Alex Broadbent

When graduate students start their studies, they usually have sound knowledge of some areas of philosophy, but the overall map of their knowledge is often patchy and disjointed. There are a number of topics that any contemporary philosopher working in any part of the analytic tradition (and in many parts of other traditions too) needs to grasp, and to grasp as a coherent whole rather than a rag-bag of interesting but isolated discussions. This book answers this need, by providing a overview of core topics in metaphysics and epistemology that is at once accessible and nuanced. Ten core topics are explained, and their relation to each other is clearly set out. The book emphasizes the utility of the concepts and distinctions it covers for philosophy as a whole, not just for specialist discussions in metaphysics or epistemology. The text is highly readable and may be used as the basis of a course on these topics. Recommendations for reading are included at the end of each chapter, divided into essential and further readings. The text is also suitable for people approaching philosophy from other disciplines, as an accessible primer to the central topics, concepts and distinctions that are needed to engage meaningfully in contemporary philosophical debate.

This paper argues that lockdown was racist, where “lockdown” refers to a historically situated kind of regulatory response to the Covid-19 pandemic imposing significant restrictions on leaving the home and on activities outside it. We articulate a notion of negligent racism which is objective and does not require intent, and show that lockdown satisfies its definition. The effects of lockdown on Africa significantly disadvantaged its inhabitants relative to the inhabitants of at least some other regions. We show how this suffices to establish the general proposition that lockdown was negligently racist (not merely “sometimes” or “someplace”), given our definitions. We defend our conclusion against two objections: that lockdown was a (moral) necessity (one version of which is the idea that it was a necessary precaution); and that race is explanatorily irrelevant, meaning that to whatever extent our argument is successful, it succeeds merely in showing that lockdown was anti-poor and not that it was racist. Nothing remains to gainsay the conclusion that lockdown was racist.

When graduate students start their studies, they usually have sound knowledge of some areas of philosophy, but the overall map of their knowledge is often patchy and disjointed. There are a number of topics that any contemporary philosopher working in any part of the analytic tradition (and in many parts of other traditions too) needs to grasp, and to grasp as a coherent whole rather than a rag-bag of interesting but isolated discussions. This book answers this need, by providing a overview of core topics in metaphysics and epistemology that is at once accessible and nuanced. Ten core topics are explained, and their relation to each other is clearly set out. The book emphasizes the utility of the concepts and distinctions it covers for philosophy as a whole, not just for specialist discussions in metaphysics or epistemology. The text is highly readable and may be used as the basis of a course on these topics. Recommendations for reading are included at the end of each chapter, divided into essential and further readings. The text is also suitable for people approaching philosophy from other disciplines, as an accessible primer to the central topics, concepts and distinctions that are needed to engage meaningfully in contemporary philosophical debate.

In myrecent book I have sought to define a notion of stability and to argue that it is a useful notion for biomedical and especially epidemiological research (Broadbent 2013, 56–80). In this paper I seek to defend the notion of stability against two possible objections: that it fails to be epistemically significant, and that it amounts to nothing more than empirical adequacy. I argue that stability is epistemically significant because to know that a hypothesis is stable is to know something about the world, even if not the truth of the hypothesis. I argue that knowledge of stability of a hypothesis is distinct from knowledge of its approximate truth. And I argue that asserting the stability of a hypothesis is distinct from asserting its empirical adequacy, because it allows that the hypothesis may still be implicated in empirically inadequate claims, entailing only that if the hypothesis is so implicated, it will not be revised soon.

Crossing the road within the traffic system is an example of an action human agents perform successfully day-to-day in complex systems. How do they perform such successful actions given that the behaviour of complex systems is often difficult to predict? The contemporary literature contains two contrasting approaches to the epistemology of complex systems: an analytic and a post-modern approach. We argue that neither approach adequately accounts for how successful action is possible in complex systems. Agents regularly perform successful actions without obeying (explicit or implicit) algorithmic rules (as the analytic approach suggests) and without an existential leap to action (as the post-modern approach suggests). We offer an alternative: A common-sense pragmatist epistemology, one that focuses on the kind of actions making up most agents’ successful moment-to-moment actions in complex systems. Successful actions obtain when agents apply ceteris paribus rules-of-thumb during predictive and decisional practices while achieving some desired goal.

The Routledge Handbook of the Philosophy of Public Health is an outstanding reference source to this exciting subject and the first collection of its kind. Comprising over forty chapters by a team of international contributors the handbook covers the following central topics: What is global health?; methodology in public health science; social determinants and health equity; politics and economics; health policy and law; globalization; macroeconomics; securitization; and specific public health challenges such as obesity, cancer, alcohol, tobacco and infectious diseases. Essential reading for students and researchers in political philosophy, bioethics, public health ethics and the philosophy of medicine the handbook will also be very useful for those in related fields, such public health professionals and epidemiologists.

According to the evolutionary sceptic, the fact that our cognitive faculties evolved radically undermines their reliability. A number of evolutionary epistemologists have sought to refute this kind of scepticism. This paper accepts the success of these attempts, yet argues that refuting the evolutionary sceptic is not enough to put any particular domain of beliefs – notably scientific beliefs, which include belief in Darwinian evolution – on a firm footing. The paper thus sets out to contribute to this positive justificatory project, underdeveloped in the literature. In contrast to a ‘wholesale’ approach, attempting to secure justification for all of our beliefs on the grounds that our belief-forming mechanisms evolved to track truth, we propose a ‘piecemeal’ approach of assessing the reliability of particular belief-forming mechanisms in particular domains. This stands in contrast to the more familiar attempt to transfer warrant obtained for one domain to another by showing how one is somehow an extension of the other. We offer a naturalist reply to the charge of circularity by appealing to reliabilist work on the problem of induction, notably Peter Lipton's distinction between self-certifying and non-self-certifying inductive arguments. We show how, for scientific beliefs, a non-self-certifying argument might be made for the reliability of our cognitive faculties in that domain. We call this strategy Humean Bootstrapping

The Covid-19 pandemic was a world event on our intellectual doorstep. What were our duties to respond, and how well did we respond? We published papers, but we did not engage extensively or influentially in public debate. Perhaps we felt we were not experts. Yet in a health crisis, philosophers of medicine can offer not only “conceptual clarification,” but also domain-specific knowledge concerning structural properties of relevant sciences and their social-political uses. I set out three conditions for the kind of contribution I felt was lacking: public, critical, and timely. And I call for us to do more of it.

"In comparison to medicine, the professional field of public health is far less familiar. What is public health, and perhaps as importantly, what should public health be or become? How do causal concepts shape the public health agenda? How do study designs either promote or demote the environmental causal factors or health inequalities? How is risk understood, expressed, and communicated? Who is public health research centered on? How can we develop technologies so the benefits are more fairly distributed? Do people have a right to public health? How should we integrate ethics into public health practice? The Routledge Handbook of Philosophy of Public Health addresses these questions and more, and is the first collection of its kind. Comprising twenty-six chapters by an international and interdisciplinary team of contributors, the handbook is divided into four clear parts: Concepts and Distinctions Reasons and Actions Distribution and Inequalities Rights and Duties. The Routledge Handbook of Philosophy of Public Health is a field-defining and sustained reflection on the various ethical, political, methodological and conceptual aspects of global public health. As such it is an essential reference source for students and scholars working in political philosophy, bioethics, public health ethics, and the philosophy of medicine, as well as for professionals and researchers in related fields such public health and epidemiology"--

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

This paper considers an important recent contribution by Miguel Hernán to the ongoing debate about causal inference in epidemiology. Hernán rejects the idea that there is an in-principle epistemic distinction between the results of randomized controlled trials and observational studies: both produce associations which we may be more or less confident interpreting as causal. However, Hernán maintains that trials have a semantic advantage. Observational studies that seek to estimate causal effect risk issuing meaningless statements instead. The POA proposes a solution to this problem: improved restrictions on the meaningful use of causal language, in particular “causal effect”. This paper argues that new restrictions in fact fail their own standards of meaningfulness. The paper portrays the desire for a restrictive definition of causal language as positivistic, and argues that contemporary epidemiology should be more realistic in its approach to causation. In a realist context, restrictions on meaningfulness based on precision of definition are neither helpful nor necessary. Hernán’s favoured approach to causal language is saved from meaninglessness, along with the approaches he rejects.

What is medicine? One obvious answer in the context of the contemporary clinical tradition is that medicine is the process of curing sick people. However, this “curative thesis” is not satisfactory, even when “cure” is defined generously and even when exceptions such as cosmetic surgery are set aside. Historian of medicine Roy Porter argues that the position of medicine in society has had, and still has, little to do with its ability to make people better. Moreover, the efficacy of medicine for improving population health has been famously doubted by historians and epidemiologists. The curative thesis demands that we have mostly been stupid, duped, or staggeringly hopeful, given that medicine has not until recently offered more than a handful of effective cures. I suggest, in this article, that the core medical competence is neither to cure, nor to prevent, disease, but to understand and to predict it. I argue that this approach does a better job than the curative thesis at explaining why not all medicine is concerned with curative efforts and that it enjoys historical support from the ancient entanglement of prophecy and medicine and from the fact that medicine thrived for centuries with almost no effective cures and continues to thrive today in various forms that are mostly without curative efficacy. I suggest that this approach grounds a fairer approach to alternative, traditional, and other medical practices, as well as some fresh lessons for the development of mainstream medicine.

In the literature on health, naturalism and normativism are typically characterized as espousing and rejecting, respectively, the view that health is objective and value-free. This article points out that there are two distinct dimensions of disagreement, regarding objectivity and value-ladenness, and thus arranges naturalism and normativism as diagonal opposites on a two-by-two matrix of possible positions. One of the remaining quadrants is occupied by value-dependent realism, holding that health facts are value-laden and objective. The remaining quadrant, which holds that they are non-objective but value-free, is unexplored. The article endorses a view in the latter quadrant, namely, the view that health is a secondary property. The article argues that a secondary property framework provides the resources to respond to the deepest objections to a broadly Boorsean account of natural function, and so preserves the spirit, though not the letter, of that account. Treating health as a secondary property permits a naturalistic explanation—specifically, an evolutionary explanation—of the health concept, in terms of the assistance such a concept might have provided to the survival and reproduction of those organisms that had it. (This approach is completely distinct from evolutionary and aetiological accounts of natural functions.) This provides the explanation, missing from Boorse's account, for the fact that function is determined with reference to the contribution to the goals of survival and reproduction, relative to the age of the sex of the species, rather than some other equally natural goals or reference classes. 1Introduction2Two Ways to Disagree about Health3Secondary Properties4Health as a Secondary Property5Conclusion.

This paper argues that bioethics requires analysis, which is not explicitly ethical in character. The first part of the paper argues the general point, that ethical problems can arise not only on occasions when moral values make conflicting recommendations, but also in understanding the facts. I suggest that this is particularly so where the facts are provided by the biomedical sciences, since it is often not clear how to relate their conceptual framework to that in which we frame our value judgements. In the second part, I illustrate the argument by criticizing the moral conclusions drawn by the authors of a recent widely publicized study of paediatric obesity. There is a failure to translate properly these results into the language we use for moral evaluation. The case therefore illustrates exactly the analytic gap which I suggest bioethics might do more to fill.

This paper seeks to determine the significance, if any, of epidemiological evidence to prove the specific causation element of liability in negligence or other relevant torts—in particular, what importance can be attached to a relative risk > 2, where that figure represents a sound causal inference at the general level. The paper discusses increased risk approaches to epidemiological evidence and concludes that they are a last resort. The paper also criticizes the proposal that the probability of causation can be estimated with reference to the RR, such that RR > 2 is necessary and sufficient for causation. It is argued, following arguments by Sander Greenland and others, that RR > 2 is not necessary for proof of specific causation, except under restrictive biological assumptions that are not known to be satisfied for any important disease, and therefore must never be required. However, the paper argues that in some circumstances RR > 2 can be sufficient to prove causation at law. This position is defended against the widely held judicial and academic view that epidemiological evidence must be accompanied by something else, particular to the case at hand, if it is to have probative force for specific causation. It is argued that far from being epistemically irrelevant, to achieve correct and just outcomes it is in fact mandatory to take epidemiological evidence into account in deciding specific causation. Failing to consider such evidence when it is available leads to error and injustice. The conclusion is that in certain circumstances epidemiological evidence of RR > 2 is not necessary to prove specific causation but that it is sufficient. This “sufficiency” is confined to circumstances where there is no other evidence, as a way of getting clear on what the epidemiological evidence says. Once we have worked out what it says, this must be weighed against the other relevant evidence, if there is any.

This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their hypotheses. I argue that the mechanistic stance is indeed a bad methodology for causal inference. However, I detach and defend a mechanistic interpretation of causal generalisations in epidemiology as existence claims about underlying mechanisms.