The Policy Studies Journal, Vol. 37, No. 1, 2009
Themes and Variations: Taking Stock of the Advocacy
Coalition Framework
Christopher M. Weible, Paul A. Sabatier, and Kelly McQueen
A policy process framework that has been developed to simplify the complexity of public policy is the
advocacy coalition framework (ACF). This essay reports on an analysis of 80 applications of the ACF
spanning nearly 20 years. The review shows that the ACF is applicable to various substantive topics,
across various geographical areas, and with other policy process theories and frameworks, including the
stages heuristic. The most commonly tested hypotheses involve policy change, learning, and coalition
stability. Although the hypotheses tend to be confirmed, questions remain about the membership,
stability, and defection of coalition members; about the causal mechanisms linking external events and
policy change; and about the conditions that facilitate cross-coalition learning. Emerging areas of
research include policy subsystem interdependencies and coordination within, and between, coalitions.
Introduction
Perennial questions in public policy involve issues of learning, belief, and policy
change, and the role of scientific and technical information in policymaking. Each of
these issues operate in complex, interdependent political environments where hundreds of participants interact in the context of nested institutional arrangements,
uneven power relations, and uncertain scientific and technical information about
problems and alternatives. This inherent complexity requires a conceptual simplification to guide research agendas, to enable communication among scholars and
practitioners, and to develop effective decision making strategies.
One policy process framework that has been developed to simplify the complexity of public policy is the advocacy coalition framework (ACF). Sabatier and JenkinsSmith (1988) initially introduced the ACF as a symposium issue for Policy Sciences. In
1993, Sabatier and Jenkins-Smith coedited a book that outlined the ACF along with
a set of hypotheses about science in policy, learning, and belief and policy change.
The 1993 book included six ACF-guided case studies, four of which were written by
other researchers, and ended with a critical assessment and subsequent revisions of
the framework. Later theoretical revisions occurred in Sabatier and Jenkins-Smith
(1999) and Sabatier and Weible (2007). Akin to Sabatier and Jenkins-Smith (1993),
this essay takes a critical look at the ACF through the eyes of the consumers by
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Published by Wiley Periodicals, Inc., 350 Main Street, Malden, MA 02148, USA, and 9600 Garsington Road, Oxford, OX4 2DQ.
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summarizing more than 80 applications of the framework spanning nearly 20 years.
By taking stock of the existing applications, this essay identifies and discusses some
of the strengths and weaknesses of the ACF and offers directions for future research.
The essay begins with a brief overview of the ACF, including a recap of some of
the theoretical revisions over time. The next section presents the methods of conducting a comprehensive literature review of ACF applications. The essay then
summarizes and draws lessons from existing ACF research.
An Overview of the ACF
The ACF was created by Sabatier and Jenkins-Smith in the late 1980s in response
to what they saw as essentially three limitations in the policy process literature. The
first limitation was their interpretation of the stages heuristic as an inadequate causal
theory of the policy process (Sabatier & Jenkins-Smith, 1993, pp. 1–4). The second
was in response to a decade-long debate about the strengths and weaknesses of
top-down and bottom-up approaches to implementation research and the need for
system-based theories of policymaking (Sabatier, 1986). The third was the apparent
lack of theory and research on the role of scientific and technical information in the
policy process (Jenkins-Smith, 1990; Sabatier, 1988). As a response, the ACF was
created as a system-based model that integrates most of the stages of the policy cycle,
incorporates aspects of both the top-down and bottom-up approaches to implementation studies, and places scientific and technical information in a central position in
many of its hypotheses.
The ACF’s causal logic and resulting hypotheses build from a set of assumptions:
(i) a central role of scientific and technical information in policy processes; (ii) a time
perspective of 10 years or more to understand policy change; (iii) policy subsystems
as the primary unit of analysis; (iv) a broad set of subsystem actors that not only
include more than the traditional iron triangles’ members but also officials from all
levels of government, consultants, scientists, and members of the media; and (v) a
perspective that policies and programs are best thought of as translations of beliefs
(Sabatier & Jenkins-Smith, 1999, pp. 118–20). Additionally, the ACF specifies a model
of the individual who is boundedly rational with limited abilities to process stimuli;
relies on beliefs as the principal heuristic to simplify, filter, and sometimes distort
stimuli; and remembers losses more than gains (Lord, Ross, & Lepper, 1979;
Quattrone & Tversky, 1988; Scholz & Pinney, 1995; Simon, 1985).
Among the assumptions, the ACF explicitly identifies beliefs as the causal driver
for political behavior. Subsequently, considerable time has been spent in the framework articulating and revising a three-tiered model of a belief system for its actors.
At the top of the belief system lies deep core beliefs, which are the broadest and most
stable among the beliefs and are predominately normative. Examples include liberal
and conservative beliefs, and relative concern for the welfare of present versus future
generations that are applicable across many subsystems. In the middle of the belief
system hierarchy is policy core beliefs, which are of moderate scope and span the
substantive and geographic breadth of a policy subsystem. The subsystem specificity
of policy core beliefs makes them ideal for forming coalitions and coordinating
Weible/Sabatier/McQueen: The Advocacy Coalition Framework
RELATIVELY STABLE
PARAMETERS
1. Basic attributes of the
problem area (good)
2. Basic distribution of
natural resources
3. Fundamental
sociocultural values and
social structure
4. Basic constitutional
structure (rules)
LONG-TERM COALITION
OPPORTUNITY
STRUCTURES
1. Overlapping societal
cleavages
2. Degree of consensus
needed for major
policy change
POLICY SUBSYSTEM
Coalition A
Coalition B
Policy
brokers
a. Policy beliefs
b. Resources
a. Policy beliefs
b. Resources
Strategy
Strategy
regarding guidance
instruments
regarding guidance
instruments
Decisions by
governmental authorities
EXTERNAL (SYSTEM)
EVENTS
1. Changes in socioeconomic conditions
2. Changes in public
opinion
3. Changes in systemic
governing coalition
4. Policy decisions and
impacts from other subsystems
123
SHORT-TERM
CONSTRAINTS AND
RESOURCES OF
SUBSYSTEM ACTORS
Institutional rules, resource
allocations, and appointments
Policy outputs
Policy impacts
2007 Advocacy Coalition Framework Flow Diagram
Figure 1. 2007 Advocacy Coalition Framework Flow Diagram.
activities among members. Policy core beliefs are resistant to change but are more
likely to adjust in response to verification and refutation from new experiences and
information than deep core beliefs. At the bottom of the belief system is secondary
beliefs. Compared to policy core beliefs, secondary beliefs are more substantively and
geographically narrow in scope, and more empirically based. The ACF predicts that
secondary beliefs, compared to deep core and policy core beliefs, are the most likely
to change over time.
The 2007 flow diagram of the ACF is shown in Figure 1. One of the major
contributions of the ACF is the posed distinction between policy subsystems and the
broader political environment. The ACF specifies subsystems as the major unit of
analysis because political systems involve many topics over broad geographical areas
that compel actors to specialize in a topic and locale to understand its complexity
and to be effective in producing change. Subsystems are not immutable to external
effects, and Figure 1 shows that subsystems operate within a broader political environment defined by relatively stable parameters and external events, and constrained by long-term coalition opportunity structures, short-term constraints and
resources of subsystem actors, and other policy subsystem events. Indeed, a rich area
of future research is to develop a deeper understanding of subsystem interdependencies (Fenger & Klok, 2001).
One of the major revisions to the ACF was summarized in Sabatier and Weible
(2007), where the framework was reformulated to ease applications outside of the
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pluralist system in the United States to corporatist regimes. The revisions included
adding two sets of variables as important long-term opportunity structures (Kriesi,
Koopmans, Duyvendak, & Giugni, 1995; Kübler, 2001; Lijphart, 1999; McAdam,
McCarthy, & Zald, 1996). The first is the degree of consensus needed for major
policy change which affects the density and membership of coalitions and coalition
strategy in reaching agreements. The second is the degree of openness of political
systems. For example, federalism and checks and balances in the United States
create decentralized processes with many venues and encourage entry and diverse
participation, whereas corporatist systems are less open, more centralized, and
restrict participation.
The original version of the ACF focused solely on two paths to policy change in a
policy subsystem. The first path is external subsystem events, which are defined as
shifts in the policy core attributes of the subsystem. External events or shocks include
broad changes in socioeconomic conditions, public opinion, governing coalitions, and
other subsystems. External shocks can foster change in a subsystem by shifting and
augmenting resources, tipping the power of coalitions, and changing beliefs.
The second path to policy change is policy-oriented learning. Policy-oriented
learning is defined as “relatively enduring alternations of thought or behavioral
intentions that result from experience and/or new information and that are concerned with the attainment or revision of policy objectives” (Sabatier & JenkinsSmith, 1999, p. 123). Because of the rigidity of the belief system of the ACF actor,
policy-oriented learning primarily affects secondary beliefs or secondary aspects of
the policy subsystem over extended periods of time (Weiss, 1977).
The latest revision of the ACF identifies a third and a fourth path to policy
change. The third path to policy change is internal subsystem events (Sabatier and
Weible, 2007, pp. 204–5). Compared with external events, internal events occur
within the subsystem and are expected to highlight failures in current subsystem
practices. The fourth path to policy change builds from the alternate dispute resolution literature and occurs through negotiated agreements involving two or more
coalitions (Bingham, 1986; Carpenter & Kennedy, 1988; O’Leary & Bingham, 2003;
Susskind, McKearnan, & Thomas-Larmer, 1999; Ury, 1993). This fourth path builds
from previous ACF work on the conditions facilitating cross-coalition learning
(Jenkins-Smith, 1990) where “professional forums” provide an institutional setting
that allows coalitions to safely negotiate, agree, and implement agreements. Sabatier
and Weible (pp. 206–7) identify nine conditions affecting the likelihood of policy
change through this fourth path: a hurting stalemate, effective leadership, consensusbased decision rules, diverse funding, duration of process and commitment of
members, a focus on empirical issues, an emphasis on building trust, and lack of
alternative venues.
Methods
This review of ACF literature focused on the population of peer-reviewed
journal articles, books, and book chapters from 1987 to 2006 that applied the framework, or components of the framework, in generating and testing hypotheses,
Weible/Sabatier/McQueen: The Advocacy Coalition Framework
125
structuring the analysis, or guiding causal or descriptive inference. We began with
the list of 34 ACF applications in Sabatier and Jenkins-Smith (1999, p. 126), which
summarizes the work up to 1998/9, and of 53 applications from 1998/9 to 2006 in
Sabatier and Weible (2007, pp. 217–19). We complimented the existing list of applications with searches on Web of Science and Google Scholar using “advocacy coalition framework” and “advocacy coalition” as key words for searches. We followed
up in a snowball fashion on any citations to additional ACF applications while
coding the articles. We excluded unpublished manuscripts, conference papers, dissertations, and articles that simply referenced the ACF. The unit of analysis for this
review is a published peer-reviewed article, book, report, and book chapter. Thirteen
of the applications were authored by Sabatier, Jenkins-Smith, or their students.
A group of five researchers developed and applied a coding framework that
contained approximately 48 elements. Articles were coded over 11 months in 2007.
The research group met periodically during the project to discuss the interpretation
and reliability of the coding scheme and preliminary findings. A total of 80 applications of the framework through 2006 were coded. Approximately 90 percent of
the applications were coded with less than, or equal to, four discrepancies between
coders and 10 percent of the applications had between five and seven discrepancies
in coding. Almost all discrepancies were resolved. Coded elements with unresolved
discrepancies were considered temporarily unreliable and not used in the current
analysis. The current sample of ACF case studies is not complete, and the sample is
constantly being updated.
Lessons from Past Applications
This section summarizes how researchers have applied the ACF, and some
observations gleaned from these applications.
1. ACF Applications have Expanded in Geographical and Substantive Breadth and Depth
Figure 2 presents the frequency count of ACF applications from 1987 through
2006, with the bars subdivided into social, economic, health, and environment/
energy policy areas. Researchers have applied the ACF to domestic violence (Abrar,
Lovenduski, & Margetts, 2000), tobacco policy (Farquharson, 2003), emergency contraception (Schorn, 2005), sport policy (Green & Houlihan, 2004; Parrish, 2003), and
disaster policy (Olson, Olson, & Grawronski, 1999). The majority of applications,
however, remain within environmental and energy policy areas, which is most likely
a legacy of the original focus by Sabatier and Jenkins-Smith.
Figure 3 presents a similar bar chart as in Figure 2, but with the bars now
subdivided into eight coded geographic areas: Africa, Asia, Australia, Canada, South
America, International, Europe, and the United States. Most of the early applications
of the ACF occurred within the United States with a gradual increase across the
world, including Africa (Tewari, 2001), South America (Carvalho, 2001), Australia
(Chen, 2003), Asia (Hsu, 2005), and Internationally (Farquharson, 2003). The majority
of applications is in the United States or in Europe.
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10
9
8
Substantive topic
Count
7
Other
Social
Economic
Health
Environment/Energy
6
5
4
3
2
1
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1993
1991
1989
1988
1987
0
Year
Figure 2. Number of Advocacy Coalition Framework Publications by Substantive Topic from
1987 to 2006.
The ACF has been criticized for a bias toward pluralistic political systems, such
as the United States (Eberg, 1997; Kübler, 1999). These criticisms will continually be
more difficult to justify with the inclusion of coalition opportunity structures in
Figure 1, and with the evidence from Figure 3 showing that the ACF can be utilized
in almost any political setting and culture, including authoritarian regimes in developing countries. While the framework has had a strong association with environmental and natural resources policies, Figure 3 shows that the ACF can be applied
across almost any policy domain.
2. ACF Applications Have Included Multiple Methods of Data Collection; in Nearly
Half of the Applications, However, the Methods of Data Collection Were
Unclear or Unspecified
Table 1 shows that many researchers have relied upon different approaches of
data collection, including interviews, content analysis, questionnaire, observational,
or some combination of these methods. Nearly half of the applications (41 percent),
however, used methods that were unspecified and appeared to rely on unsystematic
collection and analysis of existing documents and reports.
Weible/Sabatier/McQueen: The Advocacy Coalition Framework
127
10
9
8
Geographic scope
Count
7
Africa
South America
Australia
International
Asia
Canada
Europe
United States
6
5
4
3
2
1
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1993
1991
1989
1988
1987
0
Year
Figure 3. Number of Advocacy Coalition Framework Publications by Geographic Scope from 1987 to
2006.
Table 1. Frequency of Methods Used in Advocacy Coalition
Framework Publications from 1987 to 2006
Frequency
%
Unspecified
Interviews
Content analysis
Questionnaire
Observational
Interviews and content analysis
Questionnaire and interview
Questionnaire and content analysis
33
16
7
5
2
8
8
1
41
20
9
6
3
10
10
1
Total
80
100.0
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Policy Studies Journal, 37:1
3. A Majority of ACF Applications Do Not Explicitly Test One of the Formal
Hypotheses; and Hypotheses Involving Coalition Stability, Policy-Oriented Learning, and
Policy Change Have Been Tested Most Frequently
Table 2 lists 15 of the major hypotheses in the ACF based mostly on the list in
Sabatier and Jenkins-Smith (1999, p. 124). Table 2 shows that the most frequently
tested hypotheses involve core aspects of the framework: external perturbations as a
necessary, but not sufficient, condition for major policy change (18 times); stability of
coalitions (13 times); and policy-oriented learning when there is intermediate levels
of conflict (11 times), or policy-oriented learning when there exists a forum (9 times).
Three hypotheses that have not been tested at all deal with coordination and collective action of coalitions, and more than half of the applications (55 percent) do not
explicitly test any of the hypotheses.
4. Questions Remain on Linking External Perturbations to Changes
in Policy Subsystems
Many applications discuss the interplay between external shocks and internal
subsystem conditions in fostering policy change (Barke, 1993; Bischoff, 2001; Green
& Houlihan, 2004; Jordan & Greenaway, 1998; Mawhinney, 1993). For example,
Kübler (2001) shows in a Switzerland drug policy subsystem how the emergence of
the acquired immunodeficiency syndrome epidemic served as an external event that
was used by a harm reduction coalition to challenge and change their opponent’s
pro-abstinence drug policies. In a study of European steel policy, Dudley and Richardson (1999) describe how changes in beliefs by one coalition in support of free
markets altered the way it framed external events, leading eventually to major policy
change. However, not all external shocks lead to major policy change. Ameringer
(2002) argues that the absence of skillful coalition members was a reason for the lack
of major policy change after an external perturbation. Alternatively, instead of major
policy change, some researchers discuss changes in coalition structure or minor
policy changes after an external shock (Burnett & Davis, 2002; Carvalho, 2001; Davis
& Davis, 1988). The lessons from these applications are threefold: First, the effects of
external shocks cannot be understood in isolation from internal subsystem affairs.
second, there is much to learn about the intervening steps between an external
perturbation and major policy change; third, changes in coalition membership, strategies, beliefs, and minor policy changes are among the other internal subsystem
effects resulting from external perturbations.
5. Coalition Membership Is Generally Stable Over Time but Defection of Members Is
Common and Homogeneity of Members Should not Be Assumed
Several studies find that coalition membership—especially among principal
members—can be stable over time (Jenkins-Smith & St. Clair, 1993; Jenkins-Smith, St.
Clair, & Woods, 1991; Sabatier & Brasher, 1993; Zafonte & Sabatier, 2004). Notwithstanding, other researchers have tried to explain instances of coalition instability and
Weible/Sabatier/McQueen: The Advocacy Coalition Framework
129
Table 2. Frequency of Tested Advocacy Coalition Framework Hypotheses
Hypotheses
1. Significant perturbations external to the subsystem (e.g., changes in socioeconomic
conditions, public opinion, system-wide governing coalitions, or policy outputs from
other subsystems) are a necessary, but not sufficient, cause of change in the policy core
attributes of a governmental program.
2. 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.
3. 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: (i)
each have the technical resources to engage in such a debate; and that (ii) 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.
4. Policy-oriented learning across belief systems is most likely when there exists a forum
which is: (i) prestigious enough to force professionals from different coalitions to
participate; and (ii) dominated by professional norms.
5. 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.
6. 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.
7. Actors within an advocacy coalition will show substantial consensus on issues
pertaining to the policy core, although less so on secondary aspects.
8. An actor (or coalition) will give up secondary aspects of his (its) belief system before
acknowledging weaknesses in the policy core.
9. 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.
10. Within a coalition, administrative agencies will usually advocate more moderate
positions than their interest-group allies.
11. Elites of purpose groups are more constrained in their expression of beliefs and policy
positions than elites from material groups.
12. 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.
13. Coalitions are more likely to persist if (i) the major beneficiaries of the benefits that a
coalition produces are clearly identified and are members of the coalition, (ii) the
benefits received by coalition members are related to the maintenance costs of each
member, and (iii) coalition members monitor each others’ actions to ensure compliance.
14. Actors who share policy core beliefs are more likely to engage in short-term
coordination if they view their opponents as (i) very powerful, and (ii) very likely to
impose substantial costs upon them if victorious.
15. Actors who share (policy core) beliefs are more likely to engage in short-term
coordination if they: (i) interact repeatedly; (ii) experience relatively low information
costs; and (iii) believe that there are policies that, while not affecting each actor in
similar ways, at least treat each fairly.
Count
18
13
11
9
8
7
6
5
5
4
4
2
0
0
0
defection. Andersson (1999) shows how a dominant coalition may split into three
coalitions as issues shift to different preferences for core policy alternatives.
Munro (1993, p. 126) finds that extreme coalition members may defect from both
coalitions to prevent the adoption of “balanced” policies. Elliott and Schlaepfer
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(2001), Jenkins-Smith et al. (1991), and Zafonte and Sabatier (2004) argue that coalition defection possibly results from external events, such as elections. Coalition
stability and defection might also be shaped by relatively stable parameters and
political opportunity structures. For example, Larsen, Vrangbaek, and Traulsen
(2006) argue that coalitions in corporatist states, where there is a strong demand for
compromise, will consist of allies in both a solid core and on a fuzzy periphery.
Actors on the fuzzy periphery might very well switch allegiances over relatively
short periods of time to increase their political influence. Stability and defection of
coalitions might also depend on the diversity of members. For example, Olson et al.
(1999) and Weible and Sabatier (2005) find sub coalitions, which are coalitions with
members who are glued together by some of their policy core beliefs against a
common opponent but who are also internally divided in other policy core or
secondary beliefs. In sum, the coalition concept should not lead researchers to
assume homogeneity among group members either in beliefs or in coordination
patterns. Instead, researchers are encouraged to look for principal and auxiliary
members or other membership types, sub coalitions, explanations for defections over
time, and coalitions that dissolve.
6. Learning Frequently Occurs at the Secondary Level of Beliefs within Coalitions, but
Questions Remain about the Factors Facilitating Cross-Coalition Learning and Linking
Learning to Policy Change
Research has linked learning with changes in secondary and policy core beliefs
(Eberg, 1997; Elliott & Schlaepfer, 2001; Ellison, 1998; Larsen et al., 2006). Learning
seems more likely to happen, as predicted by the ACF, at the secondary than at the
policy core level (Eberg; Ellison; Lester & Hamilton, 1987; Sabatier & Brasher, 1993;
Sato, 1999).
Learning within coalitions tends to reinforce preexisting beliefs, especially in
high conflict situations (Litfin, 2000; Mawhinney, 1993; Meijerink, 2005). The ACF
hypothesizes that cross-coalition learning is more likely to occur where discussions
focus on secondary beliefs, when the issues are technical or tractable, when conflict
is at intermediate levels, and when there is a professional forum. There is mixed
support for the hypothesized conditions for cross-coalition learning. Research finds
that cross-coalition learning is more likely to occur with secondary beliefs (Larsen
et al., 2006), on tractable issues (Ladi, 2005; Meijerink), when there is intermediate
levels of conflict (Meijerink), when technical resources are available (Elliott &
Schlaepfer, 2001; Olson et al., 1999), and in professional forums (Brown & Stewart,
1993; Olson et al.). However, research also shows that learning occurs at the policy
core level between coalitions (Larsen et al.) and analytical and tractable issues, and
professional forums do not always facilitate cross-coalition learning (Brown &
Stewart; Litfin; Munro, 1993; Nagel, 2006). One reason for the mixed results is that
the conditions conducive for cross-coalition learning are necessary but not sufficient
for cross-coalition learning (Sabatier, 1988). Alternatively, the professional forums
studied might not have all of the necessary characteristics for cross-coalition learning
(Sabatier & Jenkins-Smith, 1999, pp. 146–47) or high political conflict limits the
Weible/Sabatier/McQueen: The Advocacy Coalition Framework
131
effectiveness of professional forums and the likelihood that cross-coalition learning
will occur on tractable issues (Litfin).
Learning is important, in part, because of its hypothesized connection with
policy change. A number of ACF applications have focused on this connection, or the
challenges in making such a connection, between learning and policy change. Some
researchers find a strong connection (Lester & Hamilton, 1987; McBeth, Shanahan,
Arnell, & Hathaway, 2007; Munro, 1993) and others describe a weak connection, if
there is any connection at all (Eberg, 1997; Nohrstedt, 2005). Eberg argues that the
link between learning and policy change is often tenuous, largely because of empirical challenges in measuring learning and then in linking it to changes in policy.
7. Applications Provide Support for ACF Expectations about the Role of Science in Policy
Existing studies attest to the political roles played by scientists as coalition
members (Litfin, 2000; Meijerink, 2005; Weible & Sabatier, 2005) as well as to the
political use of science in bolstering preexisting beliefs to legitimize arguments
against an opponent (Eberg, 1997; Leschine, Lind, & Sharma, 2003; Litfin, 2000;
Nicholson-Crotty, 2005; Sato, 1999). Similarly, researchers describe political conflicts
as resulting from an absence of shared scientific knowledge between coalitions
(Meijerink). Case studies also illustrate how top-down, science-based approaches to
policymaking can spark a counter mobilization by the coalition negatively affected
by the implications from the scientific results and initially excluded from deliberations (Nagel, 2006; Weible, Sabatier, & Lubell, 2004). Science, however, is not always
used as a political salvo between opposing coalitions. Cross-coalition learning over
technical issues may occur under the right conditions, such as in professional forums
or when actors have traditions of analytical discourse (Larsen et al., 2006; Meijerink;
Olson et al., 1999).
8. ACF Applications Have Found a Range in the Number Coalitions but
Rarely Discuss Issues of Coordination
Table 3 presents the count and frequency of the number of coalitions in the
applications.1 Approximately 63 percent of the case studies identified at least two
coalitions, but a number of researchers either had no intention of finding coalitions,
found less than two coalitions, or found more than two coalitions. Examples of
Table 3. Number of Coalitions
Number of Coalitions
0
1
2
3
4
5
Total
Frequency
%
7
1
50
15
5
2
80
9
1
63
19
6
3
100
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Policy Studies Journal, 37:1
applications that found no coalitions include Sabatier and Hunter’s (1989) examination of elite belief systems and Leach and Sabatier’s (2005) analysis of the impact of
trust on participants in collaborative institutions. The implication is that the ACF
applies to a variety of issues relevant to the policy process sometimes independent of
coalitions.
The ACF defines coalitions as consisting of members who share policy core
beliefs and engage in a nontrivial degree of coordination. While most applications
discuss beliefs with some level of specificity, very few mention coordination. Weible
and Sabatier (2005) and Weible (2005) are the only two ACF applications that use
relational data to investigate coordination patterns and the role of policy core beliefs
as a glue that binds coalition members together. These two studies find clusters of at
least two competing coalitions as measured by coordination partners, allies, and
information sources. The authors show that coordination was strongly associated
with allies and that policy core beliefs explained more variance in coordination than
perceptions of influential actors in the subsystem. Other scholars discuss coordinated activities within, and between, coalitions using qualitative data. For example,
Abrar et al. (2000) describe how coalition members developed joint projects and
training programs in a domestic violence policy subsystem. Farquharson (2003)
discusses the coordination of surveillance and research activities by coalition
members in a global tobacco policy subsystem. Sato (1999) describes coalition interactions in smoking control in Japan. This work begins to address how coalitions
strategize, the extent that policy core beliefs glue coalition members together, and
coordinate their behavior, but much remains unknown.
9. ACF Applications Largely Overlook Many Components of the Framework, Including
the Devil Shift, Hurting Stalemate, Policy Brokers, and Relatively Stable Parameters
The ACF provides a complex framework that borrows concepts from other
scholarly fields and disciplines, and includes its own lexicon of original concepts.
Some ACF concepts have caught on while others have not. For example, out of the
80 applications, 60, or approximately 75 percent, do not make explicit recognition of
relatively stable parameters. Fewer still mention devil shift, hurting stalemate, and
policy brokers.
The lack of attention to these concepts might simply reflect a lack of interest
among researchers. An alternative reason is that many of these concepts have yet to
be incorporated into explicit theories within the ACF. For example, there is the
potential to formalize a theory of advocacy coalitions within the ACF that would
include the devil shift as a major factor. The devil shift explains how coalition
members exaggerate the negative motives, behavior, and influence of opponents
(Sabatier, Hunter, & McLaughlin, 1987). Building from the ACF’s model of the
individual and the arguments in Sabatier et al. (1987), devil shift predicts that actors
will exaggerate the malicious motives, behaviors, and influence of opponents. The
degree of exaggeration will be contingent on both the distance in beliefs between
opponents and the number of political losses experienced in the policy subsystem.
Among the outcomes of the devil shift are polarized coordination patterns between
Weible/Sabatier/McQueen: The Advocacy Coalition Framework
133
rival coalitions, minimal communication channels between opponents, venue shopping, and long-term disagreement about major policies in the subsystem.
10. A Number of Researchers Have Reintroduced Stages Heuristic into the ACF
One of the limitations of policy process theory in the 1970s and 1980s was an
overreliance on the stages heuristic or the policy cycle (Sabatier & Jenkins-Smith,
1993). In response, the ACF was designed as a subsystem-based theory of political
behavior and policy change that purposely avoids a linear depiction of the policy
process. Despite being designed as an alternative to the stages heuristic, a number of
applications have explicitly or implicitly integrated the policy stages back into the
ACF or have applied the ACF to just one or two stages (e.g., Andersson, 1999; Brown
& Stewart, 1993; Carvalho, 2001; Sato 1999). For example, Marzotto, Burnor, and
Bonham (2000) examine coalition behavior within each policy stage in what they call
the “policy cycle advocacy system” (p. 13). The assumption underlying the arguments in Marzotto et al. (2000, p. 5) is that researchers need two lenses: one to serve
as an organizational tool, such as the stages heuristic, for understanding the life cycle
of a particular policy; and the other, such as the ACF, to zoom in to explain the
political behavior and other events within each stage. Marzotto et al. subsequently
show that coalitions are active in every stage at the same time and bring policies back
through the policy cycle, thereby illustrating how stages in the policy cycle are
neither sequential nor independent. Similarly, Nicholson-Crotty (2005) applies an
original set of hypotheses concerning bureaucratic competition within the ACF
to understand every stage of a policy process in a natural resources conflict. For
Nicholson-Crotty, the stages heuristic serves as an implicit organizing tool to portray
the effects of rival bureaucracies as members of coalitions in the policy process over
time.
Other researchers apply the ACF to a particular stage of the policy cycle. Olson
et al. (1999) argue that coalition politics cannot be understood without accounting
for agenda setting—and in particular the tendency for a dominant coalition to
suppress agenda items to maintain its superior position over a weaker coalition.
Dominant coalitions who cannot control agendas also maintain their superior position by controlling policy formulation (Carvalho, 2001; Leschine et al., 2003). A
number of researchers have applied the ACF to implementation with mixed results.
For instance, the lesson from Smith (2000) is that, while ACF portrays policies as
translations of beliefs, the framework does not describe how those belief-based
policies are put into practice at the operational level or how implementation affects
subsequent learning and policy change. Andersson (1999) argues, in an analysis of
Poland’s environmental policy, that relatively stable parameters shape policy implementation, something not emphasized enough in the ACF literature.
11. ACF Is Frequently Applied and Compared with Other Frameworks and Theories
Of the 80 ACF applications in this review, 36 have applied the ACF with another
theory or framework. The ACF has been applied with the multiple streams frame-
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work (Compston & Madsen, 2001; Dudley & Richardson, 1999), cultural theory
(Eberg, 1997; Kim, 2003), punctuated equilibrium theory (Meijerink, 2005), actorcentered institutionalism (Parrish, 2003), narrative theory (Radaelli, 1999), policy
network analysis (Smith, 2000), the policy entrepreneur model (Mintrom & Vergari,
1996), and the institutional analysis and development framework (Leach & Sabatier,
2005; Lubell, 2003; Stuart, 1991).
Smith (2000), for example, describes how policy processes are driven not only
by actors’ beliefs as in the ACF but also by actors’ resource dependence. Similar
resource dependence arguments can be found in Weible (2005), Green and Houlihan
(2004), and Lertzman, Rayner, and Wilson (1996). Alternately, Lubell (2003) focuses
on the interdependence of beliefs and institutions, specifically the dual relationship
between actors’ belief systems and specific institutional arrangements within which
the actors are involved. These two examples illustrate the limitations of any single
framework or theory, the need to compare multiple theories or frameworks in the
same study, and potential areas for theory development.
12. An Emerging Theory of Subsystem Interdependencies
A challenge in explaining the policy process is the interdependence among
multiple policy subsystems. Policy subsystems have been conceptualized as semiautonomous partitions of a broader political system. Partitioning is a useful approach to
complexity as long as the interdependencies between partitions can be temporarily
ignored. A growing number of problems today, however, span traditional subsystem
boundaries, requiring a serious look at subsystem structures and interdependence.
Salient examples of subsystem-spanning problems are in environmental issues, as
epitomized by climate change and watershed management, but can also be found in
other areas such as the globalization of economies. Litfin (2000), for example, illustrates the blurring of domestic and international climate change policy subsystems.
Working from Zafonte and Sabatier (1998), Fenger and Klok (2001) conceptually
describe three forms of subsystem interdependencies as competitive, independent,
and symbiotic, and then derive expectations about the resulting coalition behavior.
This work begins to develop an ACF theory on overlapping policy subsystems.
Conclusion
Akin to Sabatier and Jenkins-Smith (1993), who assessed the ACF based on six
applications, this essay critically reviews 80 applications of the ACF to glean some of
the framework’s strengths and limitations. The review shows that the ACF is applicable to various substantive topics, across various geographical areas, and with other
policy process theories and frameworks, including the stages heuristic. The most
commonly tested hypotheses involve policy change, learning, and coalition stability.
Although the hypotheses tend to be confirmed, questions remain about the composition and defection of coalition members, the causal mechanisms linking external
events and policy change, and the conditions fostering cross-coalition learning.
Continuing or emerging areas deserving theoretical and empirical attention include
Weible/Sabatier/McQueen: The Advocacy Coalition Framework
135
the role of institutions and resource dependence in the framework, subsystem interdependencies, and coordination within, and between, coalitions.
The continued accumulation of generalizable knowledge will be facilitated by
two research strategies. The first is clearly specified methods of data collection
and analysis. This review found a large number of applications relied upon
unspecified methodology, which threatens the overall legitimacy of a study
and limits a study’s contribution to policy process research. The goal should be
intersubjectively reliable methods that serve as the cornerstone for making
research transparent and provide a basis for collective learning. The second is to
describe external subsystem factors—especially relatively stable parameters—when
describing internal subsystem affairs. Too many applications in this review overlooked relatively stable parameters, thereby limiting comparisons across cases.
Building generalizable knowledge of the policy process requires a research mentality that encompasses rigor in single case study methodology along with a deliberate effort to communicate how the findings contribute to a large N collection of
case studies.
Within most policy subsystems are coalitions, which remain the linchpin of
most ACF studies. Existing research finds that coalition membership is relatively
stable over time and that policy core beliefs glue coalition members together,
but defection is also common. What is needed is original theorizing and deliberate
research designs that investigate both stability and defection of coalition members
over time. Examining coalition stability and defection will lead researchers toward
issues of coalition strategies; the devil shift; coordination within, and between,
coalitions; member types and composition; and learning within, and between,
coalitions.
Related to learning within, and between, coalitions is the role played by scientific and technical information in the policy process. This review supports the
arguments found in Weible (2008) that the role of scientific and technical information in the policy process is best understood in combination with the context of
the policy subsystem. In adversarial policy subsystems marked by high levels of
conflict, coalitions will more likely use scientific information as political salvo
against an opponent, learning will more likely occur within coalitions than
between coalitions, professional forums will more likely be ineffective, and coalitions will more likely rely on different analytical disciplines in making their arguments. In collaborative policy subsystems marked by intermediate levels of
conflict, many of the expectations are reversed: coalitions will more likely use scientific and technical information for cross-coalition learning, professional forums
will more likely be effective, coalitions will more likely rely on multidisciplinary
sources of information, and belief change will more likely occur at both the policy
core and secondary belief level. The factors that contribute to a shift from an adversarial subsystem to a collaborative policy subsystem include a hurting stalemate,
external event, or both.
The study of policy processes via the ACF is often carried out in conjunction with
other policy process theories and frameworks. One finding from this review is the
large number of scholars who combine the stages heuristic with the ACF. Clearly,
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issues of agenda setting, formulation, adoption, implementation, and evaluation are
important conceptual topics and are a part of the policy process. The stages heuristic
also represents critical junctures in the history of a policy subsystem and, therefore,
should not be ignored. However, the risk of integrating the stages heuristic into a
system-based framework is that researchers might, for example, fall back on the
faulty assumptions underlying the stages heuristic. What is needed is a set of guidelines for bringing aspects of the stages heuristic into system-based policy process
frameworks and theories.
We, therefore, offer the following guidelines to researchers wanting to integrate
aspects of the stages heuristic into a policy process framework or theory, such as the
ACF. First, given that the stages heuristic is a typology and lacks an underlying
causal theory, we recommend that researchers should adhere to the ACF’s assumptions, especially regarding beliefs as a causal driver. Actors in the ACF devote years
to translating their beliefs into policy using multiple political strategies and venues.
Hence, from an ACF perspective, the stages heuristic can be thought of as a political
strategy (e.g., changing an agenda) or as a venue (e.g., a legislature in policy formulation). Second, the stages heuristic narrowly focuses on just one policy—but coalitions operate across multiple policies. Thus, researchers wanting to study just one
policy should recognize that coalitions will likely be attending to multiple policies
simultaneously. Third, coalitions operate across stages, and researchers should recognize that coalitions will, for example, simultaneously devote attention to fighting
the implementation of a given policy and seek to reformulate the same policy in a
legislature. Fourth, the stages heuristic does not address group formation or strategies. The ACF provides an explanation for coalition formation and structure based on
coordinated behavior guided by policy core beliefs. Researchers are encouraged to
investigate the degree of coordination among coalition members who operate across
different policy stages.
A limitation of this essay was mentioned by an anonymous referee who
described an earlier version as “self-indulgent and inward-focused” and went on to
argue that reviews of this kind “are commonly seen as characteristics of disciplines
that are running low on ideas, relevance, or intellectual energy.” We agree that this
essay is inward focused by deliberately taking stock of existing ACF applications in
hopes of identifying future research directions. We argue, however, that gleaning
lessons from comprehensive reviews is probably one of the best ways to move
forward with any theory or framework. We disagree that the ACF literature is short
on ideas, relevance, or intellectual energy. Indeed, this essay shows that the ACF
literature continues to expand in applications in diverse geographical and topical
areas and to provide a useful lens—especially in conjunction with other theories and
frameworks—for explaining the policy process.
Christopher M. Weible is an Assistant Professor in the School of Public Affairs at the
University of Colorado Denver.
Paul A. Sabatier is a Professor in the Department of Environmental Science and
Policy at the University of California Davis.
Kelly McQueen is a graduate student in the School of Public Policy at the Georgia
Institute of Technology.
Weible/Sabatier/McQueen: The Advocacy Coalition Framework
137
Notes
We would like to recognize Jim Flowers, Nicholas Harvey, Sarang Shah, and Taner Osman for their
generous effort in helping to review the ACF applications. The original version of this manuscript was
prepared for, and presented at, “The Next Generation of Public Policy Theories: Policy Theory Workshop,”
February 27–29, 2008, sponsored by the Department of Political Science and the Center for Applied Social
Research at the University of Oklahoma, and by the Policy Studies Journal. We would also like to thank
Peter deLeon and two anonymous reviewers for their constructive feedback on previous versions of the
manuscript.
1. For applications where the number of coalitions changed over time, we coded the number of coalitions
as the maximum found over the period of study.
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