10
The advocacy coalition framework
Coalitions, learning and policy change
Christopher M. Weible and Daniel Nohrstedt
Introduction
Policy process research is the study of public policy over time and the surrounding actors, contexts,
and events. The formal academic study of policy processes began in the 1950s and 1960s,
led by the likes of Lerner and Lasswell (1951), Freeman (1955), Simon (1957), Lindblom (1959),
Dawson and Robinson (1963), Easton (1965), Ranney (1968), and Walker (1969). Policy process
research sprung, in part, from dissatisfaction with political scientists’ focus on governing
institutions (courts, legislatures, and executives), a theoretical desire to understand broader
political systems, optimism following successes of the social sciences during World War II, and a
practical desire to benefit society.
Since the 1960s, a number of complementary research programs have emerged for describing
and explaining various aspects of policy processes (e.g. Sabatier 1999, 2007). Among these
research programs is the advocacy coalition framework (ACF) created by Paul Sabatier and
Hank Jenkins-Smith in the 1980s (Sabatier 1987, 1988; Jenkins-Smith 1990; Sabatier and JenkinsSmith
1993, 1999).1
Sabatier and Jenkins-Smith established the ACF in response to several
perceived shortcomings in policy process research: a dissatisfaction with the policy cycle or stages
heuristic as a causal theory; a need to take more seriously the role of scientific and technical
information in policy processes; dissatisfaction with the top-down and bottom-up perspectives
of the implementation literature; a need to take a long-term time perspective to understand
policy processes; and a need to develop theories that assume more realistic human agents other
than the rational actor models found in microeconomics.
The ACF resulted as an amalgam inspired partly from previous studies of issue networks (Heclo
1978), implementation (Pressman and Wildavsky 1973; Mazmanian and Sabatier 1981; Hjern
and Porter 1981), learning (Heclo 1974; Weiss 1977), policy subsystems (Griffith 1939; Freeman
1955), belief systems (Ajzen and Fishbein 1980; Putnam 1976; Peffley and Hurwitz 1985; Hurwitz
and Peffley 1987), scientific and technical information in policy debates (Mazur 1981; JenkinsSmith
1990), and a model of the individual based on bounded rationality and cognitive filters
(Simon 1957). The ACF serves as an analytical guide for answering questions principally about
advocacy coalitions, policy-oriented learning, and policy change.
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The framework
Following Laudan (1977: 70–120) and Ostrom (2005: 27–9), frameworks serve as a platform for
groups of scholars to work together toward common understandings and explanations of phenomena.
Frameworks provide assumptions, specify the scope of inquiry, and establish conceptual
categories with basic definitions and general relations. Frameworks support the development
and testing of theory that, in turn, narrow the scope of inquiry, offer testable hypotheses, and
postulate causal relationships among concepts. This section introduces the ACF as an actual
“framework” by describing its assumptions, scope, and the basic concepts and the general relations
among them. The next sections describe the major theoretical emphases supported by the ACF.
Assumptions
Sabatier and Jenkins-Smith based the ACF on several foundational assumptions (1993: 17–20):
The policy subsystem is the primary unit of analysis for understanding policy processes. Policy subsystems
are defined by a substantive topic and territorial domain along with a set of people actively
involved in shaping subsystem affairs. Subsystems are simultaneously semi-autonomous while also
nested and interdependent (Sabatier 1998; Nohrstedt and Weible 2010). For example, a water policy
subsystem at local level will likely be nested in a regional policy subsystem which is nested
within a national policy subsystem. This same water policy subsystem at a local level overlaps to
various extents with other subsystems (e.g. a local-level transportation policy subsystem). To
attract the attention and involvement of actors, policy subsystems usually entail some degree of
authority or potential for authority to alter behavior and shape subsystem outcomes.
The set of relevant subsystem actors include any person attempting to influence subsystem affairs. As
policy process research developed in the 1950s and 1960s, the emphasis was on symbiotic relations
between legislative committees, interest groups, and the government agencies (what has
been referred to as the “iron triangle”). The ACF broadens the set of subsystem actors essentially
to include any person attempting to influence subsystem affairs, including government
officials, members of the private sector and nonprofits, scientists and consultants, and members
of the media.
Individuals are boundedly rational with limited ability to process stimuli, motivated by belief systems,
and prone to experience the “devil shift.” The actors involved in policy subsystems are boundedly
rational, meaning they are goal-oriented but hampered by their cognitive abilities to process
stimuli (Simon 1985). To overcome these limitations, actors simplify the world through hierarchical
belief systems consisting of normative deep core beliefs, subsystem specific policy core beliefs, and
narrow secondary beliefs (Putnam 1976; Peffley and Hurwitz 1985; see Sabatier and Jenkins-Smith
1999: 133). These belief systems are used as heuristics to filter and interpret stimuli (Lord et al.
1979; Munro et al. 1997; Munro et al. 2002). Furthermore, the ACF borrows from prospect theory
to assume that actors remember losses more than gains (Quattrone and Tversky 1988). The
result is what the ACF calls the “devil shift,” which is the tendency for individuals to exaggerate
both the power and maliciousness of their opponents (Sabatier et al. 1987).
Subsystems are simplified by aggregating actors into one or more coalitions. Given the large number
and diversity of actors involved in subsystem affairs, there is a need to simplify while not overly distorting
reality. The ACF directs researchers toward aggregating actors into one or more coalitions.
These coalitions are defined by their shared policy core beliefs and coordination patterns.
Policies and programs incorporate implicit theories and assumptions reflecting the translated beliefs of one
or more coalitions. Subsystems consist of boundedly rational actors working together in coalitions
toward shaping policy outputs and outcomes. Given the importance of beliefs systems, the ACF
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assumes that policy outputs are merely the translations of beliefs of the winning coalition or
coalitions (Pressman and Wildavsky 1973).
Scientific and technical information is important for understanding subsystem affairs. Most subsystems
involve issues that are usually difficult to describe and explain in terms of problem seriousness,
causes, and potential impacts of proposals. Scientific and technical information, thus, becomes
an important resource for coalition members for a variety of uses from argumentation with
opponents to the mobilization of supporters.
Researchers should adopt a longterm time perspective (e.g, of 10 years or more) to understand policy
processes and change. Policy process research is largely the study of public policy over time. The ACF
recommends that researchers examine their phenomenon as a point in the ongoing development
of the policy subsystem. Part of the rationale for taking a long-term perspective is to allow
for ample time to evaluate the outcomes of any policy decision, to assess political reactions, and
to study learning within and between coalitions.
Scope
A framework should provide a scope of inquiry for guiding scholars toward a shared research
agenda. The traditional foci of the ACF are descriptions and explanations of advocacy coalitions,
learning within and among coalition allies and opponents, and policy change. These emphases
should be viewed as general categories for both research inquiry and theory development.
Certainly other areas of research are permitted and have been conducted (e.g. Montpetit 2011;
Shanahan et al. 2011).
General conceptual categories and relations
A framework provides a common vocabulary including the major conceptual categories and
general relations among them. Figure 10.1 shows the ACF flow diagram (adapted from Sabatier
and Weible 2007) featuring a policy subsystem with coalitions, their resources and beliefs, and
the policy outputs and outcomes. Policy subsystems are embedded in a broader political system
with relatively stable parameters and external events, where the latter is more prone to change
than the former.
For researchers wanting to apply the ACF, it is important to consider the following basic
concepts: (1) public policy topic that defines the subsystem; (2) actors who are involved in
subsystem affairs; (3) institutions (e.g. rules) that structure overall subsystem interactions and the
behaviors within particular venues; (4) relative stable parameters and external events; (5) interdependencies
with other subsystems; and, finally, (6) time to permit observations of coalition
behavior, learning, and policy change.
The next step is to articulate the theoretical emphases within the ACF. Theories serve different
functions than frameworks in a research program. Theories narrow the scope of inquiry, link concepts
usually in the form of expectations, propositions, or observable implications, and establish
rationales (causal mechanisms) that explain how concepts interrelate. There are three major theoretical
emphases of the ACF.
First theoretical emphasis: advocacy coalitions
The first area of theoretical emphasis focuses on advocacy coalitions. Advocacy coalitions are
defined as groups of actors sharing policy core beliefs and coordinating their behavior in a nontrivial
manner. Advocacy coalitions emerge and persist because actors vary in their belief systems
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(e.g. normative values regarding a particular policy topic) and seek to form alliances to translate
their beliefs into actual policies before actors with different belief systems can do the same.
The ACF offers three reasons that permit subsystem actors to overcome threats to collective
action in mobilizing coalition activity (Zafonte and Sabatier 1998; Sabatier and Weible 2007: 197).
First, similar beliefs among coalition allies reduce transaction costs of coordination. Second, the
level of coordination varies with some actors engaging in weak coordination (modifying their
behavior to achieve shared goals or information exchange) and others in strong coordination (jointly
developing and executing action plans) (Fenger and Klok 2001). Third, in high conflict situations,
the “devil shift” occurs when actors exacerbate the power and maliciousness of opponents. When
under the devil shift, coalition members will overestimate the threats from shared opponents and
the imposed costs of inaction.
Empirical research across subsystems and political systems have confirmed that policy subsystems
are regularly composed of one to five advocacy coalitions fighting over resources, access to
venues, and influence on the formation of public policy (Weible et al. 2009). Occasionally, these
coalitions interact competitively showing intervals, sometimes spanning decades, of one-upmanship.
In other situations a single, “dominant” coalition will largely control a subsystem for extended
periods of time over a largely nonexistent, inactive, or disorganized opposition. Key descriptive
questions regarding coalition formation and development include:
 What is the structure of the networks and belief systems of advocacy coalition members?
 How stable is coalition membership over time?
 What is the role of different organizations within coalitions?
Figure 10.1 Flow diagram of the advocacy coalition framework
Source: Adapted from Sabatier and Weible (2007)
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 How much consensus is there among coalition members?
 What are the patterns of coordination among subsystem actors?
 What strategies and resources do coalitions use to achieve their policy goals?
Within the scope of the emphasis on coalitions are also a set of explanatory questions addressing
the formation of coalitions and the interaction and behavior of coalition members:
 Why do coalitions form?
 How do coalition members overcome threats to collective action?
 Why do coalition allies negotiate with opponents?
These questions are usually pursued in the form of testing and developing hypotheses. The most
important hypotheses aiming at the composition and development of advocacy coalition include:
Hyphothesis 1 On major controversies within a policy subsystem when policy core beliefs
are in dispute, the lineup of allies and opponents tends to be rather stable
over periods of a decade or so.
Hypothesis 2 Actors within an advocacy coalition will show substantial consensus on issues
pertaining to the policy core beliefs, although less so on secondary aspects.
Hypothesis 3 An actor (or coalition) will give up secondary aspects of his or her (its) belief
system before acknowledging weaknesses in the policy core beliefs.
Hypothesis 4 Within a coalition, administrative agencies will usually advocate more moderate
positions than their interest group allies.
Hypothesis 5 Elites of purposive groups are more constrained in their expression of beliefs
and policy positions than elites from material groups.
(Sabatier and Weible 2007: 220)
Hypotheses 1–5 specify some of the fundamental components of the ACF, including the
hierarchy and stability of belief systems and the distinction between different types of organizations.
Important contributions in the study of coordination networks and belief stability and
change within coalitions can be found in Jenkins-Smith et al. (1991), Zafonte and Sabatier (1998),
Weible and Sabatier (2005), Weible (2005), Ingold (2011), Henry et al. (2010), Henry (2011), Matti
and Sandström (2011), and Pierce (2011). Previous empirical research provides mixed results
regarding these hypotheses by showing patterns of both stability and defection of coalition
members over time (Jenkins-Smith and St. Clair 1993; Jenkins-Smith et al. 1991; Sabatier and
Brasher 1993; Zafonte and Sabatier 2004; Andersson 1999; Munro 1993).
While coalition resources have been a regular feature within the ACF since its inception
(Sabatier and Jenkins-Smith, 1993: 29), Sabatier and Weible (2007: 201-4) and Weible (2007)
placed more emphasis on the area by offering a typology of coalition resources: (1) formal legal
authority to make policy decisions; (2) public opinion; (3) information; (4) mobilizable troops;
(5) financial resources; and (6) skillful leadership. The access and use of these resources is theoretically
argued to be important for forming and maintaining coalitions and for policy change. However,
the empirical investigation of coalition resources has only recently been examined by scholars
(Nohrstedt 2011; Ingold 2011; Albright, 2011).
The formation and stability of advocacy coalitions over time and their political behavior is
conditioned by subsystem institutions and events outside the control of subsystem actors. The
most important institutional factors that constrain subsystem actors are first, the openness of the
political system and second, norms of consensus, which affect the level of inclusiveness of
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coalitions, exchange of information across coalition boundaries, and access to policy venues
(Sabatier and Weible 2007). Institutions shape the level of coordination within a coalition, primarily
by setting legal impediments that constrain formation of formal alliances paving the way
for weaker forms of coordination as a viable political strategy (Zafonte and Sabatier 1998;
Fenger and Klok 2001; Nohrstedt 2010). Events are likely to affect coalition behavior, particularly
by providing opportunities for exploitation of new resources (including mobilization of
new coalition members) and strategy in terms of venue exploitation.
Second theoretical emphasis: policy-oriented learning
Learning has been a central focus of the ACF since its inception (Sabatier 1988). Policy-oriented
learning is defined as “enduring alterations of thought or behavioral intentions that result from
experience and which are concerned with the attainment or revision of the precepts of the
belief system of individuals or of collectives” (Sabatier and Jenkins-Smith 1993: 42–56). To
study policy-oriented learning is to study changes in belief system components of coalition
members over time. Policy-oriented learning may entail better understanding of political goals,
the causal relationship among key factors in the subsystem, and effective strategic behaviors,
especially as used in analytic debates.
Important descriptive questions that guide inquiry into learning are the following:
 What belief system components are changing through learning?
 To what extent is one coalition learning more than another coalition?
Explanatory questions deal with issues of when, why, and how actors learn within and between
coalitions and include:
 What contexts and events foster learning by coalition members?
 How does learning diffuse among allies within a coalition?
 What contexts and events foster learning by brokers?
 To what extent, if at all, does a broker facilitate learning between coalitions?
 Why does learning occur, if at all, between some members of opposing coalitions and not
others?
On the whole, the intent of the ACF’s focus on policy-oriented learning is to understand and
explain what constitutes learning and why learning occurs within coalitions and between coalitions.
Four general factors are important for explaining policy-oriented learning. The first
involves the attributes of professional forums (see Jenkins-Smith 1990). Professional forums are
venues of discussion involving subsystem actors. Forums are structured by different sets of
institutional arrangements. Some forums are structured by open participation rules (open forum)
and others by closed participation rules (closed forum). Professional forums are based on common
analytical training and norms and are postulated to increase the likelihood for learning between
coalitions (ibid.).
The second variable conditioning learning is the level of conflict between coalitions (JenkinsSmith
1990; Weible 2008). The expectation is that there is an inverted quadratic relationship
between conflict and cross-coalition learning. On one extreme at low levels of conflict, there is
little cross-coalition learning as the opposing coalitions place their attention on other, more
pressing issues. On the other extreme at high levels of conflict, there is also little cross-coalition
learning as opposing coalitions are motivated to defend their positions and refute claims by their
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opponents. The conditions most conducive for cross-coalition learning would then be intermediate
levels of conflict where there is enough of a threat to attract the attention of rivals but
not too much of a threat to entrench opponents in rigid policy positions.
The third variable is attributes of the stimuli or data prompting learning. The stimuli can
come from many different sources including scientific and technical information, actors, and
events. One important attribute of stimuli relates to the level of analytical tractability of the
phenomenon (Jenkins-Smith 1990: 97–9). Subsystems with highly intractable issues are marked
by uncertainty and high levels of disagreement about the scientific and technical aspects of the
issue (e.g. about the quality of the data or theories used). In general, highly intractable issues are
expected to be associated with lower levels of cross-coalition learning.
The fourth variable that conditions learning involves attributes of individuals, including belief
systems, resources, and network contacts. Are actors with extreme beliefs less likely to learn
from their opponents than actors with moderate beliefs? Are some actors more or less supported
by their analytical training in learning than others? Are actors with network contacts—either
within their coalitions or with opposing coalitions—more likely to learn?
Central to the arguments about cross-coalition learning is a certain type of individual: the
policy brokers. Sabatier and Jenkins-Smith (1993: 27) define brokers as “a category of actors …
whose dominant concerns are keeping with the level of political conflict within acceptable
limits and reaching some ‘reasonable’ solution to the problem.” Sabatier and Jenkins-Smith argue
that identifying brokers is an empirical question and is not dependent upon organizational
affiliation. These broker may learn, possibly prior to the coalitions, and then facilitate cross-coalition
learning later in the process (Sabatier and Jenkins-Smith 1993: 218–19).
Given the research questions and categories above, the theoretical emphasis on policy-oriented
learning within the ACF is built into five hypotheses:
Hypothesis 1 Policy-oriented learning across belief systems is most likely when there is an
intermediate level of informed conflict between the two coalitions. This
requires that: (a) each have the technical resources to engage in such a debate;
and that (b) the conflict be between secondary aspects of one belief system and
core elements of the other or, alternatively, between important secondary
aspects of the two belief systems.
Hypothesis 2 Policy-oriented learning across belief systems is most likely when there exists
a forum which is: (a) prestigious enough to force professionals from different
coalitions to participate; and (b) dominated by professional norms.
Hypothesis 3 Problems for which accepted quantitative data and theory exist are more
conducive to policy-oriented learning across belief systems than those in which
data and theory are generally qualitative, quite subjective, or altogether lacking.
Hypothesis 4 Problems involving natural systems are more conducive to policy-oriented
learning across belief systems than those involving purely social or political
systems because in the former many of the critical variables are not themselves
active strategists and because controlled experimentation is more feasible.
Hypothesis 5 Even when the accumulation of technical information does not change the
views of the opposing coalition, it can have important impacts on policy – at
least in the short run – by altering the views of policy brokers.
A review of ACF applications in Weible et al. (2009) indicates that, of the five learning
hypotheses, the first two have been tested the most and the last two the least. From this review,
they found evidence suggesting that learning within coalitions reinforces beliefs and mixed
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results about the likelihood of cross-coalition learning. For example, Larsen et al. (2006) find
that cross-coalition learning occurs at the secondary level of belief systems (as expected) but also
at the policy-core level (not expected). Similar mixed results can be found with the measurement
and findings involving professional forums. If there is any area within the ACF needing
more attention at both the theoretical and operational levels, it is policy-oriented learning.
Third theoretical emphasis: policy change
The third theoretical emphasis in the ACF involves policy change. The ACF assumes that policies
are translations of beliefs and can be conceptualized and measured hierarchically like belief systems.
Policy components that span, and are salient to, a policy subsystem represent the policy
core aspects of the subsystem. Policy components that deal with only a part of a subsystem or
technical components of a policy represent secondary aspects of the subsystem. A change in policy
core aspects indicates a major change in the direction of the subsystem and is defined as “major
policy change.” A change in secondary aspects indicates a minor change in the subsystem and is
defined as “minor policy change” (Sabatier and Jenkins-Smith 1999: 147–8).
The descriptive questions in the study of policy change include:
 To what extent does major and minor policy change occur within the subsystem over time?
 What is the content of minor and/or major policy change?
Explanatory questions on the topic of policy change are several:
 Why do some events and contexts lead to minor and major policy change?
 What are the mechanisms linking internal and external events to minor and major policy
change?
 How do negotiated agreements lead to policy change?
 When does policy-oriented learning lead to policy change?
As reflected in these questions, the ACF specifies four pathways to policy change (Sabatier and
Weible 2007). The first two paths involve events either external or internal to the policy subsystem.
External events occur outside the territorial boundaries of the subsystem and/or the
topical policy boundaries of the subsystem and are, hence, largely outside the control of subsystem
actors. Internal events occur inside the territorial and/or the topical area of the policy
subsystem and are more likely affected by subsystem actors. The two types of events differ in their
effect on coalition behavior and policy change. Most importantly, attribution of blame or success
is higher after internal subsystem events are compared to after external subsystem events (see
Nohrstedt and Weible 2010).
Policy-oriented learning is the third path and is said to lead to policy change through altering
the beliefs of coalition members. Policies may change after a dominant coalition learns or after
learning occurs between adversarial coalitions.
The fourth path is said to occur through negotiated agreements. Sabatier and Weible (2007:
205–6) describe nine prescriptions fostering negotiation between coalitions and then policy
change. These nine prescriptions include: a hurting stalemate, broad representation, leadership,
consensus, funding, commitment by actors, importance of empirical issues, trust, and lack of alternative
venues. From this list, the most important for instigating negotiations between coalitions
is a hurting stalemate. A hurting stalemate occurs when both coalitions view the status quo as
unacceptable and do not have access to alternative venues for achieving their objectives.
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The original version of the ACF offered two hypotheses involving major policy change:
Hypothesis 1 Significant perturbations external to the subsystem are a necessary, but not sufficient,
cause of change in the policy core attributes of a governmental program.
Hypothesis 2 The policy core attributes of a governmental program in a specific jurisdiction
will not be significantly revised as long as the subsystem advocacy coalition
that instituted the program remains in power within that jurisdiction—except
when the change is imposed by a hierarchically superior jurisdiction.
These two hypotheses for policy change have existed since the original version (Sabatier
1987, 1988). After the introduction of the other paths to policy change in 2007, new hypotheses
were not added to encompass this expansion in logic. To better reflect the theoretical arguments
c. 2007, a revised Hypothesis 1 would read as follows:
Hypothesis 1 Significant perturbations external to the subsystem, a significant perturbation
internal to the subsystem, policy-oriented learning, negotiated agreement, or
some combination thereof are necessary, but not sufficient, cause of change in
the policy core attributes of a governmental program.
The underlying logic of the ACF suggests that none of the four paths are necessary and sufficient
to produce policy change. Thus, one underdeveloped area within the ACF is the explanation
that traces any path or combination of paths from its occurrence to policy change or
stasis. This research should center on one or more exploitive coalitions that seek to capitalize on
the opportunity afforded by one of the paths. But how a coalition will exploit an opportunity is
largely unknown from a theoretical perspective, with notable explorations into the topic taken
by Smith (2000), Ameringer (2002), Albright (2011), Ingold (2011), and Nohrstedt (2005, 2008,
2010, 2011). Developing knowledge in understanding the links from one or more of the four
paths to policy change will most likely involve the analysis of how resources are redistributed
between coalitions within the subsystem. It is likely, for example, that external events or internal
events or even learning might alter the distribution of resources or how those resources are used
leading to a more empowered coalition. Another theoretical area open for inquiry is the interdependencies
of the four paths or multiple occurrences within the same path. For example,
when do multiple external or internal events lead to learning and possibly negotiated agreements
among adversarial coalitions? Similarly, when do a number of events occurring over time
accumulate into sufficient momentum for a coalition to capitalize to produce major policy change
(Smith 2000)? Finally, the role and behavior of dominant coalition actors in processes leading to
policy change must be clarified (Nohrstedt 2010: 23). Under what conditions do dominant
coalition members promote stability and defend the status quo and when do they seek change?
What approaches to policy change (reformist or conservative) do dominant coalitions take following
external and internal events and why? By definition, dominant coalition members
control key political resources—primarily formal legal authority—and thereby policy programs
(Nohrstedt 2011). Therefore, understanding the motivations of dominant coalition actors is an
important avenue for future research.
Conclusions
The ACF has continued for a quarter of a century and has made progress in understanding and
explaining policy processes across the globe. The theoretical emphasis in the ACF reflects the
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specialization among people applying the framework as well as natural partitions of the hypotheses.
Clearly, the hypotheses are overlapping. Whereas a theoretical emphasis on the structure and
stability of networks and beliefs might be the dependent variable for one study about coalitions,
changes in coalition structure and stability might be the independent variable for another study
about policy change (Weible et al. 2011). Researchers should not view the theoretical emphases
as sharply distinct but rather as signifying helpful partitions that permit specialized inquiry into
questions about coalitions, learning, and policy change.
Among the next steps in applying the ACF is to continue to develop the theoretical descriptions
and explanations within each of these areas of emphases as well as to develop other unexplored
areas within the framework. It is quite possible, for example, that there is another theoretical
emphasis centered on the role of scientific and technical information and scientists in policy
subsystems (Jenkins-Smith 1990; Weible 2008; Montpetit 2011). Policy narratives are another
area that offers opportunities for theoretical growth based in part on the ACF (Shanahan et al.
2011). Scholars can also develop better theoretical understanding about how specific concepts
or categories of concepts interrelate within the framework; for example, the role of political
opportunity structures (Sabatier 1998; Kübler 2001). Most importantly, the ACF is increasingly
serving as a framework for guiding researchers from around the world in conducting comparative
public policy analysis. As such, what is needed is a clearer articulation of how subsystems
operate in different political systems and political cultures. One likely approach for international
comparisons is, first, to focus on political system differences (e.g. the continuum from corporatism
to pluralism) and, second, to compare and contrast subsystem institutions (e.g. subsystem specific
rules and norms) and their effects on coalition formation, policy learning and change.
Given the continued and growing momentum of the ACF research program, this effort must
ask the question: to what end? The immediate objective of the ACF is a better understanding
and explanation of policy processes. Such knowledge serves academia in research and teaching.
Another tradition in public policy is the service to society outside the networks of academics. In
this context, extant approaches for this aspiration can be found in various forms of engaged scholarship
(Van de Ven 2008), advocacy, and direct service. For scholars applying the ACF and
seeking practical benefits, one question should be how the framework can be used for theoreticallyguided
research toward academic ends and as a tool in providing advice to subsystem actors
toward better societal outcomes.
Note
1 See Sabatier and Jenkins-Smith (1993) for a thorough description of the framework’s underpinnings.
Additionally, readers interested in gaining a deeper understanding of the ACF are encouraged to read
Sabatier (1987, 1988, 1998), Jenkins-Smith (1990), Sabatier and Jenkins-Smith (1999), Sabatier and
Weible (2007), Weible et al. (2009), and Weible et al. (2011).
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