Open Science at the Science-policy Interface: Bringing in the Evidence?

Abstract

Part of the current enthusiasm about Open Science stems from its promises to reform scientific practicein service of the common good, to ensure that scientific outputs will be found and reused more easily,and to enhance scientific impact on policy and society. With this article, we question this optimism byanalysing the potential for Open Science practices to enhance research uptake at the science-policyinterface. Science advice is critical to help policy makers make informed decisions. Likewise, someinterpretations of Open Science hold that making research processes and outputs more transparent andaccessible will also enhance uptake of results by policy and society at large. However, we argue thatthis hope is based on an unjustifiably simplistic understanding of the science-policy interface that leaveskey terms (“impact”, “uptake”) undefined. We show that this understanding – based upon linear modelsof research uptake – likewise grounds the influential "evidence-policy gap" diagnosis which holds thatto improve research uptake, communication and interaction between researchers and policymakers needto be improved. The overall normative stance of both discussions has side-lined empirical descriptionof the science-policy interface, ignoring questions about the underlying differences between the policydomain and academia. Importantly, both Open Science and literature on closing the evidence-policy gaprecommend improving communication (either in terms of the content or the means) as a viable strategy.To correct some of these views, we combine insights from policy theory with a systematic review of theliterature on the evidence-policy gap in the health domain and find that removing barriers to access byitself will not be enough to foster research uptake.

The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray

“…Third, because we are offering practical solutions to public policy problems, such as those offered in Tables 1 and 2 of the target article, as applied by behavioural scientists, we confront the world of policy making. Maintaining a naïve understanding of the science-policy interface, where accessibility of evidence is viewed as a key to successful implementation (Reichmann & Wieser, 2022) is a considerable barrier to estimating realistic success rates of behavioural change interventions. We might think that the use of evidence works through what is often referred to as the policy cycleagenda setting, policy formation, decision making, policy implementation, and policy evaluation (Lasswell, 1956).…”