Philosophers of science and medicine now aspire to provide useful, socially relevant accounts of mechanism. Existing accounts have forged the path by attending to mechanisms in historical context, scientific practice, the special sciences, and policy. Yet, their primary focus has been on more proximate issues related to therapeutic effectiveness. To take the next step toward social relevance, we must investigate the challenges facing researchers, clinicians, and policy makers involving values and social context. Accordingly, we learn valuable lessons about the connections (...) between mechanistic processes and more fundamental reasons for medical interventions, particularly moral, ethical, religious, and political concerns about health, agency, and power. This paper uses debates over the controversial morning-after pill to gain insight into the deeper reasons for the production and use of mechanistic knowledge throughout biomedical research, clinical practice, and governmental regulation. To practice socially relevant philosophy of science, I argue that we need to account for mechanistic knowledge beyond immediate effectiveness, such as how it can also provide moral guidance, aid ethical categorization in the clinic, and function as a political instrument. Such insights have implications for medical epistemology, including the value-laden dimensions of mechanistic reasoning and the “epistemic friction” of values. Furthermore, there are broader impacts for teaching research ethics and understanding the role of science advisors as political advocates. (shrink)

In current philosophical discussions on evidence in the medical sciences, epidemiology has been used to exemplify a specific version of evidential pluralism. According to this view, known as the Russo–Williamson Thesis, evidence of both difference-making and mechanisms is produced to make causal claims in the health sciences. In this paper, I present an analysis of data and evidence in epidemiological practice, with a special focus on research on the exposome, and I cast doubt on the extent to which evidential pluralism (...) holds in this case. I start by focusing on the claim that molecular data allows for the production of mechanistic evidence. On the basis of a close look at the ways in which molecular data is used in exposome research, I caution against interpretations in terms of mechanistic evidence. Secondly, I expand my critical remarks on the thesis by addressing the conditions under which data is categorised as evidence in exposome research. I argue that these show that the classification of a dataset as a type of evidence is dependent on the ways in which the data is used. This is in contrast with the approach of evidential pluralism, where evidence is classified in different types on the basis of its intrinsic properties. Finally, I come back to what I consider the core of the thesis and suggest that the epidemiological research analysed in the paper indicates different interpretations of evidential pluralism and its applicability in the health sciences. (shrink)

My doctoral project is a study of epistemological and ethical issues in Evidence-Based Medicine, a movement in medicine which emphasizes the use of randomized controlled trials. Much of the research on EBM suggests that, for a large part of the movement's history, EBM considered expertise, mechanisms, and values to be forces contrary to its goals and has sought to remove them, both from medical research and from the clinical encounter. I argue, however, that expertise, mechanisms and values have important epistemological (...) and ethical roles to play and can be incorporated into the current EBM movement. (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)

Hierarchies of evidence are an important and influential tool for appraising evidence in medicine. In recent years, hierarchies have been formally adopted by organizations including the Cochrane Collaboration [1], NICE [2,3], the WHO [4], the US Preventive Services Task Force [5], and the Australian NHMRC [6,7]. The development of such hierarchies has been regarded as a central part of Evidence-Based Medicine, a movement within healthcare which prioritises the use of epidemiological evidence such as that provided by Randomised Controlled Trials. Philosophical (...) work on the methodology of medicine has so far mostly focused on claims about the superiority of RCTs, and hence has largely neglected the questions of what hierarchies are, what assumptions they require, and how they affect clinical practice. This thesis shows that there is great variation in the hierarchies defended and in the interpretations they are, and can be, given. The interpretative assumptions made in using hierarchies are crucial to the content and defensibility of the underlying philosophical commitments concerning evidence and medical practice. Once this variation is been identified, it becomes clear that the little philosophical work that has been done so far affects only some hierarchies, under some interpretations. Modest interpretations offered by La Caze [11], conditional hierarchies like GRADE [12-14], and heuristic approaches such as that defended by Howick et al. [15,16] all survive previous philosophical criticism. This thesis extends previous criticisms by arguing that modest interpretations are so weak as to be unhelpful for clinical practice; that GRADE and similar conditional models omit clinically relevant information, such as information about variation in treatments’ effects and the causes of different responses to therapy; and that heuristic approaches lack the necessary empirical support. The conclusion is that hierarchies in general embed untenable philosophical assumptions: principally that information about average treatment effects backed by high-quality evidence can justify strong recommendations, and that the impact of evidence from individual studies can and should be appraised in isolation. Hierarchies are a poor basis for the application of evidence in clinical practice. The Evidence-Based Medicine movement should move beyond them and explore alternative tools for appraising the overall evidence for therapeutic claims. (shrink)

Harms of medical interventions are systematically underestimated in clinical research. Numerous factors—conceptual, methodological, and social—contribute to this underestimation. I articulate the depth of such underestimation by describing these factors at the various stages of clinical research. Before any evidence is gathered, the ways harms are operationalized in clinical research contributes to their underestimation. Medical interventions are first tested in phase 1 ‘first in human’ trials, but evidence from these trials is rarely published, despite the fact that such trials provide the (...) foundation for assessing the harm profile of medical interventions. If a medical intervention is deemed safe in a phase 1 trial, it is tested in larger phase 2 and 3 clinical trials. One way to think about the problem of underestimating harms is in terms of the statistical ‘power’ of a clinical trial—the ability of a trial to detect a difference of a certain effect size between the experimental group and the control group. Power is normally thought to be pertinent to detecting benefits of medical interventions. It is important, though, to distinguish between the ability of a trial to detect benefits and the ability of a trial to detect harms. I refer to the former as power-B and the latter as power-H. I identify several factors that maximize power-B by sacrificing powerH in phase 3 clinical trials. If a medical intervention is approved for general use, it is evaluated by phase 4 post-market surveillance. Phase 4 surveillance of harms further contributes to underestimating the harm profile of medical interventions. At every stage of clinical research the hunt for harms is shrouded in secrecy, which further contributes to the underestimation of the harm profiles of medical interventions. (shrink)

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)

Since its introduction just over two decades ago, evidence-based medicine (EBM) has come to dominate medical practice, teaching, and policy. There are a growing number of textbooks, journals, and websites dedicated to EBM research, teaching, and evidence dissemination. EBM was most recently defined as a method that integrates best research evidence with clinical expertise and patient values and circumstances in the treatment of patients. There have been debates throughout the early 21st century about what counts as good research evidence between (...) EBM proponents and philosophical critics and even within the EBM community itself. Similar controversy arises about the relative worth of patient values and clinical expertise (and how these can be integrated). EBM has also evolved in ways that have come under scrutiny. Specifically, policymakers have used EBM research methodology to increase the relative importance of clinical guidelines that some clinicians have argued are tyrannical. Philosophers have addressed all of these controversies, and with very few exceptions have been critical of EBM. In addition most philosophical attention has been on the epistemic role of Randomization and evidence hierarchies, with relatively little attention being paid to the role of Diagnosis, expertise, patient values, and Systematic Reviews within EBM. (shrink)

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 research. Recent research in causality has (...) examined Ned Hall’s distinction between two concepts of causality: production and dependence. In another recent paper, Illari examined the relatively under-explored production approach to causality, arguing that at least one job of an account of causal production is to illuminate our inferential practices concerning causal linking. Illari argued that an informational account solves existing problems with traditional accounts. This paper follows up this previous work by investigating the nature of the causal links established in biomarkers research. We argue that traditional accounts of productive causality are unable to provide a sensible account of the nature of the causal link in biomarkers research, while an informational account is very promising. (shrink)

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 mechanisms alongside evidence of correlation in (...) explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM. (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.

There have recently been novel applications of medical systematic review guidelines to economic policy interventions which contain controversial methodological assumptions that require further scrutiny. A landmark 2017 Cochrane review of unconditional cash transfer (UCT) studies, based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE), exemplifies both the possibilities and limitations of applying medical systematic review guidelines to UCT and universal basic income (UBI) studies. Recognizing the need to upgrade GRADE to incorporate the differences between medical and policy interventions, (...) the GRADE Public Health Project Group (PHPG) was convened to enumerate and address these methodological challenges. However, in light of our analysis of additional methodological challenges that arise for UCT and UBI studies, we argue that the adaptation of medical systematic review guidelines to economic methodology is far from straightforward and is in fact more challenging than claimed by the PHPG. (shrink)

This paper aims to clarify the nature of understanding in medicine. The first part describes in more detail what it means to understand something and links a type of understanding (i.e., objectual understanding) to explanations. The second part proceeds to investigate what objectual understanding of a disease (i.e., biomedical understanding) requires by considering the case of scurvy from the history of medicine. The main hypothesis is that grasping a mechanistic explanation of a condition is necessary for a biomedical understanding of (...) that condition. The third part of the paper argues that biomedical understanding is necessary, but not sufficient for understanding in a clinical context (i.e., clinical understanding). The hypothesis is that clinical understanding combines biomedical understanding of a _disease_ or pathological condition with understanding _illness,_ which involves some degree of personal understanding of the patient. It is argued that, in many cases, clinical understanding necessitates adopting a particular second-personal stance and using cognitive resources _in addition_ to those involved in biomedical understanding. (shrink)

The current strategy of searching for an effective treatment for COVID-19 relies mainly on repurposing existing therapies developed to target other diseases. Conflicting results have emerged in regard to the efficacy of several tested compounds but later results were negative. The number of conducted and ongoing trials and the urgent need for a treatment pose the risk that false-positive results will be incorrectly interpreted as evidence for treatments’ efficacy and a ground for drug approval. Our purpose is twofold. First, we (...) show that the number of drug-repurposing trials can explain the false-positive results. Second, we assess the evidence for treatments’ efficacy from the perspective of evidential pluralism and argue that considering mechanistic evidence is particularly needed in cases when the evidence from clinical trials is conflicting or of low quality. Our analysis is an application of the program of Evidence Based Medicine Plus to the drug repurposing trials for COVID. Our study shows that if decision-makers applied EBM+, authorizing the use of ineffective treatments would be less likely. We analyze the example of trials assessing the efficacy of hydroxychloroquine as a treatment for COVID-19 and mechanistic evidence in favor of and against its therapeutic power to draw a lesson for decision-makers and drug agencies on how excessive hypothesis testing can lead to spurious findings and how studying negative mechanistic evidence can be helpful in discriminating genuine from spurious results. (shrink)

There are two competing views regarding the role of mechanistic knowledge in inferences about the effectiveness of interventions. One view holds that inferences about the effectiveness of interventions should be based only on data from population-level studies (often statistical evidence from randomised trials). The other view holds that such inferences must be based in part on mechanistic evidence. The competing views are local principles of inference, the plausibility of which can be assessed by a more general normative principle of inference. (...) Bayesianism tells us to base inferences on both the ‘likelihood’ and the ‘prior’. The likelihood represents statistical evidence. One influence on the prior probability of a hypothesis like ‘d causes x’ is mechanistic knowledge of how d causes x. Thus, reasoning about such inferences by appealing to both statistical and mechanistic evidence is vindicated by our best general theory of inference. The primary contribution of this paper is to assess the merits and weaknesses of the arguments on both sides of the debate, using the Bayesian framework. This analysis lends support to those who argue that we should base our causal inferences about interventions in part on mechanistic evidence. (shrink)

This thesis analyses the use of 'Evidence-Based' methodologies of evidence assessment and intervention and policy design from medicine, and their use in sport and exercise science. It argues that problems exist with the application of Evidence-Based methodologies in sports science, meaning that the quality of evidence used to inform decision-making is lower than is often assumed. This thesis also offers realistic solutions to these problems, broadly arguing for the importance of taking evidence from mechanistic studies seriously, in addition to evidence (...) from RCTs. (shrink)

This paper defends the need for evidential diversity and the mix of methods that that can in train require. The focus is on causal claims, especially ‘singular’ claims about the effects of causes in a specific setting—either what will happen or what has happened. I do so by offering a template that categorises kinds of evidence that can support these claims. The catalogue is generated by considering what needs to happen for a causal process to carry through from putative cause (...) at the start to the targeted effect at the end. The usual call for mixed methods focusses on a single overall claim and argues that we increase certainty by the use of different methods with compensating strengths and weaknesses. My proposals instead focus on the evidence that supports the great many subsidiary claims that must hold if the overall one is to be true. As is typical for singular causal claims, the mix of methods that will generally be required to collect the kinds of evidence I urge will usually have little claim to the kind of rigour that is now widely demanded in evidencing causal claims, especially those for policy/treatment effectiveness. So I begin with an exploration of what seems to be intended by ‘rigour’ in such discussions, since it is seldom made clear just what makes the favoured methods especially rigorous. I then argue that the emphasis on rigour can be counterproductive. Rigour is often the enemy of evidential diversity, and evidential diversity—lots of it—can make for big improvements in the reliability of singular causal predictions and post hoc evaluations. I illustrate with the paragon of rigour for causal claims, randomised controlled trials (RCTs), rehearsing at some length what they can and cannot do to make it easier to assess the importance of rigour in warranting singular causal claims. (shrink)

Epidemiological explanation often has a “black box” character, meaning the intermediate steps between cause and effect are unknown. Filling in black boxes is thought to improve causal inferences by making them intelligible. I argue that adding information about intermediate causes to a black box explanation is an unreliable guide to pragmatic intelligibility because it may mislead us about the stability of a cause. I diagnose a problem that I call wishful intelligibility, which occurs when scientists misjudge the limitations of certain (...) features of an explanation. Wishful intelligibility gives us a new reason to prefer black box explanations in some contexts. (shrink)

In this talk I present the main results from Anta (2021), namely, that the theoretical division between Boltzmannian and Gibbsian statistical mechanics should be understood as a separation in the epistemic capabilities of this physical discipline. In particular, while from the Boltzmannian framework one can generate powerful explanations of thermal processes by appealing to their microdynamics, from the Gibbsian framework one can predict observable values in a computationally effective way. Finally, I argue that this statistical mechanical schism contradicts the Hempelian (...) (1958) thesis that the predictive power of a scientific theory is directly proportional to its explanatory potential, and vice versa. (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)

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)

Following an analysis of the state of investigations and clinical outcomes in the Alzheimer's research field, I argue that the widely-accepted 'amyloid cascade' mechanistic explanation of Alzheimer's disease appears to be fundamentally incomplete. In this context, I propose that a framework termed 'principled mechanism' (PM) can help with remedying this problem. First, using a series of five 'tests', PM systematically compares different components of a given mechanistic explanation against a paradigmatic set of criteria, and hints at various ways of making (...) the mechanistic explanation more 'complete'. These steps will be demonstrated using the amyloid explanation, and its missing or problematic mechanistic elements will be highlighted. Second, PM makes an appeal for the discovery and application of 'biological principles' (BPs), which approximate ceteris paribus laws and are operative at the level of a biological cell. As such, although thermodynamic, evolutionary, ecological and other laws or principles from chemistry and the broader life sciences could inform them, BPs should be considered ontologically unique. BPs could augment different facets of the mechanistic explanation but also allow further independent nomological explanation of the phenomenon. Whilst this overall strategy can be complementary to certain 'New Mechanist' approaches, an important distinction of the PM framework is its equal attention to the explanatory utility of biological principles. Lastly, I detail two hypothetical BPs, and show how they could each inform and improve the potentially incomplete mechanistic aspects of the amyloid explanation and also how they could provide independent explanations of the cellular features associated with Alzheimer's disease. (shrink)

An adequate understanding of the ubiquitous practice of mechanistic explanation requires an account of what Craver termed “constitutive relevance.” Entities or activities are constitutively relevant to a phenomenon when they are parts of the mechanism responsible for that phenomenon. Craver’s mutual manipulability account extended Woodward’s account of manipulationist counterfactuals to analyze how interlevel experiments establish constitutive relevance. Critics of MM argue that applying Woodward’s account to this philosophical problem conflates causation and constitution, thus rendering the account incoherent. These criticisms, we (...) argue, arise from failing to distinguish the semantic, epistemic, and metaphysical aspects of the problem of constitutive relevance. In distinguishing these aspects of the problem and responding to these critics accordingly, we amend MM into a refined epistemic criterion, the “matched interlevel experiments” account. Further, we explain how this epistemological thesis is grounded in the plausible metaphysical thesis that constitutive relevance is causal betweenness. (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)

It is a commonly expressed sentiment that the science and philosophy of well-being would do well to learn from each other. Typically such calls identify mistakes and bad practices on both sides that would be remedied if scientists picked the right bit of philosophy and philosophers picked the right bit of science. We argue that the differences between philosophers and scientists thinking about well-being are more difficult to reconcile than such calls suggest, and that pluralism is central to this task. (...) Pluralism is a stance that explicitly drives towards accommodating and nurturing the richness and diversity of well-being, both as a concept and as an object of inquiry. We show that well-being science manifests a contingent pluralism at the level of methodology, whereas philosophy of well-being has largely rejected pluralism at the conceptual level. Recently, things have begun to change. Within philosophy, conceptual monism is under attack. But so is methodological pluralism within science. We welcome the first development, and bemoan the second. We argue that a joined-up philosophy and science of well-being should recognise the virtues of both conceptual and methodological pluralism. Philosophers should embrace the methodological justification of pluralism that can be found in the well-being sciences, and scientists should embrace the conceptual reasons to be pluralist that can be found in philosophical debate. (shrink)

It has recently been argued that successful evidence-based policy should rely on two kinds of evidence: statistical and mechanistic. The former is held to be evidence that a policy brings about the desired outcome, and the latter concerns how it does so. Although agreeing with the spirit of this proposal, we argue that the underlying conception of mechanistic evidence as evidence that is different in kind from correlational, difference-making or statistical evidence, does not correctly capture the role that information about (...) mechanisms should play in evidence-based policy. We offer an alternative account of mechanistic evidence as information concerning the causal pathway connecting the policy intervention to its outcome. Not only can this be analyzed as evidence of difference-making, it is also to be found at any level and is obtainable by a broad range of methods, both experimental and observational. Using behavioral policy as an illustration, we draw the implications of this revised understanding of mechanistic evidence for debates concerning policy extrapolation, evidence hierarchies, and evidence integration. (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)

:Proponents of behavioural policies seek to justify them as ‘evidence-based’. Yet they typically fail to show through which mechanisms these policies operate. This paper shows – at the hand of examples from economics and psychology – that without sufficient mechanistic evidence, one often cannot determine whether a given policy in its target environment will be effective, robust, persistent or welfare-improving. Because these properties are important for justification, policies that lack sufficient support from mechanistic evidence should not be called ‘evidence-based’.

The Russo Williamson thesis (RWT) states that a causal claim can be established only if it can be established that there is a difference-making relationship between the cause and the effect, and that there is a mechanism linking the cause and the effect that is responsible for such a difference-making relationship (Russo & Williamson, 2007). The applicability of Russo and Williamson’s idea was hugely debated in relation to biomedical research, and recently it has been applied to the social sciences (Shan (...) & Williamson, 2021). While many philosophers and social scientists have advocated the use of different kinds of evidence for causal discoveries, others have criticised this approach. With this paper, I aim to defend RWT from criticisms and to show its importance in the social sciences. The paper is structured as follows. After a brief introduction, in Sect. 2, I will summarise RWT, and in Sect. 3 I will describe how this approach can be applied to the social sciences. In Sect. 4, I will reconstruct two main criticisms of this thesis proposed in the philosophy of the social sciences literature: namely (i) RWT is not used in the social sciences, (ii) RWT does not work. For each criticism I will provide a defence of RWT. My defence will be based on two general considerations: (i) RWT appears perfectly in line with the research methods used in the social sciences and (ii) RWT can be applied successfully to establish causal claims. In Sect. 5, moreover, I will examine the causal accounts that have motivated such criticisms and I will argue that they should be rejected to endorse RWT and a causal account able to accommodate the current use of mechanistic and difference-making evidence in the social sciences. Section 6 will conclude with a note on the relevance of RWT in both its descriptive and normative form. (shrink)

The thesis consists of an introduction and two papers. In the introduction a brief historical survey of empirical investigations into the effectiveness of medicinal interventions is given. Also, the main ideas of the EBM movement are presented. Both included papers can be viewed as investigations into the reasonableness of EBM and its hierarchies of evidence. Paper I: Typically, in a clinical trial patients with specified symptoms are given either of two or more predetermined treatments. Health endpoints in these groups are (...) then compared using statistical methods. Concerns have been raised, not least from adherents of so-called alternative medicine, that clinical trials do not offer reliable evidence for some types of treatment, in particular for highly individualized treatments, for example traditional homeopathy. It is argued that such concerns are unfounded. There are two minimal conditions related to the nature of the treatments that must be fulfilled for evaluability in a clinical trial, namely the proper distinction of the two treatment groups and the elimination of confounding variables or variations. These are delineated, and a few misunderstandings are corrected. It is concluded that the conditions do not preclude the testing of alternative medicine, whether individualized or not. Paper II: Traditionally, mechanistic reasoning has been assigned a negligible role in standard EBM literature, although some recent authors have argued for an upgrading. Even so, mechanistic reasoning that has received attention has almost exclusively been positive -- both in an epistemic sense of claiming that there is a mechanistic chain and in a health-related sense of there being claimed benefits for the patient. Negative mechanistic reasoning has been neglected, both in the epistemic and in the health-related sense. I distinguish three main types of negative mechanistic reasoning and subsume them under a new definition of mechanistic reasoning in the context of assessing medical interventions. Although this definition is wider than a previous suggestion in the literature, there are still other instances of reasoning that concern mechanisms but do not count as mechanistic reasoning. One of the three distinguished types, which is negative only in the health-related sense, has a corresponding positive counterpart, whereas the other two, which are epistemically negative, do not have such counterparts, at least not that are particularly interesting as evidence. Accounting for negative mechanistic reasoning in EBM is therefore partly different from accounting for positive mechanistic reasoning. Each negative type corresponds to a range of evidential strengths, and it is argued that there are differences with respect to the typical strengths. The variety of negative mechanistic reasoning should be acknowledged in EBM, and presents a serious challenge to proponents of so-called medical hierarchies of evidence. (shrink)

In this paper we identify six theses that constitute core results of philosophical investigation into the nature of mechanisms, and of the role that the search for and identification of mechanisms play in the sciences. These theses represent the fruits of the body of research that is now often called New Mechanism. We concisely present the main arguments for these theses. In the literature, these arguments are scattered and often implicit. Our analysis can guide future research in many ways: it (...) provides critics of New Mechanism with clear targets, it can reduce misunderstandings, it can clarify differences of opinion among New Mechanists and it helps to define a research agenda for New Mechanists. (shrink)

At least historically, it was common for medical practitioners to believe causal hypotheses on the basis of standalone mechanistic reasoning. However, it is now widely acknowledged that standalone mechanistic reasoning is insufficient for appropriately believing a causal hypothesis in medicine, thanks in part to the so-called problem of masking. But standalone mechanistic reasoning is not the only type of mechanistic reasoning. When exactly then is it appropriate to believe a causal hypothesis on the basis of mechanistic reasoning? In this paper, (...) I argue that it has proved difficult to provide a satisfying answer to this question. I also argue that this difficulty is predicted by recent work in knowledge-first epistemology. I think this shows that recent work in epistemology has important implications for practice in the philosophy of science. It is therefore worth paying closer attention in the philosophy of science to this recent work in knowledge-first epistemology. (shrink)

The US Food and Drug Administration (FDA) is fraught with controversies over the role of values and politics in regulatory science, especially with drugs in the realm of reproductive health. Philosophers and science studies scholars have investigated the ways in which social context shapes medical knowledge through value judgments, and feminist scholars and activists have criticized sexism and injustice in reproductive medicine. Nonetheless, there has been no systematic study of values and gender norms in FDA drug regulation. I focus on (...) three questions about values in regulatory science. First, how have societal values and gender norms shaped the way that the FDA regulates drugs in the realm of reproductive health, specifically with drug labels? Second, what are the ethical, epistemic, and social consequences of these influences on regulation for women and other marginalized groups? Third, which societal values and gender norms ought to influence drug regulation about reproductive health, and how ought this happen? Integrating philosophical analysis with historical archival research and in-depth interviews, I conduct three case studies of drug labeling about reproductive health: (1) the “drug fact” about the mechanism of the morning-after pill; (2) the package inserts for patients about the health risks of oral contraceptives; and (3) the special physician labels made for prescribing drugs to pregnant women. I identify three challenges for the FDA and suggest ways to reduce the influence of sexist values and facilitate feminist alternatives. First, across these cases, I have found that there are many ways in which other concerns in reproductive medicine (such as zygotic life, fetal health, and population control) have devalued women’s health. Second, both knowledge and ignorance xvi about their reproductive health have contributed to women’s oppression, especially poor women and women of color. Finally, by avoiding the epistemic dimensions of ethics, powerful, mostly male parties in medicine (such as doctors, pharmaceutical companies, and religious institutions) have misused “informed consent,” “religious freedom,” and “paternalism” for unethical purposes. For improvement, I suggest extracting sexist values and gender norms from regulatory science that cause epistemic injustices, and I point to success stories for reforming sexism with feminism at the FDA. (shrink)

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 claims are established on the basis of a (...) plurality of evidence. We discuss the consequences of ‘evidential pluralism’ in the context of econometric modelling. (shrink)

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)

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.

Is evidential pluralism possible when we move to the social sciences, and if so, to what degree? What are the analytical benefits? The answer put forward in this article is that there is a tradeoff between how serious social science methodologies take the study of mechanisms and the analytical benefits that flow from evidential pluralism. In the social sciences, there are a range of different approaches to studying mechanisms, differentiated by the degree to which the ‘process’ is unpacked theoretically, and (...) whether the approach takes seriously the particular nature of social phenomena and the epistemological consequences that flow from this, as in realist approaches to the study of mechanisms, or whether more neopositivist-based foundational assumptions are adopted. Depending on which approach to study mechanisms is used, evidential pluralism is either: easy but superficial, very productive but challenging, or almost impossible because of the fundamental differences between the types of claims being made and the forms of evidence used. (shrink)

We show how more general knowledge can be built in information security, by the building of knowledge of mechanism clusters, some of which are multifield. By doing this, we address in a novel way the longstanding philosophical problem of how, if at all, we come to have knowledge that is in any way general, when we seem to be confined to particular experiences. We also address the issue of building knowledge of mechanisms by studying an area that is new to (...) the mechanisms literature: the methods of what we shall call mechanism discovery in information security. This domain offers a fascinating novel constellation of challenges for building more general knowledge. Specifically, the building of stable communicable mechanistic knowledge is impeded by the inherent changeability of software, which is deployed by malicious actors constantly changing how their software attacks, and also by an ineliminable secrecy concerning the details of attacks not just by attackers, but also by information security defenders as they protect their methods from both attackers and commercial competitors. We draw out ideas from the work of the mechanists Darden, Craver, and Glennan to yield an approach to how general knowledge of mechanisms can be painstakingly built. We then use three related examples of active research problems from information security to develop philosophical thinking about building general knowledge using mechanisms, and also apply this to develop insights for information security. We show that further study would be instructive both for practitioners and for philosophers. (shrink)

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)

Thinking about illness causation has a long and rich history in medicine. After a hiatus in the 1990s, the last one-and-a-half decades have seen a surge of publications on causality in the biomedical sciences. Interestingly, this surge is visible not only in the medical, epidemiological, bioinformatics, and public health literatures, but also among philosophical publications. In this essay, I review and discuss one most recent addition to the literature, "Causality: Philosophical Theory Meets Scientific Practice" written by philosophers Phyllis Illari and (...) Federica Russo about causality in the sciences, and particularly about the health sciences. (shrink)

The existing philosophical views on what is the meaning of causality adequate to medicine are vastly divided. We approach this question and offer two arguments in favor of pluralism regarding concepts of causality. First, we analyze the three main types of research designs (randomized-controlled trials, observational epidemiology and laboratory research). We argue, using examples, that they allow for making causal conclusions that are best understood differently in each case (in agreement with a version of manipulationist, probabilistic and mechanistic definitions, respectively). (...) Second, we analyze clinical practice and argue that these manipulationist, probabilistic and mechanistic causal claims can be used as evidence for different therapeutic decisions. We differentiate among ‘predicting’ that does not change the relata of causal claims, (mechanistic) ‘interferences’, and ‘interventions’ in the strict sense that act on causes to change effects. The central conclusion is that causal claims agreeing with diverse concepts of causality can deliver evidence for different types of therapeutic decisions. (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)

I argue that difference-making should be a crucial element for evaluating the quality of evidence for mechanisms, especially with respect to the robustness of mechanisms, and that it should take central stage when it comes to the general role played by mechanisms in establishing causal claims in medicine. The difference- making of mechanisms should provide additional compelling reasons to accept the gist of Russo-Williamson thesis and include mechanisms in the protocols for Evidence- Based Medicine (EBM), as the EBM+ research group (...) has been advocating. (shrink)

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)