Advocacy coalitions, beliefs, and learning: An analysis of stability, change, and reinforcement

Abstract

Policy processes are ongoing phenomena without beginning or end. Accordingly, a major focus of research has been on questions of stability and change. This paper continues in this tradition by examining advocacy coalition stability, belief change, and learning. This paper draws on three waves of policy actor surveys that compare panel and non-panel samples. The data were collected in 2013, 2015, and 2017 in the context of oil and gas development in Colorado, USA. The findings mostly confirm that coalitions and beliefs tend to be stable and that learning leans toward reinforcement rather than change in beliefs. However, although rare, some instances of belief change, change in coalition membership, and changing policy positions occur. This paper makes theoretical and empirical contributions to the study of stability, change, and reinforcement of advocacy coalitions and their beliefs and charges policy scholars to look more at the exceptions to the evidence rather than the confirmations.

Analysing the stability of advocacy coalitions and policy frames in Ghana’s oil and gas governance

“…Zafonte and Sabatier's (2004) analysis of the US automotive pollution policy subsystem found coalitions that were stable for more than 26 years. Findings from these and other studies, therefore, demonstrate that ACF's coalition stability hypothesis is well-documented (Smith 2000;Nohrstedt 2010;Li and Wong 2020;Weible et al, 2022).…”

Examining experts' discourse in South Korea's nuclear power policy making: An advocacy coalition framework approach to policy knowledge

“…A criticism of the ACF argues that it does not shed light on the role of policy knowledge, and its focus is only in connection with learning (James & Jorgensen, 2009). However, the empirical and theoretical work under the ACF on policy knowledge includes analyzing the effects of academic disciplines and scientific‐based beliefs on belief systems (Barke & Jenkins‐Smith, 1993; Weible et al, 2004; Weible & Moore, 2010), uses of expert‐based information by coalitions often for policy change (Funke et al, 2021; Heintz & Jenkins‐Smith, 1988; Lodge & Matus, 2014; Nohrstedt, 2013; Weible et al, 2010), analyses of levels of conflict, institutional rules, venues concerning expert‐based information and learning (Anderson & MacLean, 2015; Jenkins‐Smith, 1990; Weible et al, 2022; Weible & Sabatier, 2009), and analyses of experts' roles in advocacy coalitions and perceptions of them by other coalition members (Funke et al, 2012; Ingold & Gschwend, 2014; Jenkins‐Smith, 1988; Kukkonen et al, 2017; Montpetit, 2011; Rietig, 2018; Weible, 2007). These studies stand apart from other ACF research on learning, coalitions, and policy change by focusing on experts and expert‐based information, though the overlap with these more mainstream theoretical emphases in the ACF is apparent.…”

Mitigating conflict with collaboration: Reaching negotiated agreement amidst belief divergence in environmental governance

“…However, high levels of conflict can become destructive, leading to policy gridlock and undermining the foundational goals of democracy. Thus, analyzing why policy conflict occurs and how it may be alleviated has become a major focus of policy scholarship (Nie, 2003; Sotirov et al, 2017; Weible & Heikkila, 2017; Weible et al, 2022). One leading explanation for policy conflict is belief divergence (Jenkins‐Smith et al, 2018).…”

“…Beliefs are notoriously difficult to change, however. Not only are they tied to deep‐seated worldviews but boundedly rational actors often assimilate new information in a biased manner that reinforces, rather than challenges, their existing beliefs (Henry, 2011; Jenkins‐Smith et al, 2014; Weible et al, 2022). Collaborative processes can also enhance trust and social capital among policy actors (Leach & Sabatier, 2005), which may increase individuals' willingness to negotiate with others who hold persistently divergent beliefs (Weible & Heikkila, 2017).…”