Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007) put forward the thesis that, at least in the health sciences, to establish the claim that C is a cause of E, one normally needs evidence of an underlying mechanism linking C and E as well as evidence that C makes a difference to E. This epistemological thesis poses a problem for most current analyses of causality which, in virtue of analysing causality in terms of just one of mechanisms or difference (...) making, cannot account for the need for the other kind of evidence. Weber (Int Stud Philos Sci 23(2):277–295, 2009) has suggested to the contrary that Giere’s probabilistic analysis of causality survives this criticism. In this paper, we look in detail at the case of medical imaging technology, which, we argue, supports the thesis of Russo and Williamson, and we respond to Weber’s suggestion, arguing that Giere’s account does not survive the criticism. (shrink)

The mechanistic and causal accounts of explanation are often conflated to yield a ‘causal-mechanical’ account. This paper prizes them apart and asks: if the mechanistic account is correct, how can causal explanations be explanatory? The answer to this question varies according to how causality itself is understood. It is argued that difference-making, mechanistic, dualist and inferentialist accounts of causality all struggle to yield explanatory causal explanations, but that an epistemic account of causality is more promising in this regard.

This paper addresses questions about how the levels of causality (generic and single-case causality) are related. One question is epistemological: can relationships at one level be evidence for relationships at the other level? We present three kinds of answer to this question, categorised according to whether inference is top-down, bottom-up, or the levels are independent. A second question is metaphysical: can relationships at one level be reduced to relationships at the other level? We present three kinds of answer to this (...) second question, categorised according to whether single-case relations are reduced to generic, generic relations are reduced to single-case, or the levels are independent. We then explore causal inference in autopsy. This is an interesting case study, we argue, because it refutes all three epistemologies and all three metaphysics. We close by sketching an account of causality that survives autopsy—the epistemic theory. (shrink)

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 considered here (...) offer only a rudimentary assessment of mechanistic studies, and some suggestions are made as to alternative ways to establish causality. (shrink)

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 (...) causal discovery. First, the thesis better explains the role of clinical studies in establishing causal claims. Second, it yields a better account of extrapolation. (shrink)

A particular tradition in medicine claims that a variety of evidence is helpful in determining whether an observed correlation is causal. In line with this tradition, it has been claimed that establishing a causal claim in medicine requires both probabilistic and mechanistic evidence. This claim has been put forward by Federica Russo and Jon Williamson. As a result, it is sometimes called the Russo–Williamson thesis. In support of this thesis, Russo and Williamson appeal to the practice of the International Agency (...) for Research on Cancer. However, this practice presents some problematic cases for the Russo–Williamson thesis. One response to such cases is to argue in favour of reforming these practices. In this paper, we propose an alternative response according to which such cases are in fact consistent with the Russo–Williamson thesis. This response requires maintaining that there is a role for mechanism-based extrapolation in the practice of the IARC. However, the response works only if this mechanism-based extrapolation is reliable, and some have argued against the reliability of mechanism-based extrapolation. Against this, we provide some reasons for believing that reliable mechanism-based extrapolation is going on in the practice of the IARC. The reasons are provided by appealing to the role of robustness analysis. (shrink)

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 (...) develop an analogous calibration norm for epistemic causality, argue that it is the *only* evidential norm required for epistemic causality, and show how an epistemic account of causality that incorporates this norm can be used to analyse objective causal relationships. (shrink)

In a recent article in this journal, Federica Russo and Jon Williamson argue that an analysis of causality in terms of probabilistic relationships does not do justice to the use of mechanistic evidence to support causal claims. I will present Ronald Giere's theory of probabilistic causation, and show that it can account for the use of mechanistic evidence (both in the health sciences—on which Russo and Williamson focus—and elsewhere). I also review some other probabilistic theories of causation (of Suppes, Eells, (...) and Humphreys) and show that they cannot account for the use of mechanistic evidence. I argue that these theories are also inferior to Giere's theory in other respects. (shrink)

The failure to recognize a correlation as spurious can lead people to adopt strategies to bring about a specific outcome that manipulate something other than a cause of the outcome. However, in a 2008 paper appearing in the journal Analysis, Bert Leuridan, Erik Weber and Maarten Van Dyck suggest that knowledge of spurious correlations can, at least sometimes, justify adopting a strategy aiming at bringing about some change. This claim is surprising and, if true, throws into question the claim of (...) Nancy Cartwright and others that knowledge of laws of association is insufficient for distinguishing effective and ineffective strategies. This paper examines the nature of spurious correlations and their value in crafting strategies for change. The conclusion of the paper is that while knowledge of a spurious correlation may have practical value, the value depends on either having knowledge of the causal structure underlying the correlation or it depends on the use of ‘causal criteria’. (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)

One of the defining features of the classical gene was its position. In molecular genetics, positions are defined instead as nucleotide numbers and there is no clear correspondence with its classical counterpart. However, the classical gene position did not simply disappear with the development of the molecular approach, but survived in the lab associated to different genetic practices. The survival of classical gene position would illustrate Waters’ view about the practical persistence of the genetic approach beyond reductionism and anti-reductionist claims. (...) We show instead that at the level of laboratory practices there are also reductive processes, operating through the rise and fall of different techniques. Molecular markers made the concept of classical gene position practically dispensable, leading us to rethink whether it had any causal role or was just a mere heuristic. (shrink)

Philosophy of epidemiology has recently emerged as a distinct branch of philosophy. The field will surely benefit from pluralism, reflected in the broad range of topics and perspectives in this special issue. Here, I argue that a healthy pluralistic field of philosophy of epidemiology has social responsibilities that require the field as a whole to engage actively with research on social determinants of health and health disparities. Practicing epidemiologists and the broader community of public health scientists have gradually acknowledged that (...) much of their attention ought to be paid to these, i.e. inequitable between-population health variations that largely reflect the world’s inequitable distribution of resources and social conditions. The paper illustrates how and why health disparities and social determinants of health, through no ill will, become de facto secondary concerns in Alex Broadbent’s field-defining Philosophy of Epidemiology, showing the ease with which these topics can be incidentally sidelined. As means for philosophy of epidemiology to meet its social responsibility obligations, I suggest philosophy of epidemiology expand its attention to two particular lines research. First, the paper discusses Geoffrey Rose’s concept of “causes of incidence”—causes of disparities between populations—and argues for the importance of engaging with these causes. Second, the paper argues for the value of engaging with Bruce Link and Jo Phelan’s “fundamental causes” model of how flexible social resources serve as buffers from harms, generating a plethora of shifting and locally-contingent health effects. (shrink)

In 2009, the UK House of Commons Science and Technology Committee conducted an ‘evidence check’ on homeopathy to evaluate evidence for its effectiveness. In common with the wider literature critical of homeopathy, the STC report seems to endorse many of the strong claims that are made about its implausibility. In contrast with the critical literature, however, the STC report explicitly does not place any weight on implausibility in its evaluation. I use the contrasting positions of the STC and the wider (...) critical literature to examine the ‘implausibility arguments’ against homeopathy and the place of such arguments within evidence-based medicine. I argue that the STC report undervalues its strong claims about the mechanistic plausibility of homeopathy because it relies on a misunderstanding about the role of mechanistic evidence within EBM. This is not a conclusion for a revision of the role mechanistic evidence plays within EBM, however. It is a conclusion about the inconsistency of the STC report’s position towards implausibility arguments, given the evidential claims they endorse and the atypical situation that homeopathy presents. It provides a further example of the general point that mechanistic reasoning should not be seen as providing categorically lower quality evidence. (shrink)

Establishing the effectiveness of medical treatments is one of the most important aspects of medical practice. Bradford Hill's viewpoints play an important role in inferring causality in medicine,...

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. (...) We use the pulmonary condition bronchiectasis as a source of examples of the importance of mechanistic reasoning to clinical practice. (shrink)

Kaplan and Craver :601–627, 2011) and Piccinini and Craver :283–311, 2011) argue that only mechanistic explanations of cognition are genuine causal explanations, because only evidence of mechanisms reveals the causal structure of cognition. I first argue that this claim is grounded in a commitment to the mechanistic account of causality, which cannot be endorsed by a defender of causal-nonmechanistic explanations. Then, I defend the epistemic theory of causality, which holds that causal explanations are not genuine to the extent that they (...) reveal mechanistic causal structure, but, rather, to the extent that they have evidential support and yield successful prediction, explanation, and control inferences. Finally, I enact an epistemic unification of causal explanation in cognitive science, according to which both mechanistic and nonmechanistic explanations of cognition can be genuine causal explanations. (shrink)

This article examines the relationship between the precautionary principle and the well-known Hill criteria of causation. Some have charged that the Hill criteria are anti-precautionary because the...

Measuring the effectiveness of medical interventions faces three epistemological challenges: the choice of good measuring instruments, the use of appropriate analytic measures, and the use of a reliable method of extrapolating measures from an experimental context to a more general context. In practice each of these challenges contributes to overestimating the effectiveness of medical interventions. These challenges suggest the need for corrective normative principles. The instruments employed in clinical research should measure patient-relevant and disease-specific parameters, and should not be sensitive (...) to parameters that are only indirectly relevant. Effectiveness always should be measured and reported in absolute terms (using measures such as 'absolute risk reduction'), and only sometimes should effectiveness also be measured and reported in relative terms (using measures such as 'relative risk reduction')-employment of relative measures promotes an informal fallacy akin to the base-rate fallacy, which can be exploited to exaggerate claims of effectiveness. Finally, extrapolating from research settings to clinical settings should more rigorously take into account possible ways in which the intervention in question can fail to be effective in a target population. (shrink)

Evidence hierarchies are widely used to assess evidence in systematic reviews of medical studies. I give several arguments against the use of evidence hierarchies. The problems with evidence hierarchies are numerous, and include methodological shortcomings, philosophical problems, and formal constraints. I argue that medical science should not employ evidence hierarchies, including even the latest and most-sophisticated of such hierarchies.

Anya Plutynski’s Explaining Cancer extends the insights of contemporary philosophy of biology to research on cancer and cancer treatment. Cancer is conceptualized as a complex process for which a pluralist theoretical approach is the most appropriate. This review essay explores implications for philosophy of science and cancer research.

Philosophy of Medicine has for a long time been preoccupied with analyzing the concepts of health, disease and illness. Relatively speaking, the concept of medicine itself has received very little attention. This paper is a contribution to the relatively neglected debate about the nature of medicine. Building on the work of Alex Broadbent (Broadbent, 2018a, b), Chadwin Harris (Harris, 2018) and Thaddeus Metz (Metz, 2018), in this paper I question the persuasiveness of Broadbent’s account of the “core business” of medicine, (...) The Inquiry Thesis, and propose an alternative: a revised version of The Curative Thesis, which I coin The Best Available Intervention Thesis. Crudely, this suggests that Medicine is the sustained and organised effort to determine and prescribe the best available treatment (curative or preventative) for patients. (shrink)

Social scientists often draw on a variety of evidence for their causal inferences. There is also a call to use a greater variety of evidence in social science research. This topical collection examines the philosophical foundations and implications of evidential diversity in the social sciences. It assesses the application of Evidential Pluralism in the context of the social sciences, especially its application to economics and political science. It also discusses the concept of causation in cognitive science and the implications of (...) evidential diversity for the social sciences. (shrink)

Evidential Pluralism maintains that in order to establish a causal claim one normally needs to establish the existence of an appropriate conditional correlation and the existence of an appropriate mechanism complex, so when assessing a causal claim one ought to consider both association studies and mechanistic studies. Hitherto, Evidential Pluralism has been applied to medicine, leading to the EBM+ programme, which recommends that evidence-based medicine should systematically evaluate mechanistic studies alongside clinical studies. This paper argues that Evidential Pluralism can also (...) be fruitfully applied to the social sciences. In particular, Evidential Pluralism provides (i) a new approach to evidence-based policy; (ii) an account of the evidential relationships in more theoretical research; and (iii) new philosophical motivation for mixed methods research. The application of Evidential Pluralism to the social sciences is also defended against two objections. (shrink)

In his seminal Inference to the Best Explanation, Peter Lipton adopted a causal view of explanation and a broadly Millian view of how causal knowledge is obtained. This made his account vulnerable to critics who charged that Inference to the Best Explanation is merely a dressed-up version of Mill’s methods, which in the critics’ view do the real inductive work. Lipton advanced two arguments to protect Inference to the Best Explanation against this line of criticism: the problem of multiple differences (...) and the problem of inferred differences. Lipton claimed that these two problems show Mill’s method of difference to be largely unworkable unless it is embedded in an explanationist framework. Here I consider both arguments as well as the best Millian defense against them. Since the existing Millian defense is only partially successful, I will develop a new and improved account. As an integral part of the argument, I show that my solutions to the problems of multiple and inferred differences offer new insight into Lipton’s main case study: Ignaz Semmelweis’s discovery of the cause of childbed fever. I conclude that the method of difference can overcome Lipton’s challenges outside an explanationist framework. (shrink)

Semmelweis’s discovery of the cause of puerperal fever around the middle of the 19th century counts among the paradigm cases of scientific discovery. For several decades, philosophers of science have used the episode to illustrate, appraise and compare views of proper scientific methodology.Here I argue that the episode can be profitably reexamined in light of two cognate notions: causal reasoning and mechanisms. Semmelweis used several causal reasoning strategies both to support his own and to reject competing hypotheses. However, these strategies (...) have gone unappreciated in the existing literature. I show that a causal reasoning approach makes sense of the multitude of tables in Semmelweis’s main text, which in later editions were often abridged because they appeared redundant.Moreover, the existing literature tends to focus on Semmelweis’s clinical intervention and on the extent to which it alone confirms his theoretical conclusions. This neglects Semmelweis’s efforts to show by animal experiments that his clinical results are in agreement with a demonstrable mechanism of puerperal fever pathogenesis. I argue that the full evidential force of Semmelweis’s argument can only be appreciated if both his clinical and his laboratory investigations are taken into account. (shrink)

According to an influential epistemological tradition, science explains phenomena on the basis of laws, but the last two decades have witnessed a neo-mechanistic movement that emphasizes the fundamental role of mechanism-based explanations in science, which have the virtue of opening the “black box” of correlations and of providing a genuine understanding of the phenomena. Mechanisms enrich the empirical content of a theory by introducing a new set of variables, helping us to make causal inferences that are not possible on the (...) basis of macro-level correlations. However, the appeal to mechanisms has also a methodological price. They are vulnerable to interference effects; they also face underdetermination problems, because the available evidence often allows different interpretations of the underlying structure of a correlation; they are strongly context-dependent and their individuation as causal patterns can be controversial; they present specific testability problems; finally, mechanism-based extrapolations can be misleading due to the local character of mechanisms. At any rate, the study of mechanisms is an indispensable part of the human sciences, and the problems that they raise can be controlled by quantitative and qualitative methods, and an epistemologically informed exercise of critical thinking. (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)

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 intervene upon.

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 evidence of difference making over evidence of mechanisms and are flawed because the two sorts of evidence are required and they should be treated on a par. An alternative approach gives primacy to evidence of mechanism over evidence of difference making. In this paper, we argue that this alternative approach is equally flawed, again because both sorts of evidence need to be treated on a par. As an illustration of this parity, we explain how scientists working in the ‘EnviroGenomarkers’ project constantly make use of the two evidential components in a dynamic and intertwined way. We argue that such an interplay is needed not only for causal assessment but also for policy purposes. (shrink)

Evidential pluralists, like Federica Russo and Jon Williamson, argue that causal claims should be corroborated by establishing both the existence of a suitable correlation and a suitable mechanism complex. At first glance, this fits well with mixed method research in the social sciences, which often involves a pluralist combination of statistical and mechanistic evidence. However, statistical evidence concerns a population of cases, while mechanistic evidence is found in individual case studies. How should researchers combine such general statistical evidence and specific (...) mechanistic evidence? This article discusses a very recent answer to this question, ‘multi-method large-N qualitative analysis’ or multi-method LNQA, popular in political science and international relations studies of rare events like democratic transitions and cease-fire agreements. Multi-method LNQA combines a comprehensive study of all relevant event cases with statistical analysis, in an attempt to solve the issues of generalization faced by other types of qualitative research, such as selection bias and lack of representativeness. I will argue that the kind of general causal claim that multi-method LNQA is after, however, is crucially different from the average treatment effect found in statistical analysis and can in fact only be supported with mechanistic evidence. I conclude from this that mixed method research, and thereby evidential pluralism, may be inappropriate in this context. (shrink)

Evidential pluralism has been used to justify mixed-method research in political science. The combination of methodologies within case study analysis, however, has not received as much attention. This article applies the theory of evidential pluralism to causal inference in the case study method process tracing. I argue that different methodologies for process tracing commit to distinct fundamental theories of causation. I show that, problematically, one methodology may not recognize as genuine knowledge the fundamental claims of the other. By evaluating the (...) epistemic reliability of these fundamental claims, we can find a way out of such conflicts and rescue pluralism. (shrink)

The rapid, recent emergence of new medical knowledge models has engendered a dizzying number of new medical initiatives, programs and approaches. Fields such as evidence-based medicine and translational medicine all promise a renewed relationship between knowledge and medicine. The question for philosophy and other fields has been whether these new models actually achieve their promises to bring about better kinds of medical knowledge—a question that compels scholars to analyze each model’s epistemic claims. Yet, these analyses may miss critical components that (...) explain how these models actually work and function. Using the case of translational medicine, this paper suggests that analyses which treat these models as a primarily epistemic interventions miss the way that new approaches are increasingly shaped by specific financial and commercial agendas. Ultimately, social epistemological analyses that are attentive to market forces are required to make sense of emerging bioscientific research models, which are increasingly tethered to or a manifestation of increasingly financialized models of science research and innovation. (shrink)

All univocal analyses of causation face counterexamples. An attractive response to this situation is to become a pluralist about causal relationships. "Causal pluralism" is itself, however, a pluralistic notion. In this article, I argue in favor of pluralism about concepts of cause in the social sciences. The article will show that evidence for, inference from, and the purpose of causal claims are very closely linked. Key Words: causation • pluralism • evidence • methodology.

I present an alternative account of causation in the biomedical and social sciences according to which the meaning of causal claims is given by their inferential relations to other claims. Specifically, I will argue that causal claims are inferentially related to certain evidential claims as well as claims about explanation, prediction, intervention and responsibility. I explain in some detail what it means for a claim to be inferentially related to another and finally derive some implication of the proposed account for (...) the epistemology, semantics and metaphysics of causation. (shrink)

Two approaches to evidential reasoning compete in the biomedical and social sciences: the experimental and the pragmatist. Whereas experimentalism has received considerable philosophical analysis and support since the times of Bacon and Mill, pragmatism about evidence has been neither articulated nor defended. The overall aim is to fill this gap and develop a theory that articulates the latter. The main ideas of the theory will be illustrated and supported by a case study on the smoking/lung cancer controversy in the 1950s.

Despite the miraculous progress of science—it’s practitioners continue to run into mistakes, either discrediting research unduly or making leaps of causal inference where none are warranted. In this we isolate two of the reasons for such behavior involving the misplaced understanding of the role of mechanisms and mechanistic knowledge in the establishment of cause-effect relationships. We differentiate causal knowledge into causes, effects, mechanisms, cause-effect relationships, and causal stories. Failing to understand the role of mechanisms in this picture, including their absence (...) of knowledge or incorrect specification, leads to errors of wrongly excluding cause-effect relationships or wrongly inferring their existence. We highlight the primary of causality over mechanistic knowledge and causal stories in scientific reasoning. (shrink)

In this article, we discuss the issue of context-dependence of mechanism-based explanation in the social sciences. The different ways in which the context-dependence and context-independence of mechanism-based explanation have been understood in the social sciences are often motivated by different and apparently incompatible understandings of what explanatory mechanisms are. Instead, we suggest that the different varieties of context-dependence are best seen as corresponding to different research goals. Rather than conflicting with one another, these goals are complementary to each other and (...) therefore pave the way to a methodologically more cooperative approach to mechanism-based explanation in the social sciences. (shrink)

While loneliness has been linked to various mental and physical health problems, the sense in which loneliness is a cause of these conditions has so far attracted little philosophical attention. This paper aims to fill this gap by analyzing research on health effects of loneliness and therapeutic interventions through current approaches to causality. To deal with the problem of causality between psychological, social, and biological variables, the paper endorses a biopsychosocial model of health and disease. I will investigate how three (...) main approaches to causality used in psychiatry and public health apply to loneliness: interventionism, mechanisms, and dispositional theories. Interventionism can specify whether loneliness causes specific effects, or whether a treatment works, incorporating results from randomized controlled trials. Mechanisms help explain how loneliness brings about negative health effects, spelling out psychological processes involved in lonely social cognition. Dispositional approaches help stress particular features of loneliness connected to negative social interactions, such as defensiveness. I will conclude by showing that previous research alongside emerging approaches to health effects of loneliness lend themselves to analysis in terms of the causal models under discussion. (shrink)

This article addresses the contributions of the literature on the new mechanistic philosophy of science for the scientific practice of model building in ecology. This is reflected in a one-to-one interdisciplinary collaboration between an ecologist and a philosopher of science during science-in-the-making. We argue that the identification, reconstruction and understanding of mechanisms is context-sensitive, and for this case study mechanistic modeling did not present a normative role but a heuristic one. We expect our study to provides useful epistemic tools for (...) the improvement of empirically-riven work in the debates about mechanistic explanation of ecological phenomena. (shrink)

Amalgamating evidence from heterogeneous sources and across levels of inquiry is becoming increasingly important in many pure and applied sciences. This special issue provides a forum for researchers from diverse scientific and philosophical perspectives to discuss evidence amalgamation, its methodologies, its history, its pitfalls, and its potential. We situate the contributions therein within six themes from the broad literature on this subject: the variety-of-evidence thesis, the philosophy of meta-analysis, the role of robustness/sensitivity analysis for evidence amalgamation, its bearing on questions (...) of extrapolation and external validity of experiments, its connection with theory development, and its interface with causal inference, especially regarding causal theories of cancer. (shrink)

It is argued that in deterministic contexts evidence for causal relations states whether a boundary condition makes a difference or not to a phenomenon. In order to substantiate the analysis, I show that this difference/indifference making is the basic type of evidence required for eliminative induction in the tradition of Francis Bacon and John Stuart Mill. To this purpose, an account of eliminative induction is proposed with two distinguishing features: it includes a method to establish the causal irrelevance of boundary (...) conditions by means of indifference making, which is called strict method of agreement, and it introduces the notion of a background against which causal statements are evaluated. Causal statements thus become three-place-relations postulating the relevance or irrelevance of a circumstance C to the examined phenomenon P with respect to a background B of further conditions. To underline the importance of evidence in terms of difference/indifference making, I sketch two areas, in which eliminative induction is extensively used in natural and engineering sciences. One concerns exploratory experiments, the other engineering design methods. Given that a method is discussed that has been used for centuries, I make no claims to novelty in this paper, but hope that the combined discussion of several topics that are still somewhat underrepresented in the philosophy of science literature is of some merit. (shrink)

Evidence-based medicine (EBM) has long deemphasized mechanistic reasoning and pathophysiological rationale in assessing the effectiveness of interventions. The EBM+ movement has challenged this stance, arguing that evidence of mechanisms and comparative studies should both be seen as necessary and complementary. Advocates of EBM+ provide a combination of theoretical arguments and examples of mechanistic reasoning in medical research. However, EBM+ proponents have not provided recent examples of how downplaying mechanistic reasoning resulted in worse medical results than would have occurred otherwise. Such (...) examples are necessary to make the case that EBM+ responds to a problem in clinical practice that urgently demands a solution. In light of this, we examine the failed rollout of efavirenz as a first-line HIV treatment in Zimbabwe as evidence of the importance of mechanistic reasoning in improving clinical practice and public health policy decisions. We suggest that this case is analogous to examples commonly given to support EBM. (shrink)

The paper considers the legal tools that have been developed in German pharmaceutical regulation as a result of the precautionary attitude inaugurated by the Contergan decision. These tools are the notion of “well-founded suspicion”, which attenuates the requirements for safety intervention by relaxing the requirement of a proved causal connection between danger and source, and the introduction of the reversal of proof burden in liability norms. The paper focuses on the first and proposes seeing the precautionary principle as an instance (...) of the requirement that one should maximise expected utility. In order to maximise expected utility certain probabilities are required and it is argued that objective Bayesianism offers the most plausible means to determine the optimal decision in cases where evidence supports diverging choices. (shrink)

The problem of collecting, analyzing and evaluating evidence on adverse drug reactions (ADRs) is an example of the more general class of epistemological problems related to scientific inference and prediction, as well as a central problem of the health-care practice. Philosophical discussions have critically analysed the methodological pitfalls and epistemological implications of evidence assessment in medicine, however they have mainly focused on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special (...) attention to the privileged role assigned to randomized controlled trials in Evidence Based Medicine. Regardless of whether the RCT’s privilege holds for efficacy assessment, it is nevertheless important to make a distinction between causal inference of intended and unintended effects, in that the unknowns at stake are heterogonous in the two contexts. This point has been emphasized by epidemiologists in the last decade. Their main focus is methodological, and regards the fact that bias and confounding do not affect studies on intended and unintended effects in the same way. However, deeper concerns ground the intuition for such a distinction; these are related to the constraints which we impose on evidence and their epistemological justification. My thesis is that such constraints ought to be understood to be different in the case of evidence for risk vs. benefit assessment. I present the recent debate on the causal association between acetaminophen and asthma in order to illustrate the point at issue. (shrink)