Results for ' CAUSALITY'

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  1.  15
    Fred I. Dretske and Aaron Snyder.Causal Irregularity - 1999 - In Michael Tooley (ed.), Laws of nature, causation, and supervenience. New York: Garland. pp. 1--219.
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  2.  9
    Theoretical Perspectives.Causal Individualism - 1999 - In E. L. Cerroni-Long (ed.), Anthropological theory in North America. Westport, Conn.: Bergin & Garvey. pp. 105.
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  3.  15
    Mark McEVOY Hofstra University.Causal Tracking Reliabilism - 2012 - Grazer Philosophische Studien, Vol. 86-2012 86:73 - 92.
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  4. Kazem sadegh-Zadeh.A. Pragmatic Concept of Causal Explanation - 1984 - In Lennart Nordenfelt & B. Ingemar B. Lindahl (eds.), Health, Disease, and Causal Explanations in Medicine. Reidel. pp. 201.
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  5. Umlvei-idiq nacional de colcmbi.Benson Latin, Refutacion de Borges, Nota Critica El Idealismo Trascendental Kantiano, Frente Al Problema Mente-Cuerpo, Modales de Los Contextos, Putnam Y. La Teoria Causal de & U. Cabeza la ReferenciaDel Arquitecto - 1994 - Ideas Y Valores 43 (95):1.
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  6.  25
    Building causal knowledge in behavior genetics.James W. Madole & K. Paige Harden - 2023 - Behavioral and Brain Sciences 46:e182.
    Behavior genetics is a controversial science. For decades, scholars have sought to understand the role of heredity in human behavior and life-course outcomes. Recently, technological advances and the rapid expansion of genomic databases have facilitated the discovery of genes associated with human phenotypes such as educational attainment and substance use disorders. To maximize the potential of this flourishing science, and to minimize potential harms, careful analysis of what it would mean for genes to be causes of human behavior is needed. (...)
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  7. Explaining Causal Selection with Explanatory Causal Economy: Biology and Beyond.Laura R. Franklin-Hall - 2015 - In P.-A. Braillard & C. Malaterre (eds.), Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Springer. pp. 413–438.
    Among the factors necessary for the occurrence of some event, which of these are selectively highlighted in its explanation and labeled as causes-and which are explanatorily omitted, or relegated to the status of background conditions? Following J. S. Mill, most have thought that only a pragmatic answer to this question was possible. In this paper I suggest we understand this ‘causal selection problem’ in causal-explanatory terms, and propose that explanatory trade-offs between abstraction and stability can provide a principled solution to (...)
     
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  8. Probabilistic Causality.Ellery Eells - 1991 - Cambridge, England: Cambridge University Press.
    In this important book, Ellery Eells explores and refines philosophical conceptions of probabilistic causality. In a probabilistic theory of causation, causes increase the probability of their effects rather than necessitate their effects in the ways traditional deterministic theories have specified. Philosophical interest in this subject arises from attempts to understand population sciences as well as indeterminism in physics. Taking into account issues involving spurious correlation, probabilistic causal interaction, disjunctive causal factors, and temporal ideas, Professor Eells advances the analysis of (...)
  9.  28
    Actual Causality.Joseph Halpern - 2016 - MIT Press.
    A new approach for defining causality and such related notions as degree of responsibility, degrees of blame, and causal explanation. Causality plays a central role in the way people structure the world; we constantly seek causal explanations for our observations. But what does it even mean that an event C "actually caused" event E? The problem of defining actual causation goes beyond mere philosophical speculation. For example, in many legal arguments, it is precisely what needs to be established (...)
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  10.  28
    Causal Search, Causal Modeling, and the Folk.David Danks - 2016 - In Wesley Buckwalter & Justin Sytsma (eds.), Blackwell Companion to Experimental Philosophy. Malden, MA: Blackwell. pp. 463–471.
    Causal models provide a framework for precisely representing complex causal structures, where specific models can be used to efficiently predict, infer, and explain the world. At the same time, we often do not know the full causal structure a priori and so must learn it from data using a causal model search algorithm. This chapter provides a general overview of causal models and their uses, with a particular focus on causal graphical models (the most commonly used causal modeling framework) and (...)
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  11. Interpreting causality in the health sciences.Federica Russo & Jon Williamson - 2007 - International Studies in the Philosophy of Science 21 (2):157 – 170.
    We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences - pluralism about causality will not do either. Instead, we maintain, the health sciences require (...)
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  12. Causal Compatibilism and the Exclusion Problem.Terry Horgan - 2001 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 16 (1):95-115.
    Causal compatibilism claims that even though physics is causally closed, and even though mental properties are multiply realizable and are not identical to physical causal properties, mental properties are causal properties nonetheless. This position asserts that there is genuine causation at multiple descriptive/ontological levels; physics-level causal claims are not really incompatible with mentalistic causal claims. I articulate and defend a version of causal compatibilism that incorporates three key contentions. First, causation crucially involves robust patterns of counterfactual dependence among properties.Second, often (...)
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  13. Causal nominalism.Ann Whittle - 2009 - In Toby Handfield (ed.), Dispositions and causes. New York : Oxford University Press,: Clarendon Press ;.
    The causal theory of properties is standardly combined with a realist's ontology of universals or tropes. In this paper, I consider an uncharted alternative – a nominalist causal theory of properties. I discuss advantages and disadvantages of the resulting theory of properties, and explore the Rylean understanding of causal powers that emerges.
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  14. Causality, interpretation, and the mind.William Child - 1994 - Oxford, UK: Oxford University Press.
    Philosophers of mind have long been interested in the relation between two ideas: that causality plays an essential role in our understanding of the mental; and that we can gain an understanding of belief and desire by considering the ascription of attitudes to people on the basis of what they say and do. Many have thought that those ideas are incompatible. William Child argues that there is in fact no tension between them, and that we should accept both. He (...)
  15. Causality and Determination.G. E. M. Anscombe - 1993 - In E. Sosa M. Tooley (ed.), Causation. pp. 88-104.
  16. (1 other version)Causality without counterfactuals.Wesley C. Salmon - 1994 - Philosophy of Science 61 (2):297-312.
    This paper presents a drastically revised version of the theory of causality, based on analyses of causal processes and causal interactions, advocated in Salmon (1984). Relying heavily on modified versions of proposals by P. Dowe, this article answers penetrating objections by Dowe and P. Kitcher to the earlier theory. It shows how the new theory circumvents a host of difficulties that have been raised in the literature. The result is, I hope, a more satisfactory analysis of physical causality.
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  17. Causality and explanation: A reply to two critiques.Wesley C. Salmon - 1997 - Philosophy of Science 64 (3):461-477.
    This paper discusses several distinct process theories of causality offered in recent years by Phil Dowe and me. It addresses problems concerning the explication of causal process, causal interaction, and causal transmission, whether given in terms of transmission of marks, transmission of invariant or conserved quantities, or mere possession of conserved quantities. Renouncing the mark-transmission and invariant quantity criteria, I accept a conserved quantity theory similar to Dowe's--differing basically with respect to causal transmission. This paper also responds to several (...)
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  18. Causality and Coextensiveness in Aristotle's Posterior Analytics 1.13.Lucas Angioni - 2018 - Oxford Studies in Ancient Philosophy 54:159-185.
    I discuss an important feature of the notion of cause in Post. An. 1. 13, 78b13–28, which has been either neglected or misunderstood. Some have treated it as if Aristotle were introducing a false principle about explanation; others have understood the point in terms of coextensiveness of cause and effect. However, none offers a full exegesis of Aristotle's tangled argument or accounts for all of the text's peculiarities. My aim is to disentangle Aristotle's steps to show that he is arguing (...)
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  19. Causality and determination: an inaugural lecture.Gertrude Elizabeth Margaret Anscombe - 1971 - London,: Cambridge University Press.
    I IT is often declared or evidently assumed that causality is some kind of necessary connexion, or alternatively, that being caused is — non-trivially ...
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  20. Rethinking Causality in Biological and Neural Mechanisms: Constraints and Control.Jason Winning & William Bechtel - 2018 - Minds and Machines 28 (2).
    Existing accounts of mechanistic causation are not suited for understanding causation in biological and neural mechanisms because they do not have the resources to capture the unique causal structure of control heterarchies. In this paper, we provide a new account on which the causal powers of mechanisms are grounded by time-dependent, variable constraints. Constraints can also serve as a key bridge concept between the mechanistic approach to explanation and underappreciated work in theoretical biology that sheds light on how biological systems (...)
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  21.  24
    Causality.Mario Bunge - 1959 - Cambridge,: Harvard University Press.
    "I regard it as a truly seminal work in this field." — Professor William A. Wallace, author of Causality and Scientific Explanation. Non-technical and clearly written, this book focuses on the place of the casual principle in modern science. The author defines the terminology, describes various formulations, examines the two primary critiques of causality, and more.
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  22.  20
    Causal Models and Screening‐Off.Juhwa Park & Steven A. Sloman - 2016 - In Wesley Buckwalter & Justin Sytsma (eds.), Blackwell Companion to Experimental Philosophy. Malden, MA: Blackwell. pp. 450–462.
    This chapter explains the screening‐off rule in the psychological laboratory. The Markov assumption states that any variable in a set is independent in probability of all its ancestors in the set conditional on its own parents. The screening‐off rule is also critical to allow Bayes nets to make an inference of the state of an unknown variable in a causal structure from the states of other variables in that structure. The chapter examines which causal representations people use to make predictions (...)
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  23.  98
    Causal Warrant for Realism about Particle Physics.Matthias Egg - 2012 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 43 (2):259-280.
    While scientific realism generally assumes that successful scientific explanations yield information about reality, realists also have to admit that not all information acquired in this way is equally well warranted. Some versions of scientific realism do this by saying that explanatory posits with which we have established some kind of causal contact are better warranted than those that merely appear in theoretical hypotheses. I first explicate this distinction by considering some general criteria that permit us to distinguish causal warrant from (...)
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  24.  89
    Causal Bayes nets as psychological theories of causal reasoning: evidence from psychological research.York Hagmayer - 2016 - Synthese 193 (4):1107-1126.
    Causal Bayes nets have been developed in philosophy, statistics, and computer sciences to provide a formalism to represent causal structures, to induce causal structure from data and to derive predictions. Causal Bayes nets have been used as psychological theories in at least two ways. They were used as rational, computational models of causal reasoning and they were used as formal models of mental causal models. A crucial assumption made by them is the Markov condition, which informally states that variables are (...)
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  25. Causality and conserved quantities: A reply to salmon.Phil Dowe - 1995 - Philosophy of Science 62 (2):321-333.
    In a recent paper (1994) Wesley Salmon has replied to criticisms (e.g., Dowe 1992c, Kitcher 1989) of his (1984) theory of causality, and has offered a revised theory which, he argues, is not open to those criticisms. The key change concerns the characterization of causal processes, where Salmon has traded "the capacity for mark transmission" for "the transmission of an invariant quantity." Salmon argues against the view presented in Dowe (1992c), namely that the concept of "possession of a conserved (...)
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  26.  5
    The causal effects of religious service attendance on prosocial behaviours in New Zealand: A national longitudinal study.Joseph A. Bulbulia, Don E. Davis, Kenneth G. Rice, Chris G. Sibley & Geoffrey Troughton - 2024 - Archive for the Psychology of Religion 46 (3):244-267.
    We investigate the causal effects of religious service attendance on prosocial behaviours using longitudinal data from a nationally representative sample of 33,198 New Zealanders collected between 2018 and 2021. Our study innovates in three ways: (1) we use longitudinal rather than cross-sectional data; (2) we incorporate measures of help received alongside self-reported giving; and (3) our statistical models are designed to address causal questions, rather than simply to describe change over time. We model causal contrasts for three hypothetical interventions – (...)
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  27.  25
    (1 other version)A Causal Analysis of Harm.Sander Beckers, Hana Chockler & Joseph Y. Halpern - 2022 - Advances in Neural Information Processing Systems 35.
    As autonomous systems rapidly become ubiquitous, there is a growing need for a legal and regulatory framework to address when and how such a system harms someone. There have been several attempts within the philosophy literature to define harm, but none of them has proven capable of dealing with with the many examples that have been presented, leading some to suggest that the notion of harm should be abandoned and "replaced by more well-behaved notions". As harm is generally something that (...)
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  28.  92
    Causality, determination and free will: towards an anscombean account of free action.Niels van Miltenburg - 2022 - Synthese 200 (4):1-20.
    Anscombe’s “Causality and Determination” is often cited in the contemporary free will debate, but rarely discussed in much detail. It’s main contribution, it is thought, is the defense of an alternative to deterministic causation, thus clearing the way for an incompatibilist analysis of free actions in terms of probabilistic causation. However, in this paper I will show that the contemporary probabilistic analysis of free action actually stands in direct conflict with Anscombe’s lecture. Instead, I will argue, its true value (...)
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  29.  14
    Causality, Probability, and Medicine.Donald Gillies - 2017 - New York: Routledge.
    Why is understanding causation so important in philosophy and the sciences? Should causation be defined in terms of probability? Whilst causation plays a major role in theories and concepts of medicine, little attempt has been made to connect causation and probability with medicine itself. Causality, Probability, and Medicine is one of the first books to apply philosophical reasoning about causality to important topics and debates in medicine. Donald Gillies provides a thorough introduction to and assessment of competing theories (...)
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  30. Causality, identity and supervenience in the mind-body problem.Jaegwon Kim - 1979 - Midwest Studies in Philosophy 4 (1):31-49.
  31. Reducing causality to transmission.Max Kistler - 1998 - Erkenntnis 48 (1):1-25.
    The idea that causation can be reduced to transmission of an amount of some conserved quantity between events is spelled out and defended against important objections. Transmission is understood as a symmetrical relation of copresence in two distinct events. The actual asymmetry of causality has its origin in the asymmetrical character of certain irreversible physical processes and then spreads through the causal net. This conception is compatible with the possibility of backwards causation and with a causal theory of time. (...)
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  32.  79
    Volitional causality vs natural causality: reflections on their compatibility in Husserl’s phenomenology of action.Nicola Spano - 2022 - Phenomenology and the Cognitive Sciences 21 (3):669-687.
    In the present article, I introduce Husserl’s analyses of ‘natural causality’ and ‘volitional causality’, which are collected in the volume ‘Wille und Handlung’ of the Husserliana edition Studien zur Struktur des Bewußtseins. My aim is to show that Husserl’s insight into these phenomena enables us to understand more clearly both the specificity of, and the relation between, the motivational nexus belonging to the sphere of the will in contrast with the causal laws of nature. In light of this (...)
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  33. (1 other version)Bayesian Nets and Causality: Philosophical and Computational Foundations.Jon Williamson - 2004 - Oxford, England: Oxford University Press.
    Bayesian nets are widely used in artificial intelligence as a calculus for causal reasoning, enabling machines to make predictions, perform diagnoses, take decisions and even to discover causal relationships. This book, aimed at researchers and graduate students in computer science, mathematics and philosophy, brings together two important research topics: how to automate reasoning in artificial intelligence, and the nature of causality and probability in philosophy.
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  34. Causal bias in measures of inequality of opportunity.Lennart B. Ackermans - 2022 - Synthese 200 (6):1-31.
    In recent decades, economists have developed methods for measuring the country-wide level of inequality of opportunity. The most popular method, called the ex-ante method, uses data on the distribution of outcomes stratified by groups of individuals with the same circumstances, in order to estimate the part of outcome inequality that is due to these circumstances. I argue that these methods are potentially biased, both upwards and downwards, and that the unknown size of this bias could be large. To argue that (...)
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  35. Causality and Explanation in the Sciences.Bert Leuridan & Erik Weber - 2012 - Theoria 27 (2):133-136.
    Editors’ introduction to the special issue on the Causality and Explanation in the Sciences conference, held at the University of Ghent in September 2011.
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  36. Causality Reunified.Michael Strevens - 2013 - Erkenntnis 78 (2):299-320.
    Hall has recently argued that there are two concepts of causality, picking out two different kinds of causal relation. McGrath, and Hitchcock and Knobe, have recently argued that the facts about causality depend on what counts as a “default” or “normal” state, or even on the moral facts. In the light of these claims you might be tempted to agree with Skyrms that causal relations constitute, metaphysically speaking, an “amiable jumble”, or with Cartwright that ‘causation’, though a single (...)
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  37. Hierarchies, Networks, and Causality: The Applied Evolutionary Epistemological Approach.Nathalie Gontier - 2021 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 52 (2):313-334.
    Applied Evolutionary Epistemology is a scientific-philosophical theory that defines evolution as the set of phenomena whereby units evolve at levels of ontological hierarchies by mechanisms and processes. This theory also provides a methodology to study evolution, namely, studying evolution involves identifying the units that evolve, the levels at which they evolve, and the mechanisms and processes whereby they evolve. Identifying units and levels of evolution in turn requires the development of ontological hierarchy theories, and examining mechanisms and processes necessitates theorizing (...)
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  38.  53
    Causal fundamentality.Soufiane Hamri - 2022 - Synthese 200 (1):1-13.
    I present an argument for causal fundamentality, understood as the thesis that the causal history of every being, whose existence has a causal explanation, includes some uncaused beings. I argue that this thesis is a consequence of an actualist account of metaphysical modality whose novelty lies in its hybrid dispositional-essentialist foundation. I argue that my modal theory is extensionally correct and minimalistic. Its range of metaphysical necessities and possibilities is just as wide as needed to capture the pre-theoretical notion of (...)
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  39. Automatism, causality and realism: Foundational problems in the philosophy of photography.Diarmuid Costello & Dawn M. Phillips - 2008 - Philosophy Compass 4 (1):1-21.
    This article contains a survey of recent debates in the philosophy of photography, focusing on aesthetic and epistemic issues in particular. Starting from widespread notions about automatism, causality and realism in the theory of photography, the authors ask whether the prima facie tension between the epistemic and aesthetic embodied in oppositions such as automaticism and agency, causality and intentionality, realism and fictional competence is more than apparent. In this context, the article discusses recent work by Roger Scruton, Dominic (...)
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  40.  20
    Causal Mediation Analysis in the Presence of Post-treatment Confounding Variables: A Monte Carlo Simulation Study.Yasemin Kisbu-Sakarya, David P. MacKinnon, Matthew J. Valente & Esra Çetinkaya - 2020 - Frontiers in Psychology 11:554112.
    In many disciplines, mediating processes are usually investigated with randomized experiments and linear regression to determine if the treatment affects the outcome through a mediator. However, randomizing the treatment will not yield accurate causal direct and indirect estimates unless certain assumptions are satisfied since the mediator status is not randomized. This study describes methods to estimate causal direct and indirect effects and reports the results of a large Monte Carlo simulation study on the performance of the ordinary regression and modern (...)
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  41. Causal exclusion and the limits of proportionality.Neil McDonnell - 2017 - Philosophical Studies 174 (6):1459-1474.
    Causal exclusion arguments are taken to threaten the autonomy of the special sciences, and the causal efficacy of mental properties. A recent line of response to these arguments has appealed to “independently plausible” and “well grounded” theories of causation to rebut key premises. In this paper I consider two papers which proceed in this vein and show that they share a common feature: they both require causes to be proportional to their effects. I argue that this feature is a bug, (...)
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  42. Ontology, Causality and Mind: Essays in Honour of D M Armstrong.John Bacon, Keith Campbell & Lloyd Reinhardt (eds.) - 1993 - New York: Cambridge University Press.
    D. M. Armstrong is an eminent Australian philosopher whose work over many years has dealt with such subjects as: the nature of possibility, concepts of the particular and the general, causes and laws of nature, and the nature of human consciousness. This collection of essays explores the many facets of Armstrong's work, concentrating on his more recent interests. There are four sections to the book: possibility and identity, universals, laws and causality, and philosophy of mind. The contributors comprise an (...)
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  43. Causal patterns and adequate explanations.Angela Potochnik - 2015 - Philosophical Studies 172 (5):1163-1182.
    Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are not determined by settling how causal facts bear on the phenomenon to be explained. I then develop a broadly causal approach to explanation that accounts for the additional features that I argue an explanation should have. This approach to explanation makes sense of several aspects (...)
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  44. Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.
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  45. Causality in medicine with particular reference to the viral causation of cancers.Brendan Clarke - 2011 - Dissertation, University College London
    In this thesis, I give a metascientific account of causality in medicine. I begin with two historical cases of causal discovery. These are the discovery of the causation of Burkitt’s lymphoma by the Epstein-Barr virus, and of the various viral causes suggested for cervical cancer. These historical cases then support a philosophical discussion of causality in medicine. This begins with an introduction to the Russo- Williamson thesis (RWT), and discussion of a range of counter-arguments against it. Despite these, (...)
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  46.  26
    (1 other version)Causality and Explanation.Wesley C. Salmon - 1997 - New York, US: Oxford University Press USA.
    "A rich collection. Since it holds a number of introductory pieces along with advanced essays and review articles, the volume will be accessible to a broad audience and will work well in philosophy of science courses....Essential."--Lawrence Sklar, University of Michigan.
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  47. Replacing Causal Faithfulness with Algorithmic Independence of Conditionals.Jan Lemeire & Dominik Janzing - 2013 - Minds and Machines 23 (2):227-249.
    Independence of Conditionals (IC) has recently been proposed as a basic rule for causal structure learning. If a Bayesian network represents the causal structure, its Conditional Probability Distributions (CPDs) should be algorithmically independent. In this paper we compare IC with causal faithfulness (FF), stating that only those conditional independences that are implied by the causal Markov condition hold true. The latter is a basic postulate in common approaches to causal structure learning. The common spirit of FF and IC is to (...)
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  48.  91
    Local Primitive Causality and the Common Cause Principle in Quantum Field Theory.Miklos Redei & Stephen J. Summers - 2001 - Foundations of Physics 32 (3):335-355.
    If $\mathcal{A}$ (V) is a net of local von Neumann algebras satisfying standard axioms of algebraic relativistic quantum field theory and V 1 and V 2 are spacelike separated spacetime regions, then the system ( $\mathcal{A}$ (V 1 ), $\mathcal{A}$ (V 2 ), φ) is said to satisfy the Weak Reichenbach's Common Cause Principle iff for every pair of projections A∈ $\mathcal{A}$ (V 1 ), B∈ $\mathcal{A}$ (V 2 ) correlated in the normal state φ there exists a projection C (...)
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  49. (2 other versions)Causality and properties.Sydney Shoemaker - 1980 - In Peter van Inwagen (ed.), Time and Cause: Essays Presented to Richard Taylor. D. Reidel. pp. 109-35.
     
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  50.  36
    The Causal Power of Social Structures: Emergence, Structure and Agency.Dave Elder-Vass - 2010 - Cambridge University Press.
    The problem of structure and agency has been the subject of intense debate in the social sciences for over 100 years. This book offers a solution. Using a critical realist version of the theory of emergence, Dave Elder-Vass argues that, instead of ascribing causal significance to an abstract notion of social structure or a monolithic concept of society, we must recognise that it is specific groups of people that have social structural power. Some of these groups are entities with emergent (...)
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