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37Towards the entropy-limit conjectureAnnals of Pure and Applied Logic 172 (2): 102870. 2020.The maximum entropy principle is widely used to determine non-committal probabilities on a finite domain, subject to a set of constraints, but its application to continuous domains is notoriously problematic. This paper concerns an intermediate case, where the domain is a first-order predicate language. Two strategies have been put forward for applying the maximum entropy principle on such a domain: applying it to finite sublanguages and taking the pointwise limit of the resulting probabilities …Read more
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37The Principal Principle and subjective BayesianismEuropean Journal for Philosophy of Science 10 (1): 1-14. 2019.This paper poses a problem for Lewis’ Principal Principle in a subjective Bayesian framework: we show that, where chances inform degrees of belief, subjective Bayesianism fails to validate normal informal standards of what is reasonable. This problem points to a tension between the Principal Principle and the claim that conditional degrees of belief are conditional probabilities. However, one version of objective Bayesianism has a straightforward resolution to this problem, because it avoids thi…Read more
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52The Principal Principle and subjective BayesianismEuropean Journal for Philosophy of Science 10 (1): 1-14. 2019.This paper poses a problem for Lewis’ Principal Principle in a subjective Bayesian framework: we show that, where chances inform degrees of belief, subjective Bayesianism fails to validate normal informal standards of what is reasonable. This problem points to a tension between the Principal Principle and the claim that conditional degrees of belief are conditional probabilities. However, one version of objective Bayesianism has a straightforward resolution to this problem, because it avoids thi…Read more
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41Mechanisms in clinical practice: use and justificationMedicine, Health Care and Philosophy 23 (1): 115-124. 2020.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,…Read more
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IntroductionIn Veli-Pekka Parkkinen, Christian Wallmann, Michael Wilde, Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson (eds.), Evaluating evidence of mechanisms in medicine, Springer. 2018.
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How to Consider Evidence of Mechanisms: An OverviewIn Veli-Pekka Parkkinen, Christian Wallmann, Michael Wilde, Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson (eds.), Evaluating evidence of mechanisms in medicine, Springer. 2018.
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Assessing ExposuresIn Veli-Pekka Parkkinen, Christian Wallmann, Michael Wilde, Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson (eds.), Evaluating evidence of mechanisms in medicine, Springer. 2018.
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Particularisation to an IndividualIn Veli-Pekka Parkkinen, Christian Wallmann, Michael Wilde, Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson (eds.), Evaluating evidence of mechanisms in medicine, Springer. 2018.
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ToolsIn Veli-Pekka Parkkinen, Christian Wallmann, Michael Wilde, Brendan Clarke, Phyllis Illari, Michael P. Kelly, Charles Norell, Federica Russo, Beth Shaw & Jon Williamson (eds.), Evaluating evidence of mechanisms in medicine, Springer. 2018.
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79Evaluating evidence of mechanisms in medicineSpringer. 2018.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…Read more
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7Correction to: Establishing the teratogenicity of Zika and evaluating causal criteriaSynthese 198 (Suppl 10): 2519-2519. 2018.Table 4 in original article has been corrected.
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59Establishing the teratogenicity of Zika and evaluating causal criteriaSynthese 198 (Suppl 10): 2505-2518. 2018.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 con…Read more
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8From bayesianism to the epistemic view of mathematics: Richard Jeffrey. Subjective probability: The real thing. Cambridge: Cambridge university press, 2004. Isbn 0-521-82971-2 , 0-521-53668-5 . Pp. XVI + 124 (review)Philosophia Mathematica 14 (3): 365-369. 2006.
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43The use of evidence of mechanisms in drug approvalJournal of Evaluation in Clinical Practice. forthcoming.The role of mechanistic evidence tends to be under-appreciated in current evidencebased medicine (EBM), which focusses on clinical studies, tending to restrict attention to randomized controlled studies (RCTs) when they are available. The EBM+ programme seeks to redress this imbalance, by suggesting methods for evaluating mechanistic studies alongside clinical studies. Drug approval is a problematic case for the view that mechanistic evidence should be taken into account, because RCTs are almost…Read more
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22Models in medicineIn Miriam Solomon, Jeremy R. Simon & Harold Kincaid (eds.), The Routledge Companion to Philosophy of Medicine, Routledge. 2016.
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27Models in Systems MedicineDisputatio 9 (47): 429-469. 2017.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 w…Read more
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8Review of Lorenzo Magnani: 'Abduction, Reason and Science: Processes of Discovery and Explanation' (review)British Journal for the Philosophy of Science 54 (2): 353-358. 2003.
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51Justifying the Principle of IndifferenceEuropean Journal for the Philosophy of Science. forthcoming.This paper presents a new argument for the Principle of Indifference. This argument can be thought of in two ways: as a pragmatic argument, justifying the principle as needing to hold if one is to minimise worst-case expected loss, or as an epistemic argument, justifying the principle as needing to hold in order to minimise worst-case expected inaccuracy. The question arises as to which interpretation is preferable. I show that the epistemic argument contradicts Evidentialism and suggest that th…Read more
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64Justifying the principle of indifferenceEuropean Journal for Philosophy of Science 8 (3): 559-586. 2018.This paper presents a new argument for the Principle of Indifference. This argument can be thought of in two ways: as a pragmatic argument, justifying the principle as needing to hold if one is to minimise worst-case expected loss, or as an epistemic argument, justifying the principle as needing to hold in order to minimise worst-case expected inaccuracy. The question arises as to which interpretation is preferable. I show that the epistemic argument contradicts Evidentialism and suggest that th…Read more
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107Establishing Causal Claims in MedicineInternational Studies in the Philosophy of Science 32 (1): 33-61. 2019.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 …Read more
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39Intervention and Identifiability in Latent Variable ModellingMinds and Machines 28 (2): 243-264. 2018.We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian networks with hidden nodes. This allows us to clarify the use of interventions for dealing with uni…Read more
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31Maximum Entropy Applied to Inductive Logic and Reasoning (edited book)Ludwig-Maximilians-Universität München. 2015.This editorial explains the scope of the special issue and provides a thematic introduction to the contributed papers.
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28Causality in the Sciences (edited book)Oxford University Press. 2011.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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61Models for Prediction, Explanation and Control: Recursive Bayesian NetworksTheoria 26 (1): 5-33. 2011.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 cont…Read more
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467Interpreting probability in causal models for cancerIn Federica Russo & Jon Williamson (eds.), Causality and Probability in the Sciences, College Publications. pp. 217--242. 2007.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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17Teaching & Learning Guide for: Mechanistic Theories of CausalityPhilosophy Compass 6 (6): 445-447. 2011.