some ways in which, on the one hand, normative theorizing about causation and causal reasoning and, on the other, empirical psychological investigations into causal cognition can be mutually illuminating. The topics considered include the connection between causal claims and claims about the outcomes of interventions and the various ways that invariance claims figure in causal judgment.
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  43. added 2018-04-26
    Causal Cognition: Physical Connections, Proportionality, and the Role of Normative Theory.James Woodward - unknown
    This paper, like its companion explores some ways in which, on the one hand, normative theorizing about causation and causal reasoning and, on the other, empirical psychological investigations into causal cognition can be mutually illuminating. The paper carries out this exploration in connection with a variety of topics—the role of information about the presence of a “physical connection” between cause and effect in causal judgment, the role of “proportionality” in choosing the appropriate “level” of explanation, and the role of mechanism (...)
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  44. added 2018-04-26
    Dissolution Into Death: The Mind’s Last Symptoms Indicate Annihilation.David Weisman - 2015 - In Keith Augustine & Michael Martin (eds.), The Myth of an Afterlife: The Case against Life After Death. Rowman & Littlefield. pp. 83-104.
    This paper looks at progressive neurological diseases showing brain decline correlated with the decline of consciousness, as well as the content of consciousness. For instance, a young man’s healthy and fully functional brain generated an intelligent and lovely self, but then an aggressive brain tumor grew deep within his brain. As the tumor grew, it rendered brain tissue dysfunction and direct effects followed. From focal destruction of brain tissue, an aphasia first results. What follows is the dissolution of a functional (...)
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  45. added 2018-04-26
    Causation, Evidence, and Inference.Julian Reiss - 2015 - Routledge.
    In this book, Reiss argues in favor of a tight fit between evidence, concept and purpose in our causal investigations in the sciences. There is no doubt that the sciences employ a vast array of techniques to address causal questions such as controlled experiments, randomized trials, statistical and econometric tools, causal modeling and thought experiments. But how do these different methods relate to each other and to the causal inquiry at hand? Reiss argues that there is no "gold standard" in (...)
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  46. added 2018-04-26
    Manipulating Morality: Third‐Party Intentions Alter Moral Judgments by Changing Causal Reasoning.Jonathan Phillips & Alex Shaw - 2014 - Cognitive Science 38 (8):1320-1347.
    The present studies investigate how the intentions of third parties influence judgments of moral responsibility for other agents who commit immoral acts. Using cases in which an agent acts under some situational constraint brought about by a third party, we ask whether the agent is blamed less for the immoral act when the third party intended for that act to occur. Study 1 demonstrates that third-party intentions do influence judgments of blame. Study 2 finds that third-party intentions only influence moral (...)
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  47. added 2018-04-26
    An Incremental Approach to Causal Inference in the Behavioral Sciences.Keith A. Markus - 2014 - Synthese 191 (10):2089-2113.
    Causal inference plays a central role in behavioral science. Historically, behavioral science methodologies have typically sought to infer a single causal relation. Each of the major approaches to causal inference in the behavioral sciences follows this pattern. Nonetheless, such approaches sometimes differ in the causal relation that they infer. Incremental causal inference offers an alternative to this conceptualization of causal inference that divides the inference into a series of incremental steps. Different steps infer different causal relations. Incremental causal inference is (...)
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  48. added 2018-04-26
    Reichenbach's Paradise.Leszek Wroński - 2014 - De Gruyter Open.
    Since its introduction by Hans Reichenbach, many philosophers have claimed to refute the idea – known as the common cause principle – that any surprising correlation between any two factors that do not directly influence one another is due to some common cause. For example, falsity of the principle is frequently inferred from falsifiability of Bell’s inequalities. The author demonstrates, however, that the situation is not so straightforward. There is more than one version of the principle formulated with the use (...)
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  49. added 2018-04-26
    Causal Reasoning: Philosophy and Experiment.James Woodward - unknown
    This paper explores some interactions between normative/ philosophical/theoretical theorizing about causation and empirical research into causal reasoning and judgment of the sort conducted by psychologists and others. I attempt to extract some general morals regarding the kinds of interactions between the empirical and the more traditionally philosophical that in my experience have been most fruitful. I also compare the experimental work on which I focus with some of the research strategies employed in experimental philosophy.
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  50. added 2018-04-26
    Modal Collapse in Gödel's Ontological Proof.Srećko Kovač - 2012 - In Miroslaw Szatkowski (ed.), Ontological Proofs Today. Ontos Verlag. pp. 50--323.
    After introductory reminder of and comments on Gödel’s ontological proof, we discuss the collapse of modalities, which is provable in Gödel’s ontological system GO. We argue that Gödel’s texts confirm modal collapse as intended consequence of his ontological system. Further, we aim to show that modal collapse properly fits into Gödel’s philosophical views, especially into his ontology of separation and union of force and fact, as well as into his cosmological theory of the nonobjectivity of the lapse of time. As (...)
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