The Advocacy Coalition Framework

Scholars and practitioners who seek to understand collective decision-making and governance utilize frameworks and theories to identify what matters (and does not) in shaping public policy creation, implementation, and revision. Useful frameworks and theories will attempt to identify the primary elements of the policy-making process and characterize the critical interactions among them. The Advocacy Coalition Framework (ACF) was developed for that purpose. In the four decades since its first articulation in the early 1980s, the Framework has been widely applied, criticized, and revised in cases across the globe. This chapter briefly recounts that development and evolution, highlighting key milestones and adaptations that have shaped its current form. We present the three main theories embedded in the Framework and offer a characterization of the “textbook” version of the ACF that one is likely to encounter in overviews, applications, and courses on theories of the policy process. We then provide an overview of this volume's empirical chapters, highlighting a cross-section of the most exciting new scholarly developments within and outside this textbook version.

According to the ACF, policy core beliefs are the glue that holds coalitions together. What happens to coalition structures when policy beliefs change over time? To answer this question, we analyze the Finnish climate change policy subsystem before and after the Paris Agreement. Using panel survey data and methods of social network analysis we find that the coalition structure remains fairly similar, despite the fact that many collaboration ties are severed and new ones are formed. Disagreement between coalitions shifts from fundamental value priorities (economy vs. ecology) to specific policy issues (deforestation, peat as an energy source). The relative stability of coalitions despite belief changes is explained by the fact that newly divisive beliefs are correlated with those that were previously divisive, and by the fact that actors often extend their existing set of collaboration ties based on triadic closure, making the coalition structure path dependent.

Participants of the policy process coordinate with one another to share resources, take joint action, and learn about salient problems. These patterns of coordination, known as policy networks, may also co-occur with policy advocacy, where actors coordinate with the intention of jointly influencing policy change. While the concepts of policy networks and advocacy coalitions are related, they are distinct phenomena. This chapter applies the Advocacy Coalition Framework (ACF) to test where policy networks and coalition boundaries overlap. According to the ACF, most policy networks will exist within coalition boundaries. Egocentric social network analysis is applied to survey data from policy actors in the U.S. Environmental Risk policy subsystem, individuals we refer to as risk professionals, and find that the majority of coordinated policy-related activities take place outside of coalitions. This result varies in strength across types of coordination. High-stakes activities show a stronger relationship with coalition ties than low-stakes activities.

(Sievers and Jones in JAMA 2(1): 90-114, 2020) argue that theories of policy change must grapple with the concept of power and its role in policy-making. ACF policy change theory (PCT) addresses power most directly in its second hypothesis which posits a causal link between advocacy coalitions ‘in power in a jurisdiction’ and major policy change.

Most studies of policy change within the ACF have been descriptive, single-instance explorations that confirm one or more of its four pathways: external shocks, internal shocks, negotiated agreements, and policy-oriented learning. To advance ACF studies of policy change, this chapter takes a different approach to assessing the drivers of change. Rather than looking to confirm one of the four pathways for a single instance of change, we inductively explore what policy actors cite as “antecedents”—or potential influencing, motivating, or driving factors—for multiple policy changes in a textbook subsystem. We identify antecedents through policy actor references in the public discourse related to 77 new or modified policies in the Colorado oil and gas subsystem between 2007 and 2021, drawing on public and government documents, public testimony, and news articles. We then compare the inductively identified antecedents of each policy change with the four pathways of change outlined within the ACF. We find references to internal antecedents were the most commonly mentioned, followed by references to external antecedents. We conclude by discussing the significance of these results for studying policy change, the importance of including both inductive and deductive methods to expand the existing pathways, and guidelines for conducting a medium-sized analysis of policy change over time.

Relatively enduring institutional parameters that might influence the policy process have been incorporated into the ACF under the umbrella of “coalition opportunity structures” (COS). The concept can help policy scholars better understand the role of institutional factors in the policy process, including coalition formation, behavior, and ultimately policy change. However, the notion of COS needs theoretical refinement as well as empirical measurement. This chapter theorizes about how COS enable or constrict the ability of actors to influence policy change by reinforcing, challenging, and, in some cases, overturning the policy status quo. In addition, we address the dynamic nature of COS, which can lead to changes in the institutional arrangements within which coalitions compete to shape policy. We explore our theory by examining the historic impact of COS on nuclear facility siting in the US.

Policy-oriented learning is a significant component of the Advocacy Coalition Framework (ACF) and one of the pathways to policy change. In brief, policy-oriented learning involves the development of or changes in policy-relevant beliefs. Additionally, the outcomes of policy-oriented learning include both belief change and belief reinforcement. Recent work noted that beliefs can be understood as probability distributions with a central tendency (the belief) and variance (uncertainly about the belief). Belief reinforcement occurs when variance is reduced, and learning occurs when the central tendency shifts as a result of information processing. However, the nature of the information environment likely impacts information processing and learning, yet this has largely not been examined. Information environments include the type (e.g., science/technical, political) and availability (e.g., held within epistemic communities, widely available) of possibly relevant information for policymaking. In this chapter, I combine a decade’s worth of public opinion data from 2013 to 2023 to examine beliefs among the public regarding the issues of climate change and nuclear energy. Climate change and nuclear energy are complex issues that involve scientific and technical information and both are politically polarized, though nuclear energy is less polarized than climate change. However, the information environments differ as climate change is featured much more than nuclear energy in media coverage, congressional hearings, and political speeches. I found that learning occurred for both issues between 2013 and 2023 as measured by a significant shift in the mean of risk perceptions; however, learning as belief reinforcement did not occur. Indeed, variance increased for both issues, which reflects increased uncertainty. Examining learning across deep core beliefs (cultural worldviews, environmental orientation, and political ideology), I found learning across deep core beliefs and issues, but uncertainty increased regarding nuclear energy, the issue with less available information. These findings point to the need to consider the role of information environments and uncertainty in policy learning.

The ACF posits policy actors' beliefs play a crucial role in shaping policy change dynamics. Policy is a rough translation of beliefs, thereby putting individual and collective values into the practice of shaping society. However, critiques have argued the ACF (1) neglects theoretic consideration of the role democracy plays in the policy process and (2) provides an underdeveloped conceptualization of actors’ policy-oriented belief systems. This chapter addresses these critiques simultaneously because individual beliefs about democracy can vary widely within a democratic society, thus providing an opportunity to explore a novel dimension of variation in policy actor beliefs under the ACF. Using a grounded theory approach, this study examines in-depth policy actor interviews from two municipal housing policy subsystems and finds actors hold diverse beliefs about democracy and most apply their democracy-oriented beliefs to multiple tiers of their policy-oriented beliefs. The ACF has overlooked the importance of the relationship between democracy- and policy-oriented beliefs.

The ACF is well-known for its policy change theory, which hypothesizes multiple pathways to policy change, including imposition of policy change by a “hierarchically superior jurisdiction.” And yet little explicit attention has been paid to the multi-level nature of coalition-based activity in a federal, and inherently nested, subsystem. This study examines how national coalitions used a variety of resources and related strategies to influence state-level policy change in the context of a low-salience social policy subsystem: Day Habilitation and Employment services for individuals with Intellectual and Developmental Disability. The study relies on qualitative data and a process-tracing approach to illuminate the mechanisms of policy change in a nested subsystem.

Now and then, new issues arrive on the public agenda, such as a sudden health crisis or a disruptive technology. These issues get media attention, and the political actors start thinking about how to best address them. Following the Advocacy Coalition Framework (ACF), such situations can be grasped through the concept of nascent subsystems, which contrast with mature subsystems that have been around for some time and that deal with established issues. Over time, nascent subsystems can develop into autonomous subsystems, or they can be absorbed by an already mature subsystem.

The role of political resources is helpful in defining a coalition, supporting policy learning, and influencing policy change. This chapter conceptually defines political resource interrelationships and their value to the policy process by examining how coalitions leverage them. Advocacy coalition behavior around the U.S. Violence Against Women Act of 1994 and its four subsequent reauthorizations serve as the study context. The authors use a directed content analysis of evidence documenting four decades of coalition activity. The findings provide three contributions to ACF development. First, the data sources internal to the coalition and data sources external to the coalition tell different stories about coalition behavior. Second, a coalition's control over a resource determines its ability to allocate or influence the resource. Finally, resource usage must be assessed in the context of policy issue type and technological eras.

Over 30 years ago, Paul Sabatier and Hank Jenkins-Smith edited a seminal volume that described and applied the Advocacy Coalition Framework (ACF). Building on over three decades of subsequent research on the ACF, this volume's primary contribution comes from an orientation to ACF scholarship that involves distinctions between textbook and non-textbook applications. This orientation raises a question: What adjustments do scholars make when applying the ACF outside its textbook “comfort zone”? This chapter addresses this question with the following argument: The ACF has always simplified and structured the complexity of policy processes by implicitly situating subsystems and the broader system architecture on key conceptual scales and levels, wherein the placement of the textbook ACF is just one possible (albeit very useful) configuration among many. When researchers apply the ACF outside the textbook context, they consciously or unconsciously adjust these levels or operate on entirely different scales and levels. Moving forward, critical tasks for ACF scholars will be to make these scales and levels explicit, recognize the configurations that apply to any given research project, engage in conduct cross-scale and cross-level research, and focus inquiry into which scales and levels are most crucial in advancing knowledge about policy processes and contributing to a better world.