Drivers for Policy Agreement in Nascent Subsystems: An Application of the Advocacy Coalition Framework to Fracking Policy in Switzerland and the UK

Abstract

The study of public policy deals with subsystems in which actors cooperate or compete to turn their beliefs into policy solutions. Yet, most studies concern mature subsystems in which the main actors and their allies and enemies can easily be identified. This paper tackles the challenge of studying nascent subsystems, in which actors have begun to engage in politics but are uncertain about other actors’ beliefs. Actors therefore find it relatively difficult to identify their allies and opponents. Focusing on the Advocacy Coalition Framework, we examine three main ways in which actors might agree to support the same policy design before they decide whether or not to form long-term relationships within advocacy coalitions: they see the issue through the same lenses, they follow leaders, or they know each other from earlier cooperation. We use the case of fracking policy in Switzerland and the UK as a key example, in which actors have begun to agree with each other, but where final policy outputs were not yet defined, and long-term relationships not yet observable. We find that, when dealing with new issues, actors strongly rely on former contacts rather than shared ideologies or leadership

Balancing Costs and Benefits of Collaboration in an Ecology of Games

“…In governance settings defined by acute management problems or crises, actors may limit themselves to fewer relationships for expediency, having neither the interest to expand on this set of relations nor the opportunity given the short timeframe imposed by the management context (Nohrstedt, ). Empirical research on public policy supports the notion that it is typical for actors to focus on more immediate issues in nascent policy systems, but that as these systems evolve actors may experiment with engaging in different venues as they work to define their core set of collaborators and venue participation strategies (Ingold et al, ; Pralle, ).…”

“…A large body of literature has grown around the study of self-organization in collaborative governance arrangements (e.g., Berardo & Lubell, 2016;Berardo & Scholz, 2010;Folke et al, 2005;McAllister et al, 2017;Ostrom, 2009). It is long recognized that collaborative initiatives take considerable time to develop and become effective (Gurney et al, 2014;Munck af Rosenschöld, Honkela, & Hukkinen, 2014;Sandström, Crona, & Bodin, 2014), yet few studies have directly addressed the influence of time on the capacity of actors to engage with multiple venues and other actors in governance networks (e.g., Fischer & Sciarini, 2013;Ingold et al, 2016). While there are multiple ways actors may work to improve their capacity for managing the inherent complexity of increasing actor and venue relationships, social learning is a key process that helps familiarize actors with the particular policy and management issues that characterize the social-ecological system (Pahl-Wostl, 2009;Pahl-Wostl et al, 2007), as well as the suite of actors and venues that comprise the institutional setting (Ingold & Fischer, 2014;Pralle, 2003).…”

Reconceptualizing the Policy Subsystem: Integration with Complexity Theory and Social Network Analysis

“…Stritch () examines a nascent policy subsystem and finds that, when advocacy communities are dichotomized, communities form quickly and there are lower‐level forms of collaboration despite eschewing the ten‐year window generally suggested for work utilizing the ACF . Ingold et al (), in more recent work, point out that studying only mature subsystems has left scholars blind to how subsystems form and lead to advocacy coalitions. That is, they seek to understand “how actors begin to agree with each other to support the same policy design, before they decide to cooperate regularly to secure shared policy beliefs and preferences” (Ingold et al, , p. 443).…”

“…Ingold et al (), in more recent work, point out that studying only mature subsystems has left scholars blind to how subsystems form and lead to advocacy coalitions. That is, they seek to understand “how actors begin to agree with each other to support the same policy design, before they decide to cooperate regularly to secure shared policy beliefs and preferences” (Ingold et al, , p. 443). They find that, when dealing with nascent subsystems, actors will rely more on former contacts than shared policy beliefs (or ideologies) because they struggle to identify their allies and opponents.…”

Insights from ‘policy learning’ on how to enhance the use of evidence by policymakers

“…Thus, individuals within a network cluster around narrations that utilize shared heuristics (also referred to as beliefs) as to the nature of the problem and the effectiveness and beneficiaries of specific solutions. This occurs in particular where individuals regularly collaborate (Ingold et al, 2016;Matti and Sandstrom, 2011). Zafonte and Sabatier (2004) argue that in such settings individuals perceive it as less costly to build and maintain collaborations with like-minded others (through reciprocity) that can help them realize long-term policy objectives than to defect from such a partnership for short-term gains.…”