Results for 'Jon Russo'

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  1.  10
    Interpretations of probability.Jon Williamson & Federica Russo - 2010 - In Jon Williamson & Federica Russo (eds.), Key Terms in Logic. pp. 81.
    Key Terms in Logic offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no (...)
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    Bayesianism.Jon Williamson & Federica Russo - 2010 - In Jon Williamson & Federica Russo (eds.), Key Terms in Logic. pp. 27.
    Key Terms in Logic offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no (...)
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  3.  7
    Key Terms in Logic.Jon Williamson & Federica Russo (eds.) - 2010 - Continuum Press.
    An accessible guide for those facing the study of Logic For The first time, this book covers key thinkers, terms and texts.
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  4.  7
    Probabilistic logic.Jon Williamson & Federica Russo - 2010 - In Jon Williamson & Federica Russo (eds.), Key Terms in Logic. pp. 57.
    Key Terms in Logic offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no (...)
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  5.  5
    Probability.Jon Williamson & Federica Russo - 2010 - In Jon Williamson & Federica Russo (eds.), Key Terms in Logic. pp. 80.
    Key Terms in Logic offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no (...)
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  6.  8
    Richard Jeffrey.Jon Williamson & Federica Russo - 2010 - In Jon Williamson & Federica Russo (eds.), Key Terms in Logic. pp. 129.
    Key Terms in Logic offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no (...)
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  7. 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 a theory (...)
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  8. Interpreting probability in causal models for cancer.Federica Russo & Jon Williamson - 2007 - In Federica Russo & Jon Williamson (eds.), Causality and Probability in the Sciences. pp. 217--242.
    How should probabilities be interpreted in causal models in the social and health sciences? In this paper we take a step towards answering this question by investigating the case of cancer in epidemiology and arguing that the objective Bayesian interpretation is most appropriate in this domain.
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  9.  21
    Causality in the Sciences.Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.) - 2011 - New York: Oxford University Press.
    Why do ideas of how mechanisms relate to causality and probability differ so much across the sciences? Can progress in understanding the tools of causal inference in some sciences lead to progress in others? This book tackles these questions and others concerning the use of causality in the sciences.
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  10. Epistemic causality and evidence-based medicine.Federica Russo & Jon Williamson - 2011 - History and Philosophy of the Life Sciences 33 (4).
    Causal claims in biomedical contexts are ubiquitous albeit they are not always made explicit. This paper addresses the question of what causal claims mean in the context of disease. It is argued that in medical contexts causality ought to be interpreted according to the epistemic theory. The epistemic theory offers an alternative to traditional accounts that cash out causation either in terms of “difference-making” relations or in terms of mechanisms. According to the epistemic approach, causal claims tell us about which (...)
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  11. Why look at Causality in the Sciences?Phyllis McKay Illari, Federica Russo & Jon Williamson - 2011 - In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press.
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  12. EnviroGenomarkers: The Interplay Between Mechanisms and Difference Making in Establishing Causal Claims.Federica Russo & Jon Williamson - 2012 - Medicine Studies 3 (4):249-262.
    According to Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007, Hist Philos Life Sci 33:389–396, 2011a, Philos Sci 1(1):47–69, 2011b ), in order to establish a causal claim of the form, ‘_C_ is a cause of _E_’, one typically needs evidence that there is an underlying mechanism between _C_ and _E_ as well as evidence that _C_ makes a difference to _E_. This thesis has been used to argue that hierarchies of evidence, as championed by evidence-based movements, tend (...)
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  13. Causality in the sciences.Illari Phyllis McKay, Russo Federica & Williamson Jon (eds.) - 2011 - New York: Oxford University Press.
  14.  28
    Causality and Probability in the Sciences.Federica Russo & Jon Williamson (eds.) - 2007 - College Publications.
    Causal inference is perhaps the most important form of reasoning in the sciences. A panoply of disciplines, ranging from epidemiology to biology, from econometrics to physics, make use of probability and statistics to infer causal relationships. The social and health sciences analyse population-level data using statistical methods to infer average causal relations. In diagnosis of disease, probabilistic statements are based on population-level causal knowledge combined with knowledge of a particular person’s symptoms. For the physical sciences, the Salmon-Dowe account develops an (...)
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  15.  10
    Predicting “it will work for us”: (way) beyond statistics.Phyllis McKay Illari, Federica Russo & Jon Williamson - 2011 - In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences.
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  16.  86
    Evaluating evidence of mechanisms in medicine.Veli-Pekka Parkkinen, Christian Wallmann, Michael Wilde, Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson - 2018 - Dordrecht, Netherlands: Springer. Edited by Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw, Christian Wallmann, Michael Wilde & Jon Williamson.
    The use of evidence in medicine is something we should continuously seek to improve. This book seeks to develop our understanding of evidence of mechanism in evaluating evidence in medicine, public health, and social care; and also offers tools to help implement improved assessment of evidence of mechanism in practice. In this way, the book offers a bridge between more theoretical and conceptual insights and worries about evidence of mechanism and practical means to fit the results into evidence assessment procedures.
  17. Mechanisms and the Evidence Hierarchy.Brendan Clarke, Donald Gillies, Phyllis Illari, Federica Russo & Jon Williamson - 2014 - Topoi 33 (2):339-360.
    Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in (...)
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  18.  52
    Models for Prediction, Explanation and Control: Recursive Bayesian Networks.Lorenzo Casini, Phyllis McKay Illari, Federica Russo & Jon Williamson - 2011 - Theoria 26 (1):5-33.
    The Recursive Bayesian Net formalism was originally developed for modelling nested causal relationships. In this paper we argue that the formalism can also be applied to modelling the hierarchical structure of mechanisms. The resulting network contains quantitative information about probabilities, as well as qualitative information about mechanistic structure and causal relations. Since information about probabilities, mechanisms and causal relations is vital for prediction, explanation and control respectively, an RBN can be applied to all these tasks. We show in particular how (...)
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  19.  89
    The Evidence that Evidence-based Medicine Omits.Brendan Clarke, Donald Gillies, Phyllis Illari, Federica Russo & Jon Williamson - unknown
    According to current hierarchies of evidence for EBM, evidence of correlation is always more important than evidence of mechanisms when evaluating and establishing causal claims. We argue that evidence of mechanisms needs to be treated alongside evidence of correlation. This is for three reasons. First, correlation is always a fallible indicator of causation, subject in particular to the problem of confounding; evidence of mechanisms can in some cases be more important than evidence of correlation when assessing a causal claim. Second, (...)
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  20.  33
    Combining Probability and Logic.Fabio Cozman, Rolf Haenni, Jan-Willem Romeijn, Federica Russo, Gregory Wheeler & Jon Williamson - 2009 - Journal of Applied Logic 7 (2):131-135.
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  21.  16
    Assessment of Top-Down Attention for a Closed-Loop Performance Enhancement System Using High-Frequency Steady-State Visually Evoked Potentials and Eye Tracking.Matthew Pava, Walker Alexander, Gabriel Collins, Brad Galego, Jon Russo, Assaf Harel, Olivia Fox, Natalie Hansen & Bartlett Russell - 2018 - Frontiers in Human Neuroscience 12.
  22.  20
    Building a Cognitive Profile with a Non-Intrusive Sensor: How Speech and Sounds Map onto our Cognitive Worlds.Gabriel Collins, Jason Poleski, Matthias Mehl, Allison Tackman, Ramon Reyes, Amanda Kraft, Jon Russo, Dylan Kenny, Peter Bryan, Edwin Simons & William Casebeer - 2018 - Frontiers in Human Neuroscience 12.
  23.  88
    Establishing Causal Claims in Medicine.Jon Williamson - 2019 - International Studies in the Philosophy of Science 32 (1):33-61.
    Russo and Williamson put forward the following thesis: in order to establish a causal claim in medicine, one normally needs to establish both that the putative cause and putative effect are appropriately correlated and that there is some underlying mechanism that can account for this correlation. I argue that, although the Russo-Williamson thesis conflicts with the tenets of present-day evidence-based medicine, it offers a better causal epistemology than that provided by present-day EBM because it better explains two key (...)
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  24.  56
    Establishing the teratogenicity of Zika and evaluating causal criteria.Jon Williamson - 2018 - Synthese 198 (Suppl 10):2505-2518.
    The teratogenicity of the Zika virus was considered established in 2016, and is an interesting case because three different sets of causal criteria were used to assess teratogenicity. This paper appeals to the thesis of Russo and Williamson (2007) to devise an epistemological framework that can be used to compare and evaluate sets of causal criteria. The framework can also be used to decide when enough criteria are satisfied to establish causality. Arguably, the three sets of causal criteria considered (...)
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  25. Imaging Technology and the Philosophy of Causality.Jon Williamson - 2011 - Philosophy and Technology 24 (2):115-136.
    Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007) put forward the thesis that, at least in the health sciences, to establish the claim that C is a cause of E, one normally needs evidence of an underlying mechanism linking C and E as well as evidence that C makes a difference to E. This epistemological thesis poses a problem for most current analyses of causality which, in virtue of analysing causality in terms of just one of mechanisms or (...)
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  26.  7
    Williamson, Jon/Russo, Federica (eds.) 2010. Key Terms in Logic. London/New York: Continuum (192 pages, ISBN 978-1-8470-6114-0; £ 12,99 (paperback)). [REVIEW]Stamatios Gerogiorgakis - 2013 - History of Philosophy & Logical Analysis 16 (1):384-386.
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  27. [Review of] Jon Williamson/Federica Russo (eds.), Key Terms in Logic, London: Continuum, 2010. [REVIEW]Stamatios Gerogiorgakis - 2013 - History of Philosophy & Logical Analysis 16:384-386.
  28.  21
    Extrapolation and the Russo–Williamson thesis.Michael Wilde & Veli-Pekka Parkkinen - 2019 - Synthese 196 (8):3251-3262.
    A particular tradition in medicine claims that a variety of evidence is helpful in determining whether an observed correlation is causal. In line with this tradition, it has been claimed that establishing a causal claim in medicine requires both probabilistic and mechanistic evidence. This claim has been put forward by Federica Russo and Jon Williamson. As a result, it is sometimes called the Russo–Williamson thesis. In support of this thesis, Russo and Williamson appeal to the practice of (...)
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  29. The Rationale of Variation in Methodological and Evidential Pluralism.Federica Russo - 2006 - Philosophica 77 (1).
    Causal analysis in the social sciences takes advantage of a variety of methods and of a multi-fold source of information and evidence. This pluralistic methodology and source of information raises the question of whether we should accordingly have a pluralistic metaphysics and epistemology. This paper focuses on epistemology and argues that a pluralistic methodology and evidence don’t entail a pluralistic epistemology. It will be shown that causal models employ a single rationale of testing, based on the notion of variation. Further, (...)
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  30. Situations and attitudes.Jon Barwise & John Perry - 1981 - Journal of Philosophy 78 (11):668-691.
  31. Situations and Attitudes.Jon Barwise & John Perry - 1983 - Cambridge, Mass.: MIT Press. Edited by John Perry.
  32. On the physical significance of the locality conditions in the bell arguments.Jon P. Jarrett - 1984 - Noûs 18 (4):569-589.
  33. Peirce’s evolving interpretants.Jon Alan Schmidt - 2022 - Semiotica 2022 (246):211-223.
    The semeiotic of Charles Sanders Peirce is irreducibly triadic, positing that a sign mediates between the object that determines it and the interpretant that it determines. He eventually holds that each sign has two objects and three interpretants, standardizing quickly on immediate and dynamical for the objects but experimenting with a variety of names for the interpretants. The two most prominent terminologies are immediate/dynamical/final and emotional/energetic/logical, and scholars have long debated how they are related to each other. This paper seeks (...)
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  34.  50
    The Cultural Evolution of Structured Languages in an Open‐Ended, Continuous World.W. Carr Jon, Smith Kenny, Cornish Hannah & Kirby Simon - 2017 - Cognitive Science 41 (4):892-923.
    Language maps signals onto meanings through the use of two distinct types of structure. First, the space of meanings is discretized into categories that are shared by all users of the language. Second, the signals employed by the language are compositional: The meaning of the whole is a function of its parts and the way in which those parts are combined. In three iterated learning experiments using a vast, continuous, open-ended meaning space, we explore the conditions under which both structured (...)
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  35. Grounding Grounding.Jon Litland - 2017 - Oxford Studies in Metaphysics 10.
    The Problem of Iterated Ground is to explain what grounds truths about ground: if Γ grounds φ, what grounds that Γ grounds φ? This paper develops a novel solution to this problem. The basic idea is to connect ground to explanatory arguments. By developing a rigorous account of explanatory arguments we can equip operators for factive and non-factive ground with natural introduction and elimination rules. A satisfactory account of iterated ground falls directly out of the resulting logic: non- factive grounding (...)
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  36.  28
    Simplicity and informativeness in semantic category systems.Jon W. Carr, Kenny Smith, Jennifer Culbertson & Simon Kirby - 2020 - Cognition 202 (C):104289.
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  37.  83
    Changing the Paradigm for Engineering Ethics.Jon Alan Schmidt - 2014 - Science and Engineering Ethics 20 (4):985-1010.
    Modern philosophy recognizes two major ethical theories: deontology, which encourages adherence to rules and fulfillment of duties or obligations; and consequentialism, which evaluates morally significant actions strictly on the basis of their actual or anticipated outcomes. Both involve the systematic application of universal abstract principles, reflecting the culturally dominant paradigm of technical rationality. Professional societies promulgate codes of ethics with which engineers are expected to comply, while courts and the public generally assign liability to engineers primarily in accordance with the (...)
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  38. On Some Counterexamples to the Transitivity of Grounding.Jon Erling Litland - 2013 - Essays in Philosophy 14 (1):19-32.
    I discuss three recent counterexamples to the transitivity of grounding due to Jonathan Schaffer. I argue that the counterexamples don’t work and draw some conclusions about the relationship between grounding and explanation.
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  39.  49
    Generalized Quantifiers and Natural Language.Jon Barwise - 1980 - Linguistics and Philosophy 4:159.
  40. Aesthetic Testimony.Jon Robson - 2012 - Philosophy Compass 7 (1):1-10.
    It is frequently claimed that we can learn very little, if anything, about the aesthetic character of an artwork on the basis of testimony. Such disparaging assessments of the epistemic value of aesthetic testimony contrast markedly with our acceptance of testimony as an important source of knowledge in many other areas. There have, however, been a number of challenges to this orthodoxy of late; from those who seek to deny that such a contrast exists as well as attempts by those (...)
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  41. Peirce's Maxim of Pragmatism: 61 Formulations.Jon Alan Schmidt - 2020 - Transactions of the Charles S. Peirce Society 56 (4):580-599.
    Peirce is best known as the founder of pragmatism, but his dissatisfaction with how others understood and appropriated it prompted him to rename his own doctrine “pragmaticism” and to compose several variants of his original maxim defining it, as well as numerous restatements and elaborations. This paper presents an extensive selection of such formulations, followed by analysis and commentary demonstrating that for Peirce the ultimate meaning of an intellectual concept is properly expressed as a conditional proposition about the deliberate, self-controlled (...)
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  42.  11
    Targeting of widening participation measures by elite institutions: widening access or simply aiding recruitment?Jon Rainford - 2017 - Perspectives: Policy and Practice in Higher Education 21 (2-3):45-50.
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  43. Grounding, Explanation, and the Limit of Internality.Jon Erling Litland - 2015 - Philosophical Review 124 (4):481-532.
    Most authors on metaphysical grounding have taken full grounding to be an internal relation in the sense that it's necessary that if the grounds and the grounded both obtain, then the grounds ground the grounded. The negative part of this essay exploits empirical and provably nonparadoxical self-reference to prove conclusively that even immediate full grounding isn't an internal relation in this sense. The positive, second part of this essay uses the notion of a “completely satisfactory explanation” to shed light on (...)
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  44. A Natural History of Negation.Jon Barwise & Laurence R. Horn - 1991 - Journal of Symbolic Logic 56 (3):1103.
  45.  39
    Inquiry.Jon Barwise - 1986 - Philosophical Review 95 (3):429.
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  46.  34
    Admissible sets and structures: an approach to definability theory.Jon Barwise - 1975 - New York: Springer Verlag.
  47. A social epistemology of aesthetics: belief polarization, echo chambers and aesthetic judgement.Jon Robson - 2014 - Synthese 191 (11):2513-2528.
    How do we form aesthetic judgements? And how should we do so? According to a very prominent tradition in aesthetics it would be wrong to form our aesthetic judgements about a particular object on the basis of anything other than first-hand acquaintance with the object itself (or some very close surrogate) and, in particular, it would be wrong to form such judgements merely on the basis of testimony. Further this tradition presupposes that our actual practice of forming aesthetic judgements typically (...)
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  48. Information Flow: The Logic of Distributed Systems.Jon Barwise & Jerry Seligman - 1997 - Cambridge University Press.
    Presents a mathematically rigorous, philosophically sound foundation for a science of information.
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  49.  24
    A truth maintenance system.Jon Doyle - 1979 - Artificial Intelligence 12 (3):231-272.
  50.  25
    Science and values: a two-way direction.Emanuele Ratti & Federica Russo - 2024 - European Journal for Philosophy of Science 14 (1):1-23.
    In the science and values literature, scholars have shown how science is influenced and shaped by values, often in opposition to the ‘value free’ ideal of science. In this paper, we aim to contribute to the science and values literature by showing that the relation between science and values flows not only from values into scientific practice, but also from (allegedly neutral) science to values themselves. The extant literature in the ‘science and values’ field focuses by and large on reconstructing, (...)
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