All going well, it will be out in November 2019. We are now at the proofing stage.
There is an excellent article by Professor Claire Dunlop called “The irony of epistemic learning: epistemic communities, policy learning and the case of Europe’s hormones saga” (Open Access). It uses the language of ‘policy learning’ rather than ‘evidence based policymaking’, but these descriptions are closely related. I describe it below, in the form I’ll use in the 2nd ed of Understanding Public Policy (it will be Box 12.2).
Dunlop (2017c) uses a case study – EU policy on the supply of growth hormones to cattle – to describe the ‘irony of epistemic learning’. It occurs in two initial steps.
First, a period of epistemic learning allowed scientists to teach policymakers the key facts on a newly emerging policy issue. The scientists, trusted to assess risk, engaged in the usual processes associated with scientific work: gathering evidence to reduce uncertainty, but always expressing the need to produce continuous research to address inevitable uncertainty in some cases. The ‘Lamming’ committee of experts commissioned and analysed scientific evidence comprehensively before reporting (a) that the use of ‘naturally occurring’ hormones in livestock was low risk for human consumers if administered according to regulations and guidance, but (b) it wanted more time to analyse the carcinogenic effects of two ‘synthetic compounds’ (2017c: 224).
Second, a period of bargaining changed the context. EU officials (in DG Agriculture) responded to European Parliament concerns, fuelled by campaigning from consumer groups, which focused on uncertainty and worst-case scenarios. Officials suspended the committee’s deliberations before it was due to report and banned the use of growth hormones in the EU (and the importation of relevant meat).
The irony is two-fold.
First, it results from the combination of processes: scientists, operating in epistemic mode, described low risk but some uncertainty; and policymakers, operating in bargaining mode, used this sense of uncertainty to reject scientific advice.
Second, scientists were there to help policymakers learn about the evidence, but were themselves unable to learn about how to communicate and form wider networks within a political system characterised by periods of bargaining-driven policy learning.