Theorizing the functions and patterns of agency in the policymaking process

Giliberto Capano et al.

Policy Science2025https://doi.org/10.1007/s11077-024-09563-4article
AJG 1ABDC B
Weight
0.56

What the paper says

Abstract Theories of the policy process understand the dynamics of policymaking as the result of the interaction of structural and agency variables. While these theories tend to conceptualize structural variables in a careful manner, agency (i.e. the actions of individual agents, like policy entrepreneurs, policy leaders, policy brokers, and policy experts) is left as a residual piece in the puzzle of the causality of change and stability. This treatment of agency leaves room for conceptual overlaps, analytical confusion and empirical shortcomings that can complicate the life of the empirical researcher and, most importantly, hinder the ability of theories of the policy process to fully address the drivers of variation in policy dynamics. Drawing on Merton’s concept of function, this article presents a novel theorization of agency in the policy process. We start from the assumption that agency functions are a necessary component through which policy dynamics evolve. We then theorise that agency can fulfil four main functions – steering, innovation, intermediation and intelligence – that need to be performed, by individual agents, in any policy process through four patterns of action – leadership, entrepreneurship, brokerage and knowledge accumulation – and we provide a roadmap for operationalising and measuring these concepts. We then demonstrate what can be achieved in terms of analytical clarity and potential theoretical leverage by applying this novel conceptualisation to two major policy process theories: the Multiple Streams Framework (MSF) and the Advocacy Coalition Framework (ACF).

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https://doi.org/https://doi.org/10.1007/s11077-024-09563-4

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@article{giliberto2025,
  title        = {{Theorizing the functions and patterns of agency in the policymaking process}},
  author       = {Giliberto Capano et al.},
  journal      = {Policy Science},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s11077-024-09563-4},
}

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Evidence weight

0.56

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.55 × 0.4 = 0.22
M · momentum0.75 × 0.15 = 0.11
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.