Diagnosing individual barriers to collective learning: how governance contexts shape cognitive biases
Name:
Learning Barriers JEPP Policy ...
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Final Accepted Manuscript
Affiliation
School of Geography, Development and Environment and Udall Center for Studies in Public Policy, University of ArizonaIssue Date
2023-09-14Keywords
Public Administrationcognitive biases
collective learning
governance
Policy learning||public policy
Metadata
Show full item recordPublisher
Informa UK LimitedCitation
Heikkila, T., Gerlak, A. K., & Smith, B. (2023). Diagnosing individual barriers to collective learning: how governance contexts shape cognitive biases. Journal of European Public Policy, 1-24.Rights
© 2023 Informa UK Limited, trading as Taylor & Francis Group.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
A growing body of public policy and governance scholars recognise the importance of learning in supporting adaptive and responsive governance systems. Fostering learning within policy processes and governance systems, however, can be challenging. Collectively, we often ignore or misinterpret relevant policy information, or we may be incapable of translating new information into policy. Despite significant scholarly attention to learning, knowledge of the barriers to learning remains underdeveloped. To advance theoretical insights, this article integrates research on individual cognitive biases with literature on learning to identify barriers that can block learning or lead to non-learning in policy and governance processes. It also explores how these barriers can be mitigated or exacerbated by different governance contexts. Based on these insights, this paper provides guidance for researchers on how to empirically assess learning barriers across different governance contexts.Note
18 month embargo; first published: 14 September 2023ISSN
1350-1763EISSN
1466-4429Version
Final accepted manuscriptae974a485f413a2113503eed53cd6c53
10.1080/13501763.2023.2251525