Policy Learning and Information Processing

Nowlin, Matthew C.

doi:10.1111/psj.12397

Cited by 19 publications

(12 citation statements)

References 37 publications

(48 reference statements)

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“…In this context, information about the effects of a policy may come from policy evaluations. This definition is based on information processing in the Bayesian framework and used in policy process research until today (e.g., Nowlin, 2021). Another definition of policy learning is more encompassing.…”

Section: Evaluation Use As Political-and Policy Learningmentioning

confidence: 99%

Evaluation use and learning in public policy

Bundi

Trein

2022

Policy Sci

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Scientific evidence has become increasingly important for the decision-making processes in contemporary democracies. On the one hand, research dealing with the utilization of scientific knowledge in the political process has pointed out that decision-makers learn from evidence to improve policies to solve problems. On the other, scholars have underlined that actors learn from evidence to support their political interests regardless of how it affects the policy problem. One conventional insight from the policy learning literature is that higher salience of a policy issue makes it much less likely that decision-makers use evidence in an “unpolitical” way. Nevertheless, only few studies have investigated systematically how differences regarding issue salience between policy fields impact on how decision-makers learn from evaluations at the individual level. Using multilevel regression models on data from a legislative survey in Switzerland, this paper shows that salience and technical complexity of policy issues do not automatically lead to less policy learning and to more political learning from policy evaluations. Nevertheless, this article’s empirical analysis also points out that issue salience increases policy learning from evaluations if the policy issue is technically complex. Our findings contribute to research on policy learning and evidence-based policy making by linking the literature on policy evaluation and learning, which helps analyzing the micro-foundations of learning in public policy and administration.

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Section: Evaluation Use As Political-and Policy Learningmentioning

confidence: 99%

Evaluation use and learning in public policy

Bundi

Trein

2022

Policy Sci

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“…Specifically, they find that core causal lessons are transferred to the current policy being considered among policymakers and thereby shape discussion and debate. This insight helps explain why and how specific policy solutions are privileged over others and offers important contributions to the literature surrounding policy learning (e.g., Nowlin, 2020).…”

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confidence: 91%

Editorial Introduction: Exploring policy diffusion, collaborative governance, and policy conflict

Jones¹,

Song²,

Arnold³

et al. 2021

Policy Studies Journal

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“…Advocacy Coalition Framework (ACF) is one of the most sophisticated subsystem approaches to information exchange and policy learning within the policy process (Nowlin 2021). The ACF specifies that policy actors having shared policy beliefs and resources form advocacy coalitions to translate their beliefs into policy changes within a subsystem.…”

Section: Introductionmentioning

confidence: 99%

Identity-based subgroups and information exchange in adversarial policy networks

Lee

Huang

2022

J. Pub. Pol.

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While information exchange is essential in the policy process, little is known about how divergent subgroups filter actors’ technical and political information exchange, blocking learning processes. Guided by social identity, group entitativity, and self-categorisation theories, we introduce the concept and measurement of identity-based subgroups referring to informal clusters shaped by the self-referent perception of similarities among actors. The identity-based subgroup is recognised as a precursor for coalition building in a policy subsystem but received inadequate attention in the research on Advocacy Coalition Framework. We examine how divergent identity-based subgroups moderate the links between relational embeddedness and technical/political information exchanges in an adversarial fracking policy network in New York. Our quadratic assignment procedure multiple regression indicated that, despite trust, policy actors from different identity-based subgroups are less likely to share technical and political information in the network. When two actors’ identity-based subgroups are different, competition is more likely associated with lower technical information exchange in the network. These findings extend research on information exchange in adversarial policy subsystems.

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Policy Learning and Information Processing

Cited by 19 publications

References 37 publications

Evaluation use and learning in public policy

Evaluation use and learning in public policy

Editorial Introduction: Exploring policy diffusion, collaborative governance, and policy conflict

Identity-based subgroups and information exchange in adversarial policy networks

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