Policy Beliefs, Belief Uncertainty, and Policy Learning

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Within the Advocacy Coalition Framework (ACF), policy-oriented learning is understood as a change in policy beliefs. Additional work has noted that belief reinforcement, not just belief change, is also a potential policy learning outcome. Yet, little work has attempted to reconcile how learning could involve both belief change and belief reinforcement. In this paper, I propose a policy-oriented learning model where policy beliefs – deep core, policy core, or secondary aspects – are understood as having a distribution with a central tendency (i.e., the belief) as well as variance (i.e., certainty associated with the belief). With policy beliefs considered as distributions, learning can be understood as changes in beliefs (i.e., a change in the central tendency) as well as changes in certainty (i.e., variance) such as a decrease in belief uncertainty (i.e., reinforcement). Using data from a deliberative forum that brought together various stakeholders including experts, natural resource managers, and the public to discuss environmental issues impacting coastal communities, I explore changes in concern regarding several key coastal issues before and after the forum. Additionally, I examine the association between concern following the forum and self-reported learning. I find support for the proposed policy-oriented learning model as shown by significant changes in average concern as well as average variance among participants across several of the issues discussed.

Previous Version

An earlier version of this paper was presented at the Conference on Policy Process Research in January, 2023.

COPPR 2023 paper COPPR 2023 slides