Replication Data for: Learning in European Administrative Networks: a process to all or only to a few?
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
Replication Data for: Learning in European Administrative Networks: a process to all or only to a few?
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Identifier |
https://doi.org/10.7910/DVN/CTLGF9
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Creator |
Soares, Ana Carolina
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Publisher |
Harvard Dataverse
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Description |
Through the pooling and exchange of resources such as expertise, best practices, and knowledge between network participants, European Administrative Networks (EANs) are expected to play a significant role in enhancing policy learning. Yet, scarce empirical evidence has been presented concerning the learning process taking place within EANs. This paper addresses this gap through the analysis of the Network of the Heads of European Environmental Protection Agencies (EPA Network). Based on a unique survey dataset, social network analysis and exponential random graph models are used to trace the interaction patterns within the network and test which factors shape them. The analysis highlights the relevance of national political factors – i.e. the preferences of national governments and ministries – in shaping the learning processes taking place in the EPA Network. While the network is an important venue for disseminating knowledge between directly and indirectly connected actors, learning processes are mainly limited to like-minded peers.
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Subject |
Social Sciences
Social Network Analysis Exponential Random Graph Models Transgovernmental networks Environmental performance Political preference |
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Date |
2024-01-08
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Contributor |
Soares, Ana Carolina
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