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. (shrink)

When is a cause of a cause of an effect also a cause of that effect? The right answer is either Sometimes or Always . In favour of Always , transitivity is considered by some to be necessary for distinguishing causes from redundant non-causal events. Moreover transitivity may be motivated by an interest in an unselective notion of causation, untroubled by principles of invidious discrimination. And causal relations appear to add up like transitive relations, so that the obtaining of the (...) overarching relation is not independent of the obtaining of the intermediaries. On the other hand, in favour of Sometimes , often we seem not to treat events that are very spatiotemporally remote from an effect as its causes, even when connected to the effect in question by a chain of counterfactual or chance-raising dependence. Moreover cases of double prevention provide counterexamples to causal transitivity even over short chains. According to the argument of this paper, causation is non-transitive. Transitizing causation provides no viable account of causal redundancy. An unselective approach to causation may motivate resisting the distance counterexamples to transitivity, but it does not help with double prevention, and even makes it more intractable. The strongest point in favour of transitivity is the adding up of causal relations, and this is the point that extant non-transitizing analyses have not adequately addressed. I propose a necessary condition on causation that explains the adding up phenomenon. In doing so it also provides a unifying explanation of distance and double prevention counterexamples to transitivity. (shrink)

This paper takes it as a premise that a distinction between matters of fact and of law is important in the causal inquiry. But it argues that separating factual and legal causation as different elements of liability is not the best way to implement the fact/law distinction. What counts as a cause-in-fact is partly a legal question; and certain liability-limiting doctrines under the umbrella of “legal causation” depend on the application of factual-causal concepts. The contrastive account of factual causation proposed (...) in this paper improves matters. This account more clearly distinguishes matters of fact from matters of law within the cause-in-fact inquiry. It also extends the scope of cause-in-fact to answer some questions currently answered by certain doctrines of legal causation—doctrines that, it is argued, are more naturally seen as applications of our ordinary causal concept than as noncausal liability-limiting devices. (shrink)

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. (shrink)

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. (shrink)

In this article I seek to say what it is for something to count as a neglected disease. I argue that neglect should be defined in terms of efforts at prevention, mitigation and cure, and not solely in terms of research dollars per disability-adjusted life-year. I further argue that the trend towards multifactorialism and risk factor thinking in modern epidemiology has lent credibility to the erroneous view that the primary problem with neglected diseases is a lack of research. A more (...) restrictive contrastive model of disease is endorsed as better suited to the definition of neglected disease. (shrink)