Philosophical discussions on causal inference in medicine are stuck in dyadic camps, each defending one kind of evidence or method rather than another as best support for causal hypotheses. Whereas Evidence Based Medicine advocates invoke the use of Randomised Controlled Trials and systematic reviews of RCTs as gold standard, philosophers of science emphasise the importance of mechanisms and their distinctive informational contribution to causal inference and assessment. Some have suggested the adoption of a pluralistic approach to causal inference, and an inductive rather than hypothetico-deductive inferential paradigm. However, these proposals deliver no clear guidelines about how such plurality of evidence sources should jointly justify hypotheses of causal associations. In this paper, we develop the pluralistic approach along Hill's (1965) famous criteria for discerning causal associations by employing Bovens' and Hartmann's general Bayes net reconstruction of scientific inference to model the assessment of harms in an evidenceamalgamation framework.

Background: Evidence suggesting adverse drug reactions often emerges unsystematically and unpredictably in form of anecdotal reports, case series and survey data. Safety trials and observational studies also provide crucial information regarding the (un-)safety of drugs. Hence, integrating multiple types of pharmacovigilance evidence is key to minimising the risks of harm.Methods: In previous work, we began the development of a Bayesian framework for aggregating multiple types of evidence to assess the probability of a putative causal link between drugs and side effects. This framework arose out of a philosophical analysis of the Bradford Hill Guidelines. In this article, we expand the Bayesian framework and add "evidential modulators," which bear on the assessment of the reliability of incoming study results. The overall framework for evidence synthesis, "E-Synthesis", is then applied to a case study.Results: Theoretically and computationally, E-Synthesis exploits coherence of partly or fully independent evidence converging towards the hypothesis of interest (or of conflicting evidence with respect to it), in order to update its posterior probability. With respect to other frameworks for evidence synthesis, our Bayesian model has the unique feature of grounding its inferential machinery on a consolidated theory of hypothesis confirmation (Bayesian epistemology), and in allowing any data from heterogeneous sources (cell-data, clinical trials, epidemiological studies), and methods (e.g., frequentist hypothesis testing, Bayesian adaptive trials, etc.) to be quantitatively integrated into the same inferential framework.Conclusions: E-Synthesis is highly flexible concerning the allowed input, while at the same time relying on a consistent computational system, that is philosophically and statistically grounded. Furthermore, by introducing evidential modulators, and thereby breaking up the different dimensions of evidence (strength, relevance, reliability), E-Synthesis allows them to be explicitly tracked in updating causal hypotheses.

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Many philosophers hold that stakes affect ordinary knowledge ascriptions. Here’s a version of a pair of cases aimed at supporting this: Bob and his wife are driving home on Friday and considering whether to stop at the bank to deposit a check. The lines at the bank are very long and so Bob considers coming back on Saturday. In the low stakes version, nothing of importance hinges on whether the check is deposited; in the high stakes version, it is very important that the check be deposited. Bob’s wife asks whether the bank will be open on Saturday. Bob says he drove past the bank last Saturday, and it was open. However, his wife points out that banks sometimes change their hours. Bob says “I know the bank will be open tomorrow”. In the low stakes case, many philosophers maintain that Bob does indeed know that the bank will be open; in the high stakes case, these philosophers maintain that Bob is ignorant – his statement that he knows the bank will be open tomorrow is false. These philosophers also maintain that this pattern of judgments is what we would expect from competent speakers confronted with this and similar cases (e.g., Cohen, 1999, 2013; DeRose, 1992, 2009; Fantl and McGrath, 2002; Nagel, 2008; Rysiew, 2001; Stanley, 2005).\ud Though many philosophers agree that stakes play a role in ordinary knowledge ascriptions, there is disagreement about what explains this. One view, epistemic contextualism, holds that “to know” is a context sensitive verb and that the truth conditions for knowledge ascriptions can vary across conversational contexts (e.g., DeRose, 2009). For instance, Bob’s statement “I know the bank will be open tomorrow” can be true in low stakes contexts and false in high stakes contexts. Another view, interest-relative invariantism, denies that “to know” is a context sensitive verb and that the truth conditions for knowledge ascriptions vary according to conversational contexts. Instead, cases like the Bank cases show that practical factors—i.e., stakes—play a distinctive role in determining whether the knowledge relation obtains (e.g., Stanley, 2005). Yet another alternative, which we’ll call classical invariantism, denies that “to know” is a context sensitive verb and that practical factors, such as stakes, play a direct role in determining whether the knowledge relation obtains. Instead, stakes affect knowledge ascriptions only by affecting our assessment of factors that have traditionally been taken to constitute or be necessary for knowledge, such as e.g., belief, quality of evidence, etc. (e.g., Bach, 2005; Weatherson, 2005; Ganson, 2007; Nagel, 2008). If this is right, then the role of stakes in knowledge ascriptions fails to motivate such surprising views as epistemic contextualism or interest-relative invariantism. Naturally, epistemic contextualists and interest-relative invariantists deny this, claiming that even when the factors that have traditionally been taken to constitute or be necessary for knowledge are held fixed, stakes continue to play a role in ordinary kn...