Introduction
By Ozeh Cornelius
The
Belief System model of policy making is a brainchild of Prof. Paul Armand Sabatier
of the University of California, Davis, a professor of Environmental Science
and Policy and his Advocacy Coalition Framework (ACF) scholars.
Sabatier
and Jenkins-Smith (1993) developed the ACF as a theoretical framework to
analyze intense conflict in the policy making process (Kweku 2009), and policy change. As a policy framework for
explaining policy change, the ACF has been around for a long time and it has
been widely applied by scholars to explain policy change mainly in the United
States and in Canada (Ibid.).
ACF
within this long time of existence from around 1987 has undergone several
modifications but “the original version of the ACF sought to make important
contributions to the policy process literature by responding to several
perceived “needs”: a need to take longer term time perspectives to understand
policy change; a need for a more complex view of subsystems to include both
researchers and intergovernmental relations; a need for more attention to the
role of science and policy analysis in public policy; and a need for a more
realistic model of the individual rooted more deeply in psychology rather than
microeconomics,” (Weible and et al
2011).
Belief
System model of policy making and other analytical constructs were devised by
the ACF scholars led by Paul Armand Sabatier to drive home those needs outlined
above.
Our
interest here is on the belief system construct of Paul Sabatier’s Advocacy Coalition
Framework (ACF) of policy making; but a proper understanding of the subject
could not be achieved without demystifying the other analytical constructs of
the school.
Clarification of Concepts
Associated with the Belief System Model of Policy Making
Belief System
This
is simply the policy actors’ values. People
engage in politics to translate their beliefs into action, (Cairney
2013). Also, to simplify events and the
world around them, ACF individuals filter perceptions through their belief
system (Fischer and Miller, n.d). The ACF assumes that the defining
characteristic of individuals is their three-tiered hierarchical belief system
(Sabatier and Jenkins-Smith 1993, 1999). On the top tier are deep core beliefs,
which are normative/fundamental beliefs that span multiple policy subsystems
and are very resistant to change (for example, political conservatism). In the
middle tier are policy core beliefs, which are normative/empirical beliefs that
span an entire policy subsystem (Weible
2006).
Policy Subsystems
This
is defined as groups of formal and informal actors who are actively involved in
a substantive policy (Sabatier, 1987). A policy subsystem is defined by its
territorial boundary, a substantive topic, and by the hundreds of policy
participants from all levels of government, multiple interest groups, the
media, and research institutions (Fischer and Miller,Op. Cit.).
Stakeholders
specialize in a policy subsystem and maintain their participation over long
periods of time in order to foster, among other reasons, the
institutionalization and implementation of policy objectives (Sabatier and
Jenkins-Smith1993). These stakeholders often carry out several strategies to
influence the decisions in several venues. For example, stakeholders might
simultaneously pressure political sovereigns, court and the media to consider
litigation, and try to convince opponents to support their views in public
meetings (Weible 2006).
Succinctly put, “Subsystems are
issue-specific networks,” (Cairney
Op. Cit.).
Advocacy Coalition
A coalition contains, ‘people from a variety of
positions (elected and agency officials, interest group leaders, researchers)
who share a particular belief system’ and ‘who show a non-trivial degree of
coordinated activity over time,’ (ibid.). The ACF assumes that
stakeholders are primarily motivated to convert their beliefs into actual
policy and thereby seek allies to form advocacy coalitions to accomplish this
objective. Advocacy coalitions include actors of similar policy core beliefs
who engage in a nontrivial degree of coordination (Sabatier and Jenkins-Smith
1999). Belief
systems are the glue that bind advocacy coalitions
(Sabatier & Jenkins-Smith, 1993).
Policy Learning
Sabatier
(1993) defines policy learning as a relatively enduring alteration of thought
or behavioural intentions that are concerned with the attainment (or revision) of
the precepts of a policy belief system.
To
make it more operational and precise it is useful to distinguish between 3 types
of policy learning:
Instrumental
learning: Technical learning about instruments – about effects
how the instruments may be improved to achieve set goals;
Conceptual
learning or problem learning: seeing things from a
different evaluative viewpoint (in a ‘new light’); this is when the outlook on
a ‘problematique’ changes; it is called conceptual learning because it tends to
be accompanied with the development or adoption of new concepts, principle and images.
Social
learning: learning about values and other ‘higher-order’
properties such as norms, responsibilities, goals, and the framing of issues in
terms of causes and effects selected for attention (Clark n.d).
Coalitions learn from policy implementation.
Learning takes place through the lens of deeply held beliefs, producing
different interpretations of facts and events in different coalitions (Cairney
Op. Cit.). They tend to filter or ignore information that challenges their
belief and readily accept information that bolster their beliefs. These perceptual
filters tend to discount even high quality technical information if it
conflicts with their beliefs and accept technical information with high
uncertainty if it supports their beliefs (Fischer and Miller, Op. Cit.).
Policy Broker
We
have said earlier that the ACF assumes that stakeholders are primarily
motivated to convert their beliefs into actual policy and thereby seek allies
to form advocacy coalitions to accomplish this objective. Advocacy coalitions
in a policy subsystem compete for dominance.
In
competitive policy subsystems, policy disagreements between advocacy coalitions
often escalate into intense political conflicts. These conflicts are often
mediated by "policy brokers." Policy brokers seek to find reasonable
compromise among hostile coalitions (ibid.). Paul Cairney
put it in a clear statement when he stated that subsystems contain actors who mediate between coalitions and
make authoritative decisions (although policy brokers may be members of
coalitions). Many different actors play the policy broker role. Policy brokers
include elected officials, high civil servants, and courts (Fischer and
Miller, Op. Cit.).
An Overview of Paul Sabatier’s Belief
System of Policy Making
Paul
Sabatier and his ACF colleagues argue that actors in policy making strive to
translate their beliefs into policies. They divided the belief system into
three tiers. The structure of belief systems applies both to policy elites and
to government programmes, according to Sabatier and Jenkins-Smith (1993).
Deep
Core
|
Policy
Core
|
Secondary
Aspects
|
|
Defining
Characteristics
|
Fundamental,
normative and ontological axioms
Examples:
The
nature of man:
inherently
evil or socially redeemable; the relative priority of various ultimate
values: freedom,
security,
health,
knowledge
|
Fundamental
policy positions concerning the basic strategies
for
achieving core values within the subsystem
Examples:
Identification
of key issues and groups whose welfare is
of
greatest concern; proper distribution of authority between government and
market;
proper distribution of
authority
among levels of government; priority accorded
to
policy instruments
(regulation,
covenants,
economic
instruments);
technological
optimism vs.
pessimism
|
Instrumental
decisions
and
information searches necessary to implement policy core
Examples
Seriousness
of specific aspects of the problem in specific locales; causal links;
efficacy of administrative rules, and policies, appropriateness of funding
arrangements
and
budgets; statutory
interpretation
|
Scope
|
Across
all policy
subsystems
|
Specific
to a subsystem
|
Specific
to a subsystem or
a
sub-subsystem
|
Susceptibility
to Change
|
Very
difficult; akin to a religious conversion
|
Difficult
but can occur if experience reveals serious anomalies
|
Moderately
easy; this is the topic of most
administrative
and even legislative policy making
|
Type
of Learning
|
Social
learning
|
Problem
learning, social learning
|
Instrumental
learning
|
Source: adapted from Sabatier and
Jenkins-Smith (1993, p. 221)
Paul
Sabatier argues that the expansive set of actors in policy systems have their
respective three-tiered belief systems.
The ACF assumes that the defining
characteristic of individuals is their three-tiered hierarchical belief system
(Sabatier and Jenkins-Smith 1993, 1999). On the top tier are deep core beliefs,
which are normative/fundamental beliefs that span multiple policy subsystems
and are very resistant to change (for example, political conservatism). In the
middle tier are policy core beliefs, which are normative/empirical beliefs that
span an entire policy subsystem. Policy core beliefs are still resistant to
change but are more pliable than deep core beliefs. On the bottom tier are secondary
beliefs, which are empirical beliefs that relate to a subcomponent (either
substantively or territorially) of a policy subsystem. Of the three layers of
beliefs, secondary beliefs are most susceptible to change in response to new
information and events (Weible 2006).
These
expansive set of actors involved in policy systems according to Sabatier, “may
be aggregated into coalitions; and policy designs are interpreted as
translations of coalition beliefs” (Sabatier, 1988). It follows therefore to
mean that nothing is a policy but the belief system of the dominant coalitions in
policy subsystems.
The
anti-gay policy of the Federal Republic of Nigeria for instance, is
understandable with this belief system model in which the deep core beliefs
obviously held by coalitions that dominated the policy subsystem on gay
marriage was purely African belief that repudiates same sex marriage. That
African belief system shared with like-minded coalitions held sway and produced
the policy.
Belief
system model of policy making wields a strong explanatory power on virtually all
conceivable policies but this paper is not comfortable with its trivialization
of some important factors that influence the outcome of policies such as the
public opinion and interests.
Criticizing the Belief System Model
of Policy Making
The
model under discussion highly trivialized public opinion. The concept of public
opinion has been employed within the ACF to mean different things which this
study argues that they are not befitting to the overwhelming influence of
public opinion on policy making.
Jones and Jenkins-Smith (2009)
chronicled the evolution of the treatment of the concept of public opinion
within the ACF thus: First, public opinion acts as an exogenous constraint
outside of the policy subsystem. Second, public opinion can also operate as an
internal shock within a subsystem, critically redistributing resources
(Sabatier & Weible, 2007). And third, public opinion is a resource that
elites within subsystems will tap when possible (Shanahan
and et al 2011).
Public
opinion just like other actors in policy subsystems is also under the influence
of belief systems. It is actually the belief system of the majority of the
people that surfaces as the public opinion. One could simply describe public
opinion as an aggregate view of persons with the same belief system. The ACF
scholars should have elevated public opinion to the status of a coalition so
that when other coalitions shop for the “resources,” public opinion, they would
actually be seeking alliance with the public opinion coalition.
On
the other hand, the role of interests in the determination of actors’ policy
choices was utterly disregarded in this ACF model. Weible (2006) came close to discovering this salient factor, “interest”
in his An Advocacy Coalition
Framework Approach to Stakeholder Analysis: Understanding the Political Context
of California Marine Protected Area (MPA) Policy; but he was unable to give
it a baptismal name. Belief and interest disagree at times and that was exactly
what happened when he observed thus:
Stakeholders from both sides of the
debate agree on some aspects of the severity and causes of the problem and on
some important uses of MPAs. Unfortunately, there is a mismatch between where
they agree on a problem and where they agree on the important uses of MPAs…
most stakeholders agree that California fisheries are in trouble but disagree
that MPAs are a viable approach to fisheries management…. Weible (2006).
What
caused the mismatch was belief-interest disagreement. In the study by Weible,
commercial fishers believed that fisheries were in danger (belief system) but insisted
that MPAs should not be used (interest); because
the implementation of MPAs will affect their income (emphasis mine). Upon
disagreement, “interest” takesv precedence over “belief system”.
Conclusions
The
belief system model of policy making as propounded by Paul Armand Sabatier and
his ACF colleagues is a strong analytical tool of policies. It gives a very
clear picture of how policies are simply the crystal reflections of the belief
system of the dominant coalitions in policy subsystems. The model however, trivialized
public opinion as mere resources to be accessed by coalitions to drive home
their policy positions. Public opinion is better treated as a full-fledged
coalition. It also disregarded the role of interest in the complex world of
policy making. It is observable as in Weible (2006) that “interests” influence
coalitions choice even more than the ACF’s prided “belief system.”
References
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