Reducing ambiguity to close the science-policy gap
Adam Wellstead, Paul Cairney, Kathryn Oliver
Abstract
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Adam Wellstead, Paul Cairney, Kathryn Oliver
Abstract
Open-access reader
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.
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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.
Key concepts: Ambiguity, Worry, Causality (physics), Process (computing), Persuasion, Positive economics, Evidence-based policy, Scholarship