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  1. Resolving empirical controversies with mechanistic evidence.Mariusz Maziarz - forthcoming - Synthese:1-22.
    The results of econometric modeling are fragile in the sense that minor changes in estimation techniques or sample can lead to statistical models that support inconsistent causal hypotheses. The fragility of econometric results undermines making conclusive inferences from the empirical literature. I argue that the program of evidential pluralism, which originated in the context of medicine and encapsulates to the normative reading of the Russo-Williamson Thesis that causal claims need the support of both difference-making and mechanistic evidence, offers a ground (...)
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  • Mechanisms in Clinical Practice: Use and Justification.Mark R. Tonelli & Jon Williamson - 2020 - Medicine, Health Care and Philosophy 23 (1):115-124.
    While the importance of mechanisms in determining causality in medicine is currently the subject of active debate, the role of mechanistic reasoning in clinical practice has received far less attention. In this paper we look at this question in the context of the treatment of a particular individual, and argue that evidence of mechanisms is indeed key to various aspects of clinical practice, including assessing population-level research reports, diagnostic as well as therapeutic decision making, and the assessment of treatment effects. (...)
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  • Reinforced Reasoning in Medicine.Daniel Auker-Howlett & Michael Wilde - 2020 - Journal of Evaluation in Clinical Practice 26 (2):458-464.
    Some philosophers have argued that evidence of underlying mechanisms does not provide evidence for the effectiveness of a medical intervention. One such argument appeals to the unreliability of mechanistic reasoning. However, mechanistic reasoning is not the only way that evidence of mechanisms might provide evidence of effectiveness. A more reliable type of reasoning may be distinguished by appealing to recent work on evidential pluralism in the epistemology of medicine. A case study from virology provides an example of this so‐called reinforced (...)
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  • Evidential Proximity, Independence, and the Evaluation of Carcinogenicity.Jon Williamson - 2019 - Journal of Evaluation in Clinical Practice 25 (6):955-961.
    This paper analyses the methods of the International Agency for Research on Cancer for evaluating the carcinogenicity of various agents. I identify two fundamental evidential principles that underpin these methods, which I call Evidential Proximity and Independence. I then show, by considering the 2018 evaluation of the carcinogenicity of styrene and styrene‐7,8‐oxide, that these principles have been implemented in a way that can lead to inconsistency. I suggest a way to resolve this problem: admit a general exception to Independence and (...)
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  • Models in Systems Medicine.Jon Williamson - unknown
    Systems medicine is a promising new paradigm for discovering associations, causal relationships and mechanisms in medicine. But it faces some tough challenges that arise from the use of big data: in particular, the problem of how to integrate evidence and the problem of how to structure the development of models. I argue that objective Bayesian models offer one way of tackling the evidence integration problem. I also offer a general methodology for structuring the development of models, within which the objective (...)
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  • Rules Versus Standards: What Are the Costs of Epistemic Norms in Drug Regulation?David Teira & Mattia Andreoletti - 2019 - Science, Technology, and Human Values 44 (6):1093-1115.
    Over the last decade, philosophers of science have extensively criticized the epistemic superiority of randomized controlled trials for testing safety and effectiveness of new drugs, defending instead various forms of evidential pluralism. We argue that scientific methods in regulatory decision-making cannot be assessed in epistemic terms only: there are costs involved. Drawing on the legal distinction between rules and standards, we show that drug regulation based on evidential pluralism has much higher costs than our current RCT-based system. We analyze these (...)
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  • 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 aspects of (...)
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  • Evaluating Evidential Pluralism in Epidemiology: Mechanistic Evidence in Exposome Research.Stefano Canali - 2019 - History and Philosophy of the Life Sciences 41 (1):4.
    In current philosophical discussions on evidence in the medical sciences, epidemiology has been used to exemplify a specific version of evidential pluralism. According to this view, known as the Russo–Williamson Thesis, evidence of both difference-making and mechanisms is produced to make causal claims in the health sciences. In this paper, I present an analysis of data and evidence in epidemiological practice, with a special focus on research on the exposome, and I cast doubt on the extent to which evidential pluralism (...)
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  • Calibration for Epistemic Causality.Jon Williamson - forthcoming - Erkenntnis:1-20.
    The epistemic theory of causality is analogous to epistemic theories of probability. Most proponents of epistemic probability would argue that one's degrees of belief should be calibrated to chances, insofar as one has evidence of chances. The question arises as to whether causal beliefs should satisfy an analogous calibration norm. In this paper, I formulate a particular version of a norm requiring calibration to chances and argue that this norm is the most fundamental evidential norm for epistemic probability. I then (...)
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