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558The Rationale of Variation in Methodological and Evidential PluralismPhilosophica 77 (1). 2006.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 dont entail a pluralistic epistemology. It will be shown that causal models employ a single rationale of testing, bas…Read more
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488Interpreting causality in the health sciencesInternational Studies in the Philosophy of Science 21 (2). 2007.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 th…Read more
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375The Agency and the Manipulability theory of causation, in spite of significant differences, share at least three claims. First, that manipulation – roughly, that by manipulating causes we bring about effects – is a central notion for causation; second, that such a notion of manipulation allows a reductive – i.e. general and comprehensive – account of causation; third, that this view has its forefathers in the works of Collingwood, Gasking and von Wright. This paper mainly challenges the third cl…Read more
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278Salmon and Van Fraassen on the existence of unobservable entities: A matter of interpretation of probability (review)Foundations of Science 11 (3): 221-247. 2006.A careful analysis of Salmon’s Theoretical Realism and van Fraassen’s Constructive Empiricism shows that both share a common origin: the requirement of literal construal of theories inherited by the Standard View. However, despite this common starting point, Salmon and van Fraassen strongly disagree on the existence of unobservable entities. I argue that their different ontological commitment towards the existence of unobservables traces back to their different views on the interpretation of pro…Read more
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272Mechanisms and the Evidence HierarchyTopoi 33 (2): 339-360. 2014.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 mecha…Read more
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169Causality and causal modelling in the social sciencesSpringer, Dordrecht. 2009.The anti-causal prophecies of last century have been disproved. Causality is neither a ‘relic of a bygone’ nor ‘another fetish of modern science’; it still occupies a large part of the current debate in philosophy and the sciences. This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus break…Read more
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124Public health policy, evidence, and causation: lessons from the studies on obesityMedicine, Health Care and Philosophy 15 (2): 141-151. 2012.The paper addresses the question of how different types of evidence ought to inform public health policy. By analysing case studies on obesity, the paper draws lessons about the different roles that different types of evidence play in setting up public health policies. More specifically, it is argued that evidence of difference-making supports considerations about ‘what works for whom in what circumstances’, and that evidence of mechanisms provides information about the ‘causal pathways’ to inte…Read more
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114Epistemic causality and evidence-based medicineHistory and Philosophy of the Life Sciences 33 (4). 2011.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 …Read more
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113Variational Causal Claims in EpidemiologyPerspectives in Biology and Medicine 52 (4): 540-554. 2009.The paper examines definitions of ‘cause’ in the epidemiological literature. Those definitions all describe causes as factors that make a difference to the distribution of disease or to individual health status. In the philosophical jargon, causes in epidemiology are difference-makers. Two claims are defended. First, it is argued that those definitions underpin an epistemology and a methodology that hinge upon the notion of variation, contra the dominant Humean paradigm according to which we inf…Read more
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106Causality: Philosophical theory meets scientific practiceOxford University Press. 2014.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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105Correlational Data, Causal Hypotheses, and ValidityJournal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 42 (1). 2011.A shared problem across the sciences is to make sense of correlational data coming from observations and/or from experiments. Arguably, this means establishing when correlations are causal and when they are not. This is an old problem in philosophy. This paper, narrowing down the scope to quantitative causal analysis in social science, reformulates the problem in terms of the validity of statistical models. Two strategies to make sense of correlational data are presented: first, a 'structural st…Read more
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104EnviroGenomarkers: The Interplay Between Mechanisms and Difference Making in Establishing Causal ClaimsMedicine Studies 3 (4): 249-262. 2012.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 to give primacy to ev…Read more
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101Causality in the sciences (edited book)Oxford University Press. 2011.The book tackles these questions as well as others concerning the use of causality in the sciences.
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86Representation and Structure in Economics. The Methodology of Econometric Models of the Consumption Function, Hsiang-Ke Chao. Routledge, 2009, xiv + 161 pages (review)Economics and Philosophy 26 (1): 114-118. 2010.
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84The notion of ‘causal web’ emerged in the epidemiological literature in the early Sixties and had to wait until the Nineties for a thorough critical appraisal. Famously, Nancy Krieger argued that such a notion isn’t helpful unless we specify what kind of spiders create the webs. This means, according to Krieger, (i) that the role of the spiders is to provide an explanation of the yarns of the web and (ii) that the sought spiders have to be biological and social. This paper contributes to the dev…Read more
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82Evaluating 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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78Are causal analysis and system analysis compatible approaches?International Studies in the Philosophy of Science 24 (1). 2010.In social science, one objection to causal analysis is that the assumption of the closure of the system makes the analysis too narrow in scope, that is, it considers only 'closed' and 'hermetic' systems thus neglecting many other external influences. On the contrary, system analysis deals with complex structures where every element is interrelated with everything else in the system. The question arises as to whether the two approaches can be compatible and whether causal analysis can be integrat…Read more
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74Information Channels and Biomarkers of DiseaseTopoi 35 (1): 175-190. 2016.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 …Read more
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70Causal models and evidential pluralism in econometricsJournal of Economic Methodology 21 (1): 54-76. 2014.Social research, from economics to demography and epidemiology, makes extensive use of statistical models in order to establish causal relations. The question arises as to what guarantees the causal interpretation of such models. In this paper we focus on econometrics and advance the view that causal models are ‘augmented’ statistical models that incorporate important causal information which contributes to their causal interpretation. The primary objective of this paper is to argue that causal …Read more
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68Introduction: Evidence and Causality in the SciencesTopoi 33 (2): 293-294. 2014.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 astro…Read more
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57Connecting ethics and epistemology of AIAI and Society 1-19. forthcoming.The need for fair and just AI is often related to the possibility of understanding AI itself, in other words, of turning an opaque box into a glass box, as inspectable as possible. Transparency and explainability, however, pertain to the technical domain and to philosophy of science, thus leaving the ethics and epistemology of AI largely disconnected. To remedy this, we propose an integrated approach premised on the idea that a glass-box epistemology should explicitly consider how to incorporate…Read more
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51Models 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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51On Empirical GeneralisationsIn Dennis Dieks, Wenceslao J. Gonzalez, Stephan Hartmann, Michael Stöltzner & Marcel Weber (eds.), Probabilities, Laws, and Structures, Springer Verlag. pp. 123-139. 2012.Manipulationism holds that information about the results of interventions is of utmost importance for scientific practices such as causal assessment or explanation. Specifically, manipulation provides information about the stability, or invariance, of the relationship between X and Y: were we to wiggle the cause X, the effect Y would accordingly wiggle and, additionally, the relation between the two will not be disrupted. This sort of relationship between variables are called 'invariant empirica…Read more
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49Scientific Disagreement and Evidential Pluralism: Lessons from the Studies on HypercholesterolemiaHumana Mente 10 (32): 75-116. 2017.Inconsistencies between scientific theories have been studied, by and large, from the perspective of paraconsistent logic. This approach considered the formal properties of theories and the structure of inferences one can legitimately draw from theories. However, inconsistencies can be also analysed from the perspective of modelling practices, in particular how modelling practices may lead scientists to form opinions and attitudes that are different, but not necessarily inconsistent. In such cas…Read more
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48Functions and Mechanisms in Structural-Modelling ExplanationsJournal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 45 (1): 187-208. 2014.One way social scientists explain phenomena is by building structural models. These models are explanatory insofar as they manage to perform a recursive decomposition on an initial multivariate probability distribution, which can be interpreted as a mechanism. Explanations in social sciences share important aspects that have been highlighted in the mechanisms literature. Notably, spelling out the functioning the mechanism gives it explanatory power. Thus social scientists should choose the varia…Read more
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46What Invariance Is and How to Test for ItInternational Studies in the Philosophy of Science 28 (2): 157-183. 2014.Causal assessment is the problem of establishing whether a relation between (variable) X and (variable) Y is causal. This problem, to be sure, is widespread across the sciences. According to accredited positions in the philosophy of causality and in social science methodology, invariance under intervention provides the most reliable test to decide whether X causes Y. This account of invariance (under intervention) has been criticised, among other reasons, because it makes manipulations on the pu…Read more
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45Epistemic Diversity and the Question of Lingua Franca in Science and PhilosophyFoundations of Science 25 (1): 185-207. 2020.Epistemic diversity is the ability or possibility of producing diverse and rich epistemic apparati to make sense of the world around us. In this paper we discuss whether, and to what extent, different conceptions of knowledge—notably as ‘justified true belief’ and as ‘distributed and embodied cognition’—hinder or foster epistemic diversity. We then link this discussion to the widespread move in science and philosophy towards monolingual disciplinary environments. We argue that English, despite a…Read more
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40Strevens. 2009. Depth. An account of scientific explanations (review)Theoria : An International Journal for Theory, History and Fundations of Science 26 (2): 261-263. 2011.
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40The reality of the unobservable. Observability, unobservability and their impact on the issue of scientific realism. Edited by Evandro Agazzi and Massimo Pauri (review)Revue Philosophique De Louvain 101 (1): 176-179. 2003.
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38Causality in Cancer Research: a Journey Through Models in Molecular Epidemiology and their Philosophical InterpretationEmerging Themes in Epidemiology 14 (7): 1-8. 2017.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…Read more