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Phyllis Illari [28]Phyllis McKay Illari [6]Phyllis Kirstin Illari [2]
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Phyllis Illari
University College London
  1. What is a Mechanism? Thinking About Mechanisms Across the Sciences.Phyllis Illari & Jon Williamson - 2012 - European Journal for Philosophy of Science 2 (1):119-135.
    After a decade of intense debate about mechanisms, there is still no consensus characterization. In this paper we argue for a characterization that applies widely to mechanisms across the sciences. We examine and defend our disagreements with the major current contenders for characterizations of mechanisms. Ultimately, we indicate that the major contenders can all sign up to our characterization.
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  2. 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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  3.  1
    A Radical Approach to Ebola: Saving Humans and Other Animals.Sarah J. L. Edwards, Charles H. Norell, Phyllis Illari, Brendan Clarke & Carolyn P. Neuhaus - 2018 - American Journal of Bioethics 18 (10):35-42.
    As the usual regulatory framework did not fit well during the last Ebola outbreak, innovative thinking still needed. In the absence of an outbreak, randomised controlled trials of clinical efficacy in humans cannot be done, while during an outbreak such trials will continue to face significant practical, philosophical, and ethical challenges. This article argues that researchers should also test the safety and effectiveness of novel vaccines in wild apes by employing a pluralistic approach to evidence. There are three reasons to (...)
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  4.  51
    Mechanistic Evidence: Disambiguating the Russo–Williamson Thesis.Phyllis McKay Illari - 2011 - International Studies in the Philosophy of Science 25 (2):139 - 157.
    Russo and Williamson claim that establishing causal claims requires mechanistic and difference-making evidence. In this article, I will argue that Russo and Williamson's formulation of their thesis is multiply ambiguous. I will make three distinctions: mechanistic evidence as type vs object of evidence; what mechanism or mechanisms we want evidence of; and how much evidence of a mechanism we require. I will feed these more precise meanings back into the Russo?Williamson thesis and argue that it is both true and false: (...)
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  5.  86
    Mechanistic Explanation: Integrating the Ontic and Epistemic.Phyllis Illari - 2013 - Erkenntnis 78 (2):237-255.
    Craver claims that mechanistic explanation is ontic, while Bechtel claims that it is epistemic. While this distinction between ontic and epistemic explanation originates with Salmon, the ideas have changed in the modern debate on mechanistic explanation, where the frame of the debate is changing. I will explore what Bechtel and Craver’s claims mean, and argue that good mechanistic explanations must satisfy both ontic and epistemic normative constraints on what is a good explanation. I will argue for ontic constraints by drawing (...)
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  6. Function and Organization: Comparing the Mechanisms of Protein Synthesis and Natural Selection.Phyllis McKay Illari & Jon Williamson - 2010 - Studies in History and Philosophy of Science Part C 41 (3):279-291.
    In this paper, we compare the mechanisms of protein synthesis and natural selection. We identify three core elements of mechanistic explanation: functional individuation, hierarchical nestedness or decomposition, and organization. These are now well understood elements of mechanistic explanation in fields such as protein synthesis, and widely accepted in the mechanisms literature. But Skipper and Millstein have argued that natural selection is neither decomposable nor organized. This would mean that much of the current mechanisms literature does not apply to the mechanism (...)
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  7.  20
    Causality: Philosophical Theory Meets Scientific Practice.Phyllis Illari & Federica Russo - 2014 - Oxford University Press.
    Scientific and philosophical literature on causality has become highly specialised. It is hard to find suitable access points for students, young researchers, or professionals outside this domain. This book provides a guide to the complex literature, explains the scientific problems of causality and the philosophical tools needed to address them.
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  8.  40
    In Defence of Activities.Phyllis Illari & Jon Williamson - 2013 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 44 (1):69-83.
    In this paper, we examine what is to be said in defence of Machamer, Darden and Craver’s (MDC) controversial dualism about activities and entities (Machamer, Darden and Craver’s in Philos Sci 67:1–25, 2000). We explain why we believe the notion of an activity to be a novel, valuable one, and set about clearing away some initial objections that can lead to its being brushed aside unexamined. We argue that substantive debate about ontology can only be effective when desiderata for an (...)
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  9.  35
    The Evidence That Evidence-Based Medicine Omits.Brendan Clarke, Donald Gillies, Phyllis Illari, Frederica Russo & Jon Williamson - 2013 - Preventive Medicine 57:745-747.
    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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  10.  9
    Editors’ Letter.Phyllis Kirstin Illari & Federica Russo - 2018 - European Journal for Philosophy of Science 8 (3):307-308.
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  11. Mechanisms Are Real and Local.Phyllis McKay Illari & Jon Williamson - 2011 - In Phyllis McKay Illari, Federica Russo & Jon Williamson (eds.), Causality in the Sciences. Oxford University Press.
    Mechanisms have become much-discussed, yet there is still no consensus on how to characterise them. In this paper, we start with something everyone is agreed on – that mechanisms explain – and investigate what constraints this imposes on our metaphysics of mechanisms. We examine two widely shared premises about how to understand mechanistic explanation: (1) that mechanistic explanation offers a welcome alternative to traditional laws-based explanation and (2) that there are two senses of mechanistic explanation that we call ‘epistemic explanation’ (...)
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  12.  57
    Causality in the Sciences.Illari Phyllis McKay, Russo Federica & Williamson Jon (eds.) - 2011 - Oxford University Press.
    The book tackles these questions as well as others concerning the use of causality in the sciences.
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  13.  8
    Evaluating Evidence of Mechanisms in Medicine: Principles and Procedures.Veli-Pekka Parkkinen, Christian Wallmann, Michael Edward Wilde, Brendan Clarke, Phyllis Illari, Michael Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson - 2018 - Springer Verlag.
    This book is the first to develop explicit methods for evaluating evidence of mechanisms in the field of medicine. It explains why it can be important to make this evidence explicit, and describes how to take such evidence into account in the evidence appraisal process. In addition, it develops procedures for seeking evidence of mechanisms, for evaluating evidence of mechanisms, and for combining this evaluation with evidence of association in order to yield an overall assessment of effectiveness. Evidence-based medicine seeks (...)
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  14.  4
    Mechanisms, Models and Laws in Understanding Supernovae.Phyllis Illari - unknown
    There has been a burst of work in the last couple of decades on mechanistic explanation, as an alternative to the traditional covering-law model of scientific explanation. That work makes some interesting claims about mechanistic explanations rendering phenomena ‘intelligible’, but does not develop this idea in great depth. There has also been a growth of interest in giving an account of scientific understanding, as a complement to an account of explanation, specifically addressing a three-place relationship between explanation, world, and the (...)
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  15.  4
    Causality in Cancer Research: A Journey Through Models in Molecular Epidemiology and Their Philosophical Interpretation.Paolo Vineis, Phyllis Illari & Federica Russo - 2017 - Emerging Themes in Epidemiology 14 (7):1-8.
    In the last decades, Systems Biology (including cancer research) has been driven by technology, statistical modelling and bioinformatics. In this paper we try to bring biological and philosophical thinking back. We thus aim at making diferent traditions of thought compatible: (a) causality in epidemiology and in philosophical theorizing—notably, the “sufcient-component-cause framework” and the “mark transmission” approach; (b) new acquisitions about disease pathogenesis, e.g. the “branched model” in cancer, and the role of biomarkers in this process; (c) the burgeoning of omics (...)
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  16. 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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  17.  39
    Why Theories of Causality Need Production : An Information Transmission Account.Phyllis Illari - 2011 - Philosophy and Technology 24 (2):95-114.
    In this paper, I examine the comparatively neglected intuition of production regarding causality. I begin by examining the weaknesses of current production accounts of causality. I then distinguish between giving a good production account of causality and a good account of production. I argue that an account of production is needed to make sense of vital practices in causal inference. Finally, I offer an information transmission account of production based on John Collier’s work that solves the primary weaknesses of current (...)
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  18.  2
    Building General Knowledge of Mechanisms in Information Security.Jonathan M. Spring & Phyllis Illari - forthcoming - Philosophy and Technology:1-33.
    We show how more general knowledge can be built in information security, by the building of knowledge of mechanism clusters, some of which are multifield. By doing this, we address in a novel way the longstanding philosophical problem of how, if at all, we come to have knowledge that is in any way general, when we seem to be confined to particular experiences. We also address the issue of building knowledge of mechanisms by studying an area that is new to (...)
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  19.  45
    The Philosophy of Information - a Simple Introduction.Phyllis Illari - 2012 - Society for the Philosophy of Information.
    This book serves as the main reference for an undergraduate course on Philosophy of Information. The book is written to be accessible to the typical undergraduate student of Philosophy and does not require propaedeutic courses in Logic, Epistemology or Ethics. Each chapter includes a rich collection of references for the student interested in furthering her understanding of the topics reviewed in the book. -/- The book covers all the main topics of the Philosophy of Information and it should be considered (...)
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  20.  1
    Mechanisms in Medicine.Phyllis Illari - unknown
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  21.  25
    Erratum To: Metaphysics, Prescription and Methodological Disagreement.Alexander Reutlinger, Phyllis Illari, Andreas Hüttemann & Mathias Frisch - 2016 - Metascience 25 (2):339-339.
  22.  5
    Editors’ Letter.Phyllis Kirstin Illari & Federica Russo - 2018 - European Journal for Philosophy of Science 8 (1):1-2.
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  23.  5
    Editors’ Letter.Phyllis Illari & Federica Russo - 2017 - European Journal for Philosophy of Science 7 (3):391-392.
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  24.  29
    Introduction: Evidence and Causality in the Sciences.Phyllis Illari & Federica Russo - 2014 - Topoi 33 (2):293-294.
    Evidence and CausalityCausality is a vibrant and thriving topic in philosophy of science. It is closely related to many other challenging scientific concepts, such as probability and mechanisms, which arise in many different scientific contexts, in different fields. For example, probability and mechanisms are relevant to both causal inference (finding out what causes what) and causal explanation (explaining how a cause produces its effect). They are also of interest to fields as diverse as astrophysics, biochemistry, biomedical and social sciences. At (...)
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  25.  1
    Information Quality, Data and Philosophy.Luciano Floridi & Phyllis Illari - 2014 - In Phyllis Illari & Luciano Floridi (eds.), The Philosophy of Information Quality. Switzerland: Springer International Publishing. pp. 5-23.
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  26.  27
    Information Channels and Biomarkers of Disease.Phyllis Illari & Federica Russo - 2016 - Topoi 35 (1):175-190.
    Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has (...)
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  27.  1
    IQ: Purpose and Dimensions.Phyllis Illari - unknown
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  28.  20
    Introduction.Phyllis Illari, Julian Reiss & Federica Russo - 2012 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 43 (4):758-760.
  29.  4
    Information Quality, Data and Philosophy.Phyllis Illari & Luciano Floridi - unknown
    In this opening chapter, we review the literature on information quality. Our major aim is to introduce the issues, and trace some of the history of the debates, with a view to situating the chapters in this volume – whose authors come from different disciplines – to help make them accessible to readers with different backgrounds and expertise. We begin in this section by tracing some influential analyses of IQ in computer science. This is a useful basis for examining some (...)
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  30.  1
    Models for Prediction, Explanation and Control: Recursive Bayesian Networks.Lorenzo Casini, Phyllis McKay Illari, Federica Russo & Jon Williamson - 2011 - Theoria : An International Journal for Theory, History and Fundations of Science 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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  31. The Routledge Handbook of Mechanisms and Mechanical Philosophy.Stuart Glennan & Phyllis Illari (eds.) - 2017 - Routledge.
    From the operation of the universe to DNA, the brain and the economy, natural and social frequently describe their activity as being concerned with discovering mechanisms. Despite this fact, for much of the twentieth century philosophical discussions of the nature of mechanisms remained outside philosophy of science. The Routledge Handbook of Mechanisms and Mechanical Philosophy is an outstanding reference source to the key topics, problems and debates in this exciting subject and is the first collection of its kind. Comprising over (...)
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  32. The Routledge Handbook of the Philosophy of Mechanisms.Stuart Glennan & Phyllis Illari (eds.) - 2018 - Routledge.
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  33. Causality in the Sciences.Phyllis Illari, Federica Russo & Jon Williamson (eds.) - 2011 - 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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  34. Causality: Philosophical Theory Meets Scientific Practice.Phyllis Illari & Federica Russo - 2014 - Oxford, UK: Oxford University Press.
    Scientific and philosophical literature on causality has become highly specialised. It is hard to find suitable access points for students, young researchers, or professionals outside this domain. This book provides a guide to the complex literature, explains the scientific problems of causality and the philosophical tools needed to address them.
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  35. The Philosophy of Information Quality.Phyllis Illari & Luciano Floridi (eds.) - 2014 - Springer International Publishing.
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  36. Evaluating Evidence of Mechanisms in Medicine.Veli-Pekka Parkinen, Christian Wallman, Michael Wilde, Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson - 2018 - Dordrecht, Netherlands: Springer.
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