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Well-resourced and well-connected individuals, or “policy entrepreneurs,” often play an important role in advocating and securing the adoption of policies. There is a striking lack of inquiry into the ways that social networks shape the ability of these actors to achieve their aims, including the ways in which network ties may channel policy conflict. To address these gaps, we analyze data from an original survey and an original database of policies to assess the success of policy entrepreneurs active in a highly contentious arena: municipal policymaking concerning high-volume hydraulic fracturing (HVHF) in New York. We use text-mining to collect social network data from local newspaper archives, then use those data to construct municipal HVHF policy networks. Municipal anti-HVHF policy entrepreneurs appear more successful when they operate in less cohesive networks, act as bridges to relative newcomers to the governance network, and have a larger number of network connections. Pro-HVHF policy entrepreneurs appear more successful when they can forge high-value connections to key decision-makers. Policy entrepreneurs on both sides of the issue are more successful when they have a greater number of sympathetic coalition partners.
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SPID: A New Database for Inferring Public Policy Innovativeness and Diffusion Networks
Despite its rich tradition, there are key limitations to researchers' ability to make generalizable inferences about state policy innovation and diffusion. This paper introduces new data and methods to move from empirical analyses of single policies to the analysis of comprehensive populations of policies and rigorously inferred diffusion networks. We have gathered policy adoption data appropriate for estimating policy innovativeness and tracing diffusion ties in a targeted manner (e.g., by policy domain, time period, or policy type) and extended the development of methods necessary to accurately and efficiently infer those ties. Our state policy innovation and diffusion (SPID) database includes 728 different policies coded by topic area. We provide an overview of this new dataset and illustrate two key uses: (i) static and dynamic innovativeness measures and (ii) latent diffusion networks that capture common pathways of diffusion between states across policies. The scope of the data allows us to compare patterns in both across policy topic areas. We conclude that these new resources will enable researchers to empirically investigate classes of questions that were difficult or impossible to study previously, but whose roots go back to the origins of the political science policy innovation and diffusion literature.
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- PAR ID:
- 10457799
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Policy Studies Journal
- Volume:
- 48
- Issue:
- 2
- ISSN:
- 0190-292X
- Page Range / eLocation ID:
- p. 517-545
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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