This paper argues that machine learning and epidemiology are on collision course over causation. The discipline of epidemiology lays great emphasis on causation, while ML research does not. Some epidemiologists have proposed imposing what amounts to a causal constraint on ML in epidemiology, requiring it either to engage in causal inference or restrict itself to mere projection. We whittle down the issues to the question of whether causal knowledge is necessary for underwriting predictions about the outcomes of public health interventions. (...) While there is great plausibility to the idea that it is, conviction that something is impossible does not by itself motivate a constraint to forbid trying. We disambiguate the possible motivations for such a constraint into definitional, metaphysical, epistemological, and pragmatic considerations and argue that “Proceed with caution” is the outcome of each. We then argue that there are positive reasons to proceed, albeit cautiously. Causal inference enforces existing classification schema prior to the testing of associational claims, but associations and classification schema are more plausibly discovered in a back-and-forth process of gaining reflective equilibrium. ML instantiates this kind of process, we argue, and thus offers the welcome prospect of uncovering meaningful new concepts in epidemiology and public health—provided it is not causally constrained. (shrink)

The general goal is to encourage informal logicians and those interested in applied epistemology to look at epidemiology as a paradigmatic science crucially dependant on argumentation to justify its claims. Three specific goals are: 1. exemplify applied epistemology by looking critically at causal argumentation in epidemiology, 2. show that justification of causal claims in epidemiology is a form of “argument to the best explanation,” 3. show that there could be a symbiotic relationship between epidemiology and work in various applied reasoning (...) disciplines such as argumentation and “applied epistemology.”. (shrink)

Improving the evidence in public health is an important goal for the health promotion community. With better evidence, health professionals can make better decisions to achieve effectiveness in their interventions. The relative failure of such evidence in public health is well-known, and it is due to several factors. Briefly, from an epistemological point of view, it is not easy to develop evidence-based public health because public health interventions are highly complex and indeterminate. This paper proposes an analytical explanation of the (...) complexity and indeterminacy of public health interventions in terms of 12 points. Public health interventions are considered as a causal chain constituted by three elements and two levels of evaluation. Public health interventions thus differ from clinical interventions, which comprise two causal elements and one level of evaluation. From the two levels of evaluation, we suggest a classification of evidence into four typologies: evidence of both relations; evidence of the second but not of the first relation; evidence of the first but not of the second relation; and no evidence of either relation. In addition, a grading of indeterminacy of public health interventions is introduced. This theoretical point of view could be useful for public health professionals to better define and classify the public health interventions before acting. (shrink)

After describing the disorder of psychopathy, I examine the theories and the evidence concerning the psychopaths’ deficient moral capacities. I first examine whether or not psychopaths can pass tests of moral knowledge. Most of the evidence suggests that they can. If there is a lack of moral understanding, then it has to be due to an incapacity that affects not their declarative knowledge of moral norms, but their deeper understanding of them. I then examine two suggestions: it is their deficient (...) practical reason or their stunted emotions that are at fault. The evidence supports both explanations. I conclude with an overview of the debate concerning whether they are morally or legally responsible for their actions. (shrink)

Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the discussion (...) by proposing the etiological stance as a comprehensive approach to identify modifiable causes of illness. (shrink)

This volume reflects the development and theoretical foundation of a new paradigm for critical thinking based on inquiry. The field of critical thinking, as manifested in the Informal Logic movement, developed primarily as a response to the inadequacies of formalism to represent actual argumentative practice and to provide useful argumentative skills to students. Because of this, the primary focus of the field has been on informal arguments rather than formal reasoning. Yet the formalist history of the field is still evident (...) in its emphasis, with respect to both theory and pedagogy, on the structure and evaluation of individual, de-contextualized arguments. It is our view that such a view of critical thinking is excessively narrow and limited, failing to provide an understanding of argumentation as largely a matter of comparative evaluation of a variety of contending positions and arguments with the goal of reaching a reasoned judgment on an issue. As a consequence, traditional critical thinking instruction is problematic in failing to provide the reasoning skills that students need in order to accomplish this goal. Instead, the goal of critical thinking instruction has been seen largely as a defensive one: of learning to not fall prey to invalid, inadequate, or fallacious arguments. (shrink)

The goal of research in social epidemiology is not simply conceptual clarification or theoretical understanding, but more importantly it is to contribute to, and enhance the health of populations (and so, too, the people who constitute those populations). Undoubtedly, understanding how various individual risk factors such as smoking and obesity affect the health of people does contribute to this goal. However, what is distinctive of much on-going work in social epidemiology is the view that analyses making use of individual-level variables (...) is not enough. In the spirit of Durkheim and Weber, S. Leonard Syme makes this point by writing that just “as bad water and food may be harmful to our health, unhealthful forces in our society may be detrimental to our capacity to make choices and to form opinions” conducive to health and well-being. Advocates of upstream (distal) causes of adverse health outcomes propose to identify the most important of these “unhealthful forces” as the fundamental causes of adverse health outcomes. However, without a clear, theoretically precise and well-grounded understanding of the characteristics of fundamental causes, there is little hope in applying the statistical tools of the health sciences to hypotheses about fundamental causes, their outcomes, and policies intended to enhance the health of populations. This paper begins the process of characterizing the social epidemiological concept of fundamental cause in a theoretically respectable and robust way. (shrink)

Nancy Cartwright begins her recent book, Hunting Causes and Using Them, by noting that while a few years ago real causal claims were in dispute, nowadays “causality is back, and with a vengeance.” In the case of the social sciences, Keith Morrison writes that “Social science asks ‘why?’. Detecting causality or its corollary—prediction—is the jewel in the crown of social science research.” With respect to the health sciences, Judea Pearl writes that the “research questions that motivate most studies in the (...) health sciences are causal in nature.” However, not all data used by people interested in making causal claims come from experiments that use random assignment to control and treatment groups. Indeed, much research in the social and health science depends on non-experimental, observational data. Thus, one of the most important problems in the social and health sciences concerns making warranted causal claims using non-experimental, observational data; viz., “Can observational data be used to make etiological inferences leading to warranted causal claims?” This paper examines one method of warranting causal claims that is especially widespread in epidemiology and the health sciences generally—the use of causal criteria. It is argued that cases of complex causation generally, and redundant causation—both causal overdetermination and causal preemption—specifically, undermine the use of such criteria to warrant causal claims. (shrink)

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 infer causality from regularity. Second, despite the fact (...) that causes be defined in terms of ‘difference-making’, this cannot fixes the causal metaphysics. Causality in epidemiology ought to be interpreted according to the epistemic theory. In this approach relations are deemed causal depending on the evidence and on the available methods. Indeed, evidence to establish causal claims requires difference-making considerations; furthermore, those definitions of cause reflect the ‘variational’ epistemology and methodology of epidemiology. (shrink)

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 (...) of causality that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification. (shrink)

The goal of this paper is two-fold: first, to emphasize causality in disease ontology and knowledge representation, presenting a general and cursory discussion of causality and causal chains; and second, to clarify and develop the River Flow Model of Diseases (RFM). The RFM is an ontological account of disease, representing the causal structure of pathology. It applies general knowledge of causality using the concept of causal chains. The river analogy of disease is explained, formal descriptions are offered, and the RFM (...) disease definition is refined by describing causal chains in terms of causal relations. The definition is updated to coincide with the actual RFM classes found in its upper-level ontology, YAMATO, which brings to light some challenges in developing both YAMATO and the RFM. The RFM is also discussed in relation to another ontological account of disease. Strategies are offered toward interoperability between these theories. (shrink)

This paper contrasts biomedical and epidemiological approaches to the diagnosis and treatment of disease, and uses Collingwoods principle of the relativity of causes to show how different approaches focus on different causal factors reflecting different interests. By distinguishing between the etiology of a disease and an epidemic, the paper argues that, from an epidemiological perspective, poverty is an important causal factor in the African AIDS epidemic and that emphasizing this should not be considered incompatible with recognizing the causal necessity of (...) HIV for the AIDS disease. (shrink)

In this paper I offer an anti-Humean critique to Williamson and Russo’s approach to medical mechanisms. I focus on one of the specific claims made by Williamson and Russo, namely the claim that micro-structural ‘mechanisms’ provide evidence for the stability across populations of causal relationships ascertained at the (macro-) level of (test) populations. This claim is grounded in the epistemic account of causality developed by Williamson, an account which—while not relying exclusively on mechanistic evidence for justifying causal judgements—appeals nevertheless to (...) mechanisms, and rejects their anti-Humean interpretation in terms of capacities, powers, potencies, etc. By using (and expanding on) Cartwright’s basic critique against Humean mechanisms, I suggest that, in order to move beyond the level of plausibility, Williamson and Russo’s position is in need of a clarification as to the occurent reading of the components, functioning and interferences of mechanisms. Relatedly, as concerns Williamson’s epistemic account of causation, I argue that this account is in need of a more straightforward answer as to what truth-makers its causal claims should have. (shrink)

Abstract In this paper I offer an anti-Humean interpretation of the causal interactions in somatic medicine. I focus on life-threatening pathological states and show how Nancy Cartwright’s capacities can offer a plausible epistemology for medical processes and the singular causal claims advanced in medical diagnoses. I argue that the capacities manifested in the emergence of symptoms and signs could be tracked down if healthy organisms are construed as nomological machines and suggest that the causal reasoning from current medical practice bears (...) a tacit adherence to anti-Humean assumptions. Content Type Journal Article Pages 1-28 DOI 10.1007/s12136-011-0141-1 Authors Stefan Dragulinescu, Drumul Taberei 20, Bucharest, Romania Journal Acta Analytica Online ISSN 1874-6349 Print ISSN 0353-5150. (shrink)

Epidemiologists’ discussions on causation are not always very enlightening with regard to the notion of ‘cause’ in epidemiology. Epidemiologists rightly work from a science-based approach to causation in epidemiology, but largely disagree about the matter. Disagreement may be partly due to confusion of the question of useful concepts for causal inference in epidemiological practice with the question of the metaphysical presuppositions of causal concepts used in epidemiology. In other words, epidemiologists seem to confuse the practical results of epidemiological research at (...) the population level with the metaphysical views about the reality of disease causation at the individual level in their writings on causation. (shrink)

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 breaking down the dominant (...) Human paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models: e.g. Rubin’s model, contingency tables, and multilevel analysis. It is also shown to be latent – yet fundamental – in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability. This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science. (shrink)

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.

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 (...) inferences (e.g., diagnoses and prognoses) are appropriate, rather than about the presence of some physical causal relation analogous to distance or gravitational attraction. It is shown that the epistemic theory has important consequences for medical practice, in particular with regard to evidence-based causal assessment. (shrink)

In this thesis, I give a metascientific account of causality in medicine. I begin with two historical cases of causal discovery. These are the discovery of the causation of Burkitt’s lymphoma by the Epstein-Barr virus, and of the various viral causes suggested for cervical cancer. These historical cases then support a philosophical discussion of causality in medicine. This begins with an introduction to the Russo- Williamson thesis (RWT), and discussion of a range of counter-arguments against it. Despite these, I argue (...) that the RWT is historically workable, given a small number of modifications. I then expand Russo and Williamson’s account. I first develop their suggestion that causal relationships in medicine require some kind of evidence of mechanism. I begin with a number of accounts of mechanisms and produce a range of consensus features of them. I then develop this consensus position by reference to the two historical case studies with an eye to their operational competence. In particular, I suggest that it is mechanistic models and their representations which we are concerned with in medicine, rather than the mechanism as it exists in the world. -/- I then employ these mechanistic models to give an account of the sorts of evidence used in formulating and evaluating causal claims. Again, I use the two human viral oncogenesis cases to give this account. I characterise and distinguish evidence of mechanism from evidence of difference-making, and relate this to mechanistic models. I then suggest the relationship between types of evidence presents us with a means of tackling the reference-class problem. This sets the scene for the final chapter. Here, I suggest the manner in which these two different classes of evidence become integrated is also reflected in the way that developing research programmes change as their associated causal claims develop. (shrink)

A large number of legal rules create an obligation to prevent, repair or otherwise mitigate damage to human health or the environment. Many of these rules require that a legally relevant causal relation between human behaviour and the damage at issue is established, and in the establishment of causal relations of this kind scientific information is often pressed into service. This thesis examines this specifically legal use of scientific information. It shows that many legally relevant causal relations cannot be established (...) in this way. It also shows that the legal strategy for dealing with epistemic difficulties by relaxing the standard of proof is of limited value in tackling this problem. Consequently, the legal rules focused upon are less efficient tools for combating damage to human health and the environment than their appearances suggest. Other legal means to achieve this aim should therefore be considered. The thesis begins by presenting a framework which can be used to solve some important problems with communication and the division of labour that arise when scientific information is used to answer legal questions. This framework recognizes both epistemological and ontological differences between law and science. The latter are differences between the kinds of entity which are relevant in distinct theoretical contexts; the former, by contrast, are differences between applicable standards of proof. In subsequent parts of the thesis this framework shapes the discussion of the question: To what extent can legally relevant causal relations, involving legally significant entities, be established through the application of scientific information about other, scientifically relevant entities and legal standards of proof. The thesis concludes with a discussion of some of the ways in which the legal regulation could, potentially, be adapted, so as to counteract damage to human health and the environment more efficiently. (shrink)