Robustness is a common platitude: hypotheses are better supported with evidence generated by multiple techniques that rely on different background assumptions. Robustness has been put to numerous epistemic tasks, including the demarcation of artifacts from real entities, countering the “experimenter’s regress,” and resolving evidential discordance. Despite the frequency of appeals to robustness, the notion itself has received scant critique. Arguments based on robustness can give incorrect conclusions. More worrying is that although robustness may be valuable in ideal evidential circumstances (i.e., (...) when evidence is concordant), often when a variety of evidence is available from multiple techniques, the evidence is discordant. †To contact the author, please write to: Jacob Stegenga, Department of Philosophy, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093; e‐mail: [email protected]. (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.

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)

The issue of how to incorporate the individual's first‐hand experience of illness into broader medical understanding is a major question in medical theory and practice. In a philosophical context, phenomenology, with its emphasis on the subject's perception of phenomena as the basis for knowledge and its questioning of naturalism, seems an obvious candidate for addressing these issues. This is a review of current phenomenological approaches to medicine, looking at what has motivated this philosophical approach, the main problems it faces and (...) suggesting how it might become a useful philosophical tool within medicine, with its own individual, but interrelated, contribution to make to current medical debates. After the general background, there is a brief summary of phenomenological ideas and their current usage in a medical context. Next is a critique of four key claims within current phenomenological medical works, concerning both the role phenomenology plays and the supposedly clear divide between phenomenology and other approaches. There are significant problems within these claims, largely because they overlook the complexity of the questions they consider. Finally, there is some more in‐depth examination of phenomenology itself and the true complexity of phenomenological debate concerning subjectivity. The aim is to show that it will be both more productive and truer to phenomenology itself, if we use phenomenology as a philosophical method for explicating and gaining deeper understanding of complex and fundamental problems, which are central to medicine, rather than as providing simple, but flawed solutions. (shrink)

We claim that if a complete philosophy of evidence-based practice is intended, then attention to the nature of causation in health science is necessary. We identify how health science currently conceptualises causation by the way it prioritises some research methods over others. We then show how the current understanding of what causation is serves to constrain scientific progress. An alternative account of causation is offered. This is one of dispositionalism. We claim that by understanding causation from a dispositionalist stance, many (...) of the processes within an evidence-based practice framework are better accounted for. Further, some of the problems associated with the health research, e.g. external validity of causal findings, dissolve. (shrink)

Developments in Machine Learning (ML) have attracted attention in a wide range of healthcare fields to improve medical practice and the benefit of patients. Particularly, this should be achieved by providing more or less automated decision recommendations to the treating physician. However, some hopes placed in ML for healthcare seem to be disappointed, at least in part, by a lack of transparency or traceability. Skepticism exists primarily in the fact that the physician, as the person responsible for diagnosis, therapy, and (...) care, has no or insufficient insight into how such recommendations are reached. The following paper aims to make understandable the specificity of the deliberative model of a physician-patient relationship that has been achieved over decades. By outlining the (social-)epistemic and inherently normative relationship between physicians and patients, I want to show how this relationship might be altered by non-traceable ML recommendations. With respect to some healthcare decisions, such changes in deliberative practice may create normatively far-reaching challenges. Therefore, in the future, a differentiation of decision-making situations in healthcare with respect to the necessary depth of insight into the process of outcome generation seems essential. (shrink)

Several have argued that the aims of scientific research are not always independent of social and ethical values. Yet this is often assumed only to have implications for decisions about what is studied, or which research projects are funded, and not for methodological decisions or standards of evidence. Using the case of the recently developed HPV vaccines, we argue that the social aims of research can also play important roles in justifying decisions about (1) how research problems are defined in (...) drug development, (2) evidentiary standards used in testing drug “success”, and (3) clinical trial methodology. As a result, attending to the social aims at stake in particular research contexts will produce more rational methodological decisions as well as more socially relevant science. (shrink)

Consensus conferences are social techniques which involve bringing together a group of scientific experts, and sometimes also non-experts, in order to increase the public role in science and related policy, to amalgamate diverse and often contradictory evidence for a hypothesis of interest, and to achieve scientific consensus or at least the appearance of consensus among scientists. For consensus conferences that set out to amalgamate evidence, I propose three desiderata: Inclusivity, Constraint, and Evidential Complexity. Two examples suggest that consensus conferences can (...) readily satisfy Inclusivity and Evidential Complexity, but consensus conferences do not as easily satisfy Constraint. I end by discussing the relation between social inclusivity and the three desiderata. (shrink)

One way to make philosophy of science more socially relevant is to attend to specific scientific practises that affect society to a great extent. One such practise is biomedical research. This paper looks at contemporary U.S. biomedical research in particular and argues that it suffers from important epistemic, moral and socioeconomic failings. It then discusses and criticises existing approaches to improve on the status quo, most prominently by Thomas Pogge (a political philosopher), Joseph Stiglitz (a Nobel-prize winning economist) and James (...) Robert Brown (a philosopher of science). Finally, it sketches an alternative proposal and argues for its superiority. The proposal has four components: changing the intellectual property regime; instituting independent clinical research; aligning innovators' and patients' interests; and enacting additional regulation. (shrink)

Pluralism about scientific method is more-or-less accepted, but the consequences have yet to be drawn out. Scientists adopt different methods in response to different epistemic situations: depending on the system they are interested in, the resources at their disposal, and so forth. If it is right that different methods are appropriate in different situations, then mismatches between methods and situations are possible. This is most likely to occur due to method bias: when we prefer a particular kind of method, despite (...) that method clashing with evidential context or our aims. To explore these ideas, we sketch a kind of method pluralism which turns on two properties of evidence, before using agent-based models to examine the relationship between methods, epistemic situations, and bias. Based on our results, we suggest that although method bias can undermine the efficiency of a scientific community, it can also be productive through preserving a diversity of evidence. We consider circumstances where method bias could be particularly egregious, and those where it is a potential virtue, and argue that consideration of method bias reveals that community standards deserve a central place in the epistemology of science. (shrink)

Over the past several decades, we devoted much energy to generating, reviewing and summarizing evidence. We have given far less attention to the issue of how to thoughtfully apply the evidence once we have it. That’s fine if all we care about is that our clinical decisions are evidence-based, but not so good if we also want them to be well-reasoned. Let us not forget that evidence based medicine (EBM) grew out of an interest in making medicine ‘rational’, with the (...) idea that rational clinical evaluations should be evidence-based. I agree with the uncontroversial statement that the best decision is supported, at least in part, by the best available evidence. Rationality, however, is constituted by reasoning, not evidence. Complete arguments are necessary for rational evaluations, arguments that begin with general evidence and end in a conclusion about a particular patient. In order to traverse these inferential gaps, medicine must address the issue of how to establish, as an intermediate premise, what the evidence has to say about the efficacy of an intervention for particular patients in a particular practice setting. (shrink)

In the human sciences, experimental research is used to establish causal relationships. However, the extrapolation of these results to the target population can be problematic. To facilitate extrapolation, we propose to use the statistical technique Latent Class Regression Analysis in combination with the analogical reasoning theory for extrapolation. This statistical technique can identify latent classes that differ in the effect of X on Y. In order to extrapolate by means of analogical reasoning, one can characterize the latent classes by a (...) combination of features, and then compare these features to features of the target. (shrink)

Philosophers of science often make reference — whether tacitly or explicitly — to the notion of a scientific community. Sometimes, such references are useful to make our object of analysis tractable in the philosophy of science. For others, tracking or understanding particular features of the development of science proves to be tied to notions of a scientific community either as a target of theoretical or social intervention. We argue that the structure of contemporary scientific research poses two unappreciated, or at (...) least underappreciated, challenges to this concept of the “scientific community” in the philosophy of science. In particular, we will present two case studies from robotics research, broadly construed, which show that (1) the boundedness of the scientific community is threatened when private citizens can develop scientific and technological advances at minimal expense (democratization), and (2) the discreteness of scientific research programs is threatened by the complexly interrelated environment of contemporary scientific work (interconnectivity). Taken together, the extent of democratization and interconnectivity present a significant challenge for any practically oriented philosophy of science, one which we hope will be taken on directly by philosophers in the future. (shrink)

The initial successes in recent years in harnessing machine learning technologies to improve medical practice and benefit patients have attracted attention in a wide range of healthcare fields. Particularly, it should be achieved by providing automated decision recommendations to the treating clinician. Some hopes placed in such ML-based systems for healthcare, however, seem to be unwarranted, at least partially because of their inherent lack of transparency, although their results seem convincing in accuracy and reliability. Skepticism arises when the physician as (...) the agent responsible for the implementation of diagnosis, therapy, and care is unable to access the generation of findings and recommendations. There is widespread agreement that, generally, a complete traceability is preferable to opaque recommendations; however, there are differences about addressing ML-based systems whose functioning seems to remain opaque to some degree—even if so-called explicable or interpretable systems gain increasing amounts of interest. This essay approaches the epistemic foundations of ML-generated information specifically and medical knowledge generally to advocate differentiations of decision-making situations in clinical contexts regarding their necessary depth of insight into the process of information generation. Empirically accurate or reliable outcomes are sufficient for some decision situations in healthcare, whereas other clinical decisions require extensive insight into ML-generated outcomes because of their inherently normative implications. (shrink)

Medical scientists employ ‘quality assessment tools’ (QATs) to measure the quality of evidence from clinical studies, especially randomized controlled trials (RCTs). These tools are designed to take into account various methodological details of clinical studies, including randomization, blinding, and other features of studies deemed relevant to minimizing bias and error. There are now dozens available. The various QATs on offer differ widely from each other, and second-order empirical studies show that QATs have low inter-rater reliability and low inter-tool reliability. This (...) is an instance of a more general problem I call the underdetermination of evidential significance. Disagreements about the strength of a particular piece of evidence can be due to different—but in principle equally good—weightings of the fine-grained methodological features which constitute QATs. (shrink)

This article critically analyses the concept of evidence in evidence‐based policy, arguing that there is a key problem: there is no existing practicable theory of evidence, one which is philosophically‐grounded and yet applicable for evidence‐based policy. The article critically considers both philosophical accounts of evidence and practical treatments of evidence in evidence‐based policy. It argues that both fail in different ways to provide a theory of evidence that is adequate for evidence‐based policy. The article contributes to the debate about how (...) evidence can and should be used to reduce contingency in science and in policy based on science. (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 standardised randomised clinical trial (RCT) has been exceedingly popular in medical research, economics, and practical policy making. Recently, RCTs have faced criticism. First, it has been argued by John Worrall that we cannot be certain that our sample is not atypical with regard to possible confounding factors. I will argue that at least in the case of medical research, we know enough about the relevant causal mechanisms to be justified to ignore a number of factors we have good reason (...) not to expect to be disruptive. I will also argue against an argument provided by Nancy Cartwright and Eileen Munro that RCTs should not be taken to deductively infer probabilistic causal claims, but ampliatively. The paper will end on a discussion of evidence hierarchies and a defence of the stance of evidence-based medicine that RCTs are the best available method to assess a treatment’s efficacy. (shrink)

This paper reflects on the relationship between theory and practice in bioethics, by using various concepts drawn from debates on innovation in healthcare research—in particular debates around how best to connect up blue skies ‘basic’ research with practical innovations that can improve human lives. It argues that it is a mistake to assume that the most difficult and important questions in bioethics are the most abstract ones, and also a mistake to assume that getting clear about abstract cases will automatically (...) be of much help in getting clear about more complex cases. It replaces this implicitly linear model with a more complex one that draws on the idea of translational research in healthcare. On the translational model, there is a continuum of cases from the most simple and abstract to the most concrete and complex. Insights need to travel in both directions along this continuum—from the more abstract to the more concrete and from the more concrete to the more abstract. The paper maps out some difficulties in moving from simpler to more complex cases, and in doing so makes recommendations about the future of bioethics. (shrink)

The underreporting of suspected adverse drug reactions remains a primary issue for contemporary post-market drug surveillance or ‘pharmacovigilance.’ Pharmacovigilance pioneer W.H.W. Inman argued that ‘deadly sins’ committed by clinicians are to blame for underreporting. Of these ‘sins,’ ignorance and lethargy are the most obvious and impactful in causing underreporting. However, recent analyses show that diffidence, insecurity, and indifference additionally play a major role. I aim to augment our understanding of diffidence, insecurity, and indifference by arguing these sins are underwritten by (...) value judgments arising via epistemic risk. I contend that ‘evidence-based’ medicine codifies these sins. (shrink)

This paper outlines the methodological and empirical limitations of analysing the potential relationship between complex social phenomena such as democracy and inequality. It shows that the means to assess how they may be related is much more limited than recognised in the existing literature that is laden with contradictory hypotheses and findings. Better understanding our scientific limitations in studying this potential relationship is important for research and policy because many leading economists and other social scientists such as Acemoglu and Robinson (...) mistakenly claim to identify causal linkages between inequality and democracy but at times still inform policy. In contrast to the existing literature, the paper argues that ‘structural’ or ‘causal’ mechanisms that may potentially link the distribution of economic wealth and different political regimes will remain unknown given reasons such as their highly complex and idiosyncratic characteristics, fundamental econometric constraints and analysis at the macro-level. Neither new data sources, different analysed time periods nor new data analysis techniques can resolve this question and provide robust, general conclusions about this potential relationship across countries. Researchers are thus restricted to exploring rough correlations over specific time periods and geographic contexts with imperfect data that are very limited for cross-country comparisons. (shrink)

In a well-cited book chapter, ecologist Jared Diamond characterizes three main types of experiment performed in community ecology: laboratory experiment, field experiment, and natural experiment. Diamond argues that each form of experiment has strengths and weaknesses, with respect to, for example, realism or the ability to follow a causal trajectory. But does Diamond’s typology exhaust the available kinds of cause-finding practices? Some social scientists have characterized something they call “causal process tracing.” Is this a fourth type of experiment or something (...) else? I examine Diamond’s typology and causal process tracing in the context of a case study concerning the dynamics of wolf and deer populations on the Kaibab Plateau in the 1920s, a case that has been used as a canonical example of a trophic cascade by ecologists but which has also been subject to controversy. I argue that ecologists have profitably deployed causal process tracing together with other types of experiment to help settle questions of causality in this case. It remains to be seen how widespread the use of causal process tracing outside of the social sciences is (or could be), but there are some potentially promising applications, particularly with respect to questions about specific causal sequences. (shrink)

In this paper we consider the problem of how to measure the strength of statistical evidence from the perspective of evidence amalgamation operations. We begin with a fundamental measurement amalgamation principle : for any measurement, the inputs and outputs of an amalgamation procedure must be on the same scale, and this scale must have a meaningful interpretation vis a vis the object of measurement. Using the p value as a candidate evidence measure, we examine various commonly used approaches to amalgamation (...) of evidence across similar studies, including standard forms of meta-analysis. We show that none of these methods satisfies MAP. Thus an underlying measurement problem remains. We argue that a successful approach to evidence amalgamation necessitates a solution to the problem of evidence measurement, and we suggest some lines of reasoning that might guide further work towards this end. (shrink)

ABSTRACT“Evidence-based” methods, which most prominently include randomized controlled trials, have gained increasing purchase as the “gold standard” for assessing the effect of public policies. But the enthusiasm for evidence-based research overlooks questions about the reliability and applicability of experimental findings to diverse real-world settings. Perhaps surprisingly, a qualitative study of British educators suggests that they are aware of these limitations and therefore take evidence-based findings with a much larger grain of salt than do policy makers. Their experience suggests that the (...) real world is more heterogeneous than the world imagined by evidence-based policy enthusiasts. (shrink)

Robert Truog describes the controversial randomized controlled trials (RCTs) of extracorporeal membrane oxygenation (ECMO) therapy in newborns. Because early results with ECMO indicated that it might be a great advance, saving many lives, Truog argues that ECMO should not have been tested using RCTs, but that a long-term, large-scale observational study of actual clinical practice should have been conducted instead. Central to Truog’s argument, however, is the idea that ECMO is an unusual case. Thus, it is an open question whether (...) Truog’s conclusions can be extended to other areas of medical research. In this paper, I look at epistemological and ethical issues arising in the care of patients with chronic diseases, using ECMO as a starting point. Both the similarities and the dissimilarities of these two cases highlight important issues in biomedical research and support a conclusion similar to Truog’s. Observational studies of clinical practice provide the best evidence to inform the treatment of patients with chronic disease. (shrink)

Evidence-based approaches to policy-making are growing in popularity. A generally embraced view is that with the appropriate evidence at hand, decision and policy making will be optimal, legitimate and publicly accountable. In practice, however, evidence-based policy making is constrained by a variety of problems of evidence. Some of these problems will be explored in this article, in the context of the debates on evidence from which they originate. It is argued that the source of much disagreement might be a failure (...) to addressing crucial philosophical assumptions that inform, often silently, these debates. Three controversial questions will be raised which appear central to some of the challenges faced by evidence-based policy making: firstly, how do certain types of facts candidate themselves as evidence; secondly, how do we decide what evidence we have, and how much of it; and thirdly, can we combine evidence. In addressing these questions it will be shown how a philosophically informed debate might prove instrumental in clarifying and settling practical difficulties. (shrink)

John Worrall and Nancy Cartwright have both argued that randomized controlled trials are “testing the wrong theory.” They claim that RCTs are designed to test inferences about the causal relationships in the study population, but this does not guarantee a justified inference about the causal relationships in the more diverse population in clinical practice. In this article I argue that the epistemology of theory testing in trials is more complicated than either Worrall’s or Cartwright’s accounts suggest. I illustrate this more (...) complex theoretical structure with case studies in medical theory testing from Alzheimer’s research and anticancer drugs in personalized medicine. (shrink)

While the history and methodology of laboratory experiments in economics have been extensively studied by philosophers, those of field experiments have not attracted much attention until recently. What is the historical context in which field experiments have been advocated? And what are the methodological rationales for conducting experiments in the field as opposed to in the lab? This article addresses these questions by combining historical and methodological perspectives. In terms of history, we show that the movement toward field experiments in (...) economics has two distinct roots. One is the general orientation of medical and social sciences to evidence-based policy evaluation, which gave rise to randomized field experiments in economics (e.g., behavioral public policy, poverty alleviation policy). The other is an awareness of several methodological limitations of lab experiments in economics, which required practitioners to get out of the lab and into the field. In these senses, the movement is a consequence of influences from both outside and inside economics: the general evidence-based trend in policy science and an internal methodological development of experimental economics. In terms of methodology, we show that these two roots resulted in two somewhat different notions of “external validity” as methodological rationales of field experiment. Finally, we suggest that analysis of experiments as exhibits highlights a methodological strategy in which both strands complement each other. (shrink)

This book develops an integrated perspective on the practices and politics of making knowledge work in inclusive development and innovation. While debates about development and innovation commonly appeal to the authority of academic researchers, many current approaches emphasize the plurality of actors with relevant expertise for addressing livelihood challenges. Adopting an action-oriented and reflexive approach, this volume explores the variety of ways in which knowledge works, paying particular attention to dilemmas and controversies. The six parts of the book address the (...) complex interplay of knowledge and politics, starting with the need for knowledge integration in the first part and decolonial perspectives on the politics of knowledge integration in the second part. The following three parts focus on the practices of inclusive development and innovation through three major themes of transformative learning, evidence, and digitization. The final part of the book addresses the governance of knowledge and innovation in the light of political struggles about inclusivity. Exploring conceptual and practical themes through case studies from the Global North and South, this book will be of great interest to students, scholars and practitioners researching and working in development studies, epistemology, innovation studies, science and technology studies and sustainability studies more broadly. (shrink)

This chapter provides an introduction to the study of the philosophical notions of mechanisms and causality in biology and economics. This chapter sets the stage for this volume, Mechanism and Causality in Biology and Economics, in three ways. First, it gives a broad review of the recent changes and current state of the study of mechanisms and causality in the philosophy of science. Second, consistent with a recent trend in the philosophy of science to focus on scientific practices, it in (...) turn implies the importance of studying the scientific methods employed by researchers. Finally, by way of providing an overview of each chapter in the volume, this chapter demonstrates that biology and economics are two fertile fields for the philosophy of science and shows how biological and economic mechanisms and causality can be synthesized. (shrink)

Clinical equipoise has been proposed as an ethical principle relating uncertainty and moral leeway in clinical research. Although CE has traditionally been indicated as a necessary condition for a morally justified introduction of a new RCT, questions related to the interpretation of this principle remain woefully open. Recent proposals to rehabilitate CE have divided the bioethical community on its ethical merits. This paper presents a new argument that brings out the epistemological difficulties we encounter in justifying CE as a principle (...) to connect uncertainty and moral leeway in clinical ethics. The argument proposes, first, that the methodology of hypothetical retrospection is applicable to the RCT design and that it can accommodate uncertainty. As currently understood, however, HR should give up its reliance on the assumption of uncertainty transduction, because the latter assumes the principle of indifference, which does not accommodate uncertainty in the right way. The same principle is then seen to distort also the received interpretations of CE. (shrink)

This paper assesses the epistemic challenges of giving nutrition advice to elite athletes in light of recent philosophical discussion concerning evidence-based practice. Our trust in experts largely depends on the assumption that their advice is based on reliable evidence. In many fields, the evaluation of the reliability of evidence is made on the basis of standards that originate from evidence-based medicine. I show that at the Olympic or professional level, implementing nutritional plans in real-world competitions requires contextualization of knowledge in (...) a way that contravenes the tenets of evidence-based thinking. Nutrition experts need to be able to combine and apply evidence from multiple sources, including the previous successes and failures of particular athletes. I argue that in this sense, the practice of elite sport nutrition embodies casuistic reasoning. (shrink)

The notion of ‘causal web’ emerged in the epidemiological literature in the early Sixties and had to wait until the Nineties for a thorough critical appraisal. Famously, Nancy Krieger argued that such a notion isn’t helpful unless we specify what kind of spiders create the webs. This means, according to Krieger, (i) that the role of the spiders is to provide an explanation of the yarns of the web and (ii) that the sought spiders have to be biological and social. (...) This paper contributes to the development of the notion of causal web, elaborating on the two following points: (i) to catch the spiders we need multi-fold evidence—specifically, mechanistic and difference-making—and (ii) for the eco-social to be explanatory, the web has to be mechanistic in a sense to be specified. (shrink)

Empirical success is a central criterion for scientific decision-making. Yet its understanding in philosophical studies of science deserves renewed attention: Should philosophers think differently about the advancement of science when they deal with the uncertainty of outcome in ongoing research in comparison with historical episodes? This paper argues that normative appeals to empirical success in the evaluation of competing scientific explanations can result in unreliable conclusions, especially when we are looking at the changeability of direction in ongoing investigations. The challenges (...) we encounter arise from the inherent dynamics of disciplinary and experimental objectives in research practice. In this paper we discuss how these dynamics inform the evaluation of empirical success by analyzing three of its requirements: data accommodation, instrumental reliability, and predictive power. We conclude that the assessment of empirical success in developing inquiry is set against the background of a model’s interactive success and prospective value in an experimental context. Our argument is exemplified by the analysis of an apparent controversy surrounding the model of a quantum nose in research on olfaction. Notably the public narrative of this controversy rests on a distorted perspective on measures of empirical success. (shrink)

As the quality movement in health care now enters its fourth decade, the language of quality is ubiquitous. Practitioners, organizations, and government agencies alike vociferously testify their commitments to quality and accept numerous forms of governance aimed at improving quality of care. Remarkably, the powerful phrase ‘‘quality of care’’ is rarely defined in the health care literature. Instead it operates as an accepted and assumed goal worth pursuing. The status of evidence-based medicine, for instance, hinges on its ability to improve (...) quality of care, and efforts are made by both proponents and detractors to unpack the contents and outcomes of evidence-based practice while the contents of ‘‘quality of care’’ are presumed to be understood. Because the goals of medicine are far from obvious, this paper investigates the neglected term, ‘‘quality of care,’’ in an effort to understand what it is that health care practices are so uncritically assumed to be striving for. Finding lack of consensus on the terminology in the quality literature, I propose that the term operates rhetorically by way of persuasive appeal (and lack of descriptive meaning). Unsatisfied that ‘‘quality of care’’ operates as a mere buzzword in morally contentious debates over resource allocation and duties of care, I implore health care communities to go beyond mere commitments to quality and, instead, to focus attention on the difficult task of specifying what counts as quality care within an economically constrained health care system. (shrink)

The paper addresses charges of risk and loss aversion as well as of irrationality directed against the precautionary principle, by providing an epistemic analysis of its specific role in the safety law system. In particular, I contend that: 1) risk aversion is not a form of irrational or biased behaviour; 2) both risk and loss aversion regard the form of the utility function, whereas PP rather regards the information on which to base the decision; 3) thus PP has formally nothing (...) to do with risk or loss aversion but rather with risk awareness; 4) PP removes a fictional construct in the legal system, according to which any hazard should be ignored and denied until it is scientifically proven; 5) the quandary originates in the tension between current methods of evidence evaluation, and the logic underlying PP which demands for a probabilistic epistemology. (shrink)

Because few would object to evidence-based medicine’s (EBM) principal task of basing medical decisionmaking on the most judicious and up-to-date evidence, the debate over this prolific movement may seem puzzling. Who, one may ask, could be against evidence (Carr-Hill, 2006)? Yet this question belies the sophistication of the evidence-based movement. This chapter presents the evidence-based approach as a socio-medical phenomenon and seeks to explain and negotiate the points of disagreement between supporters and detractors. This is done by casting EBM as (...) more than the simple application of research findings to clinical care and improved health outcomes, but rather an umbrella term that harnesses a specific set of pedagogical objectives (some rather radical) under a name that makes it difficult to argue against. (shrink)

The present paper deals with the problem of evaluating empirical evidence for therapeutic decisions in medicine. The article discusses the views of Nancy Cartwright and John Worrall on the function that randomization plays in ascertaining causal relations with reference to the therapies applied. The main purpose of the paper is to present a general idea of alternative method of evaluating empirical evidence. The method builds on data analysis that makes use of rough set theory. The first attempts to apply the (...) method show that it is an interesting alternative to randomized controlled trials. (shrink)

This article argues that the credibility of both theoretical and empirical models in economics is best understood through their connection with the empirical aspects of the real world. The discussion herein demonstrates that the similarity between the model and the real world is not enough to justify a theoretical model’s explanatory power. The best way to secure the model’s credibility is to prove the existence of representation theorems.

Many in the international development community have embraced the randomized controlled field experiment, akin to a biomedical clinical trial for social interventions, as the new “gold evidential standard” in program impact evaluation. In response, critics have called upon the method’s advocates to consider the moral dimensions of randomization, leading to a debate about the method’s ethics. My research intervenes in this debate by empirically investigating how researchers manage the perception of randomization in the field. Without the possibility of a placebo, (...) researchers rhetorically and materially frame the experiment differently for the control and treatment groups. Three technologies allow for this differential framing: geographic separation, temporal delay, and public randomization ceremonies. Geographic separation is a “technology of opacity” designed to obscure unequal resource distribution by disentangling the intervention and research components of the experiment for the control group. The latter two are technologies of transparency designed to expose the element of randomization but downplay conditions that may affect participant buy in. All three technologies work to preclude collective definitions of fair resource allocation, yet they are not fully successful in preventing modes of confrontation and resistance that lie outside of the experiment’s framing. (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)

This thesis examines philosophical controversies surrounding the evaluation of medical treatments, with a focus on the evidential roles of randomised trials and mechanisms in Evidence-Based Medicine. Current 'best practice' usually involves excluding non-randomised trial evidence from systematic reviews in cases where randomised trials are available for inclusion in the reviews. The first paper challenges this practice and evaluates whether adding of evidence from non-randomised trials might improve the quality and precision of some systematic reviews. The second paper compares the alleged (...) methodological benefits of randomised trials over observational studies for investigating treatment benefits. It suggests that claims about the superiority of well-conducted randomised controlled trials over well-conducted observational studies are justified, especially when results from the two methods are contradictory. The third paper argues that postulating the unpredictability paradox in systematic reviews when no detectable empirical differences can be found requires further justification. The fourth paper examines the problem of absence causation in the context of explaining causal mechanisms and argues that a recent solution is incomplete and requires further justification. Solving the problem by describing absences as causes of 'mechanism failure' fails to take into account the effects of absences that lead to vacillating levels of mechanism functionality. The fifth paper criticises literature that has emphasised functioning versus 'broken' or 'non-functioning' mechanisms emphasising that many diseases result from increased or decreased mechanism function, rather than complete loss of function. Mechanistic explanations must account for differences in the effectiveness of performed functions, yet current philosophical mechanistic explanations do not achieve this. The last paper argues that the standard of evidence embodied in the ICE theory of technological function is too permissive for evaluating whether the proposed functions of medical technologies have been adequately assessed and correctly ascribed. It argues that high-quality evidence from clinical studies is necessary to justify functional ascriptions to health care technologies. (shrink)

Agent-based models (ABMs) are one type of simulation model used in the context of the COVID-19 pandemic. In contrast to equation-based models, ABMs are algorithms that use individual agents and attribute changing characteristics to each one, multiple times during multiple iterations over time. This paper focuses on three philosophical aspects of ABMs as models of causal mechanisms, as generators of emergent phenomena, and as providers of explanation. Based on my discussion, I conclude that while ABMs cannot help much with causal (...) inference, they can be viewed as etio-prognostic explanations of illness occurrence and outcome. (shrink)

I describe two traditions of philosophical accounts of evidence: one characterizes the notion in terms of signs of success, the other characterizes the notion in terms of conditions of success. The best examples of the former rely on the probability calculus, and have the virtues of generality and theoretical simplicity. The best examples of the latter describe the features of evidence which scientists appeal to in practice, which include general features of methods, such as quality and relevance, and general features (...) of evidence, such as patterns in data, concordance with other evidence, and believability of the evidence. Two infamous episodes from biomedical research help to illustrate these features. Philosophical characterization of these latter features—conditions of success—has the virtue of potential relevance to, and descriptive accuracy of, practices of experimental scientists. (shrink)

Psychotherapy research is known for its pursuit of evidence-based treatment. Psychotherapeutic efficacy is assessed by calculation of aggregated differences between pre treatment- and post treatment symptom levels. As this ‘gold standard methodology’ is regarded as ‘procedurally objective’, the efficacy number that results from the procedure is taken as a valid indicator of treatment efficacy. However, I argue that the assumption of procedural objectivity is not justified, as the methodology is build upon a problematic numerical basis. I use an empirical case (...) study to show how measurement problems practically occur in the first step of data collection, i.e. in individual symptom measurement. These problems have been discussed and acknowledged for decades, but still measurement is regarded as the best epistemic means to gain evidence on psychotherapeutic efficacy. Therefore, I show how initial measurement problems are overlooked in the remainder of the methodological procedure, which harms the ‘evidence-base’ of psychotherapeutic EBT. Via this applied analysis, I exhibit concerns that are increasingly raised in the literature in an empirical way, to emphasize the need for a non-idealized consideration of the ‘gold standard methodology’ as a means towards its clinical end. (shrink)

Evidence in medicine can come from more or less trustworthy sources and be produced by more or less reliable methods, and its interpretation can be disputed. As such, it can be unclear when disagreements in medicine result from different, but reasonable, interpretations of the available evidence and when they result from unreasonable refusals to consider legitimate evidence. In this article, we seek to show how assessments of the relevance and implications of evidence are typically affected by factors beyond that evidence (...) itself, such as our beliefs about the credibility of the speaker or source of the evidence. In evaluating evidence, there is thus a need for reflective awareness about why we accept or dismiss particular claims. (shrink)

Evidence-based policy is gaining support in many areas of government and in public affairs more generally. In this paper we outline what evidence—based policy is then discuss its strengths and weaknesses. In particular, we argue that it faces a serious challenge to provide a plausible account of evidence. This account needs to be at least in the spirit of the hierarchy of evidence subscribed to by evidence-based medicine (from which evidence—based policy derives its name and inspiration). Yet evidence-based policy’s hierarchy (...) needs to be tailored to the kinds of evidence relevant and available to the policy arena. The evidence required for policy decisions does not easily lend itself to randomised controlled trials (the "gold standard" in evidence-based medicine), nor, for that matter, being listed in a single all—purpose hierarchy. (shrink)