Abstract
Scientists often worry that their evidence is not used properly in the policy-making process. Their main response is to change the supply of evidence to reduce policymaker uncertainty. They should focus more on ambiguity, combining evidence and persuasion to help policymakers define the policy problem. To do so, they need to understand the policy process in which they engage. They cannot do so alone. Policy scholars can help, by articulating the practical value of policy theories. To help most effectively, they need to state clearly the “causal mechanisms” of the policy process. For example, what causes policymakers to pay attention to an issue informed partly by evidence, or what rules guide their behavior most strongly when weighing up evidence with other factors? In this paper, we show that policy theories have informed this debate, but often without making explicit statements of causality. We draw on the social science causal mechanisms field to improve such analysis and suggest use qualitative methods to clarify and measure causal mechanisms to benefit policy scholars and the wider policy analysis community. A focus on mechanisms can inform policy scholarship, science community engagement and on-the-ground policy work.
Highlights
Scientists often worry that their evidence is not used properly in the policy-making process
A large literature on the “barriers” to evidence impact on policy, and exemplar commentaries, blame decisionmakers for failing to make decisions based on the best evidence (Oliver, Lorenc, and Innvaer 2014; Sutherland and Wordley 2017)
Within government departments, there has been a focus on increasing “analytical policy capacity” in order to enhance the possibility of policy success by improving the amount and type of information processed in public policy decision-making (Howlett 2009, 157)
Summary
Weible and Sabatier (2018) argues that “causal drivers” are at the heart of the scientific assumptions underlying policy theories. Causation is often implied or sketched, and there are few explicit discussions of causal mechanisms (Yee 1996; Johns 2003; Steinberg 2007; Real-Dato 2009; Nowlin 2011; Kay and Baker 2015) Bunge described such incomplete theorizing as a “gray box theory” where causality is assumed but the mechanisms are poorly described and hypotheses are often infrequently tested Morgan and Winship (2014) describe “mechanism sketches” in contrast to “mechanism schema” where the component parts or entities are known. This is the possibility that contributors to the literature using policy-process frameworks may engage in implicit mechanistic thinking even if they do not explicitly use mechanism language, when operationalizing frameworks for empirical studies. Identifying causal mechanisms helps us to explain how and why some evidence-advocacy strategies have the desired effect and others are resisted
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