Inferring Policy from Experiment was the title of a workshop held at the University of Kent on 15 May. There were three speakers:
Last week, there was a very interesting, and very wet, conference on Causation and Complexity in Sydney. This was the 10th Munich-Sydney-Tilburg Conference in the Philosophy of Science (MuST10). Some of the talks related to EBM+ and RWT. Before I introduce these talks, let’s review the difference between EBM+ and RWT:
This was the title of a very nice workshop at Durham on 3rd May, hosted by Julian Reiss. The aim of the work discussed here was to develop, propagate and understand methods for evaluating multifarious evidence.
Monika Schnitzer (Department of Economics, Ludwig-Maximilians-University of Munich) discussed a variety of methods for evaluating public policies, each of which tries to compare what happened after the policy was implemented with what would have happened had the policy not been implemented. Paul Pearce (Defence and Security Analysis Division, Defence Science and Technology Laboratory) explained the structure of a new approach to analysing evidence put in place by the military. He’s a keen advocate of systems thinking. I talked about the principle of total evidence in medicine, including the EBM+ approach. Then Sharon Crasnow (Norco College) talked about mixed methods in the social sciences – a combination of qualitative and quantitative methods – and argued that these support causal pluralism.
A fascinating workshop and a reminder of how difficult it is to amalgamate evidence in practice!
This 9th conference of the Munich-Sydney-Tilburg (MuST) conference series aims at gathering philosophers and scientists of the natural and social sciences in order to examine the theoretical and methodological issues involved in evidence evaluation, statistical inference and causal inference in relation to risk assessment and management in various disciplines, with a special attention to pharmacology. In particular, following questions will be on focus:
How should we collect, evaluate, and use evidence for the purpose of risk management and prevention? What methods should be adopted in causal inference for preventing harm? What kinds of scientific inferences are we allowed to draw from data-mining techniques? What are the relevant decision-theoretic dimensions involved in different kinds of risks, and what kinds of decision rules are more advisable in diverse contexts? What types of uncertainties can we identify when dealing with hazards?
These questions raise methodological concerns related to the data and tools available for risk measurement and modeling, the right kinds of interventions we should adopt in order to prevent or minimize it, and the best ways to gather, evaluate and combine different sources of knowledge. Furthermore, they are intimately connected with epistemological issues in the philosophy of science, and the foundations of statistics and probability.
Pharmacology is a particularly interesting field of investigation in these respects. Together with revolutionary successes, e.g. the discovery of penicillin, the history of pharmacology is also characterized by a series of tragic disasters (from the thalidomide to the rofecoxib case), which showcase the extreme variance of its scientific performance. Furthermore, pharmaceutical decisions are set in a complex environment where scientific uncertainty, conflicts of interests, and regulatory constraints strongly interact. The workshop intends to investigate these phenomena in light of the current methodological and philosophical debate.
This series of annual conferences is a joint undertaking between the Sydney Centre for the Foundations of Science (SCFS), the Tilburg Center for Logic and Philosophy of Science (TiLPS) and, since 2012, the MCMP. For a list of previous conferences, click here.
More information about the MuST9 Conference here
EBM+ Participants in the MuST9 conference
- Phyllis Illari: “Who´s Afraid of Mechanisms?“
- David Teira, Brendan Clarke, Maël Lemoine: “Taking the Risks of Testing Personalized Treatments“
- Plenary Session: Jon Williamson: “Establishing Causal Claims in Medicine“
- Christian Wallmann: “Three Methods for Solving the Problem of Inconsistent Marginals in Data Integration“.