Narrative policy analysis and policy change theory rarely intersect in the literature. This research
proposes an integration of these approaches through an empirical analysis of the narrative political
strategies of two interest groups involved in policy debate and change over an eight-year period in the
Greater Yellowstone Area. Three research questions are explored: (i) Is it possible to reconcile these
seemingly disparate approaches? (ii) Do policy narrative strategies explain how interest groups expand
or contain policy issues despite divergent core policy beliefs? (3) How does this new method of analysis
add to the literature? One hundred and five documents from the Greater Yellowstone Coalition and the
Blue Ribbon Coalition were content analyzed for policy narrative strategies: identification of winners
and losers, diffusion or concentration of costs and benefits, and use of condensation symbols, policy
surrogates, and science. Five of seven hypotheses were confirmed while controlling for presidential
administration and technical expertise. The results indicate that interest groups do use distinctive
narrative strategies in the turbulent policy environment.
2. During the last two decades, the work of social constructionists in the field of
NPA (e.g., Fischer & Forrester, 1993; Roe, 1994; Stone, 2002) has developed concur-
rently with that of policy change theorists. NPA focuses on the centrality of narra-
tives in understanding policy issues, problems, and definitions and does so without
the grand theoretical aspirations of the more traditional policy change works. One of
the most developed works in the narrative genre is that of Deborah Stone (2002),
whose Policy Paradox is an NPA gold mine of “mini-theories” about agenda setting,
issue and problem definition, and policy dynamics. The centerpiece of Stone’s work
is the use of literary devices such as characters, plots, colorful language, and meta-
phors to analyze policy narratives. In particular, the storyteller’s political tactics are
revealed in how they construct who wins and who loses in a policy story (or who
reaps the benefits and pays the costs), how they characterize policy issues and their
opposition, and how they either entangle policies in larger cultural issues or alter-
natively try to ground such issues in the certainty of scientifically deduced numbers
and facts. Ultimately, Stone (p. 229) asserts that the goal of this strategic problem
definition is to portray a political problem so that one’s favored course of action
appears to be in the broadest public interest.
With some exceptions (Baumgartner, 1989; Baumgartner & Jones, 1993, pp. 27–9;
Hajer, 1993; Radaelli, 1999; Schneider & Ingram, 2005), NPA and the policy change
literature rarely intersect. The exclusion of narratives from the grand theories of
policy change is grounded in the belief that narratives are value-based random
garble. Sabatier (2000, p. 138), for example, argues that constructivists “have dem-
onstrated very little concern with being sufficiently clear to be proven wrong” and
that their lack of clarity leads him to have “no interest in popularizing their posi-
tion.” We argue that narratives are the lifeblood of politics. Narratives are both the
visible outcome of differences in policy beliefs (McBeth, Shanahan, & Jones, 2005)
and the equally visible outcome of political strategizing. Both policy beliefs and
political strategies, as found in policy narratives, are not random occurrences. Policy
beliefs are arguably stable, and political strategies are predictable.
NPA and Policy Change Theory
Sabatier and Jenkins-Smith (1993, p. 16) outline premises for their ACF, for
which we assert that narrative theory can serve a methodological role. First, they
claim that policy change must be analyzed over time, a decade or longer; narratives
are written words that can easily be documented and tracked through a temporal
perspective. Second, they purport that policy change can be understood through the
examination of political subsystems (advocacy coalitions) that seek to influence
governmental decisions. Other research (McBeth et al., 2005) has discovered that the
narratives generated by political subsystems in the polity at large, not just in the
legislative arena, also contain stable core policy beliefs and are a legitimate source of
policy change analysis.
The work of Baumgartner and Jones (1993) is also essential for a study of
narratives and policy change. They point out that, at any particular time, an interest
group is part of a winning policy monopoly or they are part of an out-of-power
88 Policy Studies Journal, 35:1
3. minority coalition. However, with “wicked problems” (Rittel & Webber, 1973),
where rationality and science are minimized in importance, winning and losing
is more of a perception than necessarily a reality. Wicked problems resist “resolu-
tion by appeal to the facts” (Schon & Rein, 1994, p. 4) and beliefs are grounded in
competing cultural norms (Wood & Doan, 2003, p. 641). Jenkins-Smith and Sabatier
(1993, p. 49) furthermore assert that when core beliefs are at stake, competing sides
will defend their own belief systems and attack the belief systems of the opposition.
Yet, as later hypothesized by Sabatier and Jenkins-Smith (1999, p. 124), through the
development of technical expertise, coalitions move toward policy learning. Because
of the intense value-based conflict between competing groups, policy narratives are
an important element of study for wicked problems and add to the ability of more
traditional policy change theories to understand the strategic representation of
values in framing the conflict.
Interest groups attempt to maintain, demonstrate, and increase their political
power as they seek to win a favorable policy. Furthermore, whether an interest group
perceives themselves as winning or losing on a policy issue greatly influences how
they play politics. According to Schattschneider (1960, p. 16), winning groups try to
restrict participation (issue containment) in a policy issue by limiting the scope of
the conflict whereas losing groups try to widen participation (issue expansion) in
a policy issue. Such a conclusion is reinforced in a wide variety of literature (e.g.,
Baumgartner, 1989; Cobb & Elder, 1983; Baumgartner & Jones, 1993). While Radaelli
(1999, p. 674) concludes that narratives are understood within “broader political
dynamics,” the unanswered questions are how do the policy narratives of interest
groups play into the equation of issue containment and issue expansion in wicked
policy problems and how do these narratives play into the role of policy change (or
lack of change, thus contributing to policy intractability)? Our methodology,
drawing on the insights of NPA, Baumgartner, Jones, Sabatier and Jenkins-Smith,
allows us to answer these questions.
Primary Beliefs and Political Strategies
We assert that interest group narratives possess both primary beliefs and politi-
cal strategies. This differs slightly from Sabatier and Jenkins-Smith’s (1999, p. 122)
view of policy beliefs. They contend that policy beliefs are composed of core beliefs
that remain stable and secondary beliefs that are more susceptible to change. The
same principle of core beliefs and secondary beliefs can be applied to the study of
policy narratives. When we read a policy narrative regarding an environmental
issue, part of the narrative consists of underlying beliefs in such issues as federalism,
science, and the relationship between humans and nature. These are primary policy
beliefs held by interest groups, and narratives reveal that they tend to be stable over
time (McBeth et al., 2005).
We argue that narratives also possess political strategies and that these elements
are much more dynamic. In contrast to Sabatier and Jenkins-Smith (1993: 30–31),
who define secondary beliefs as instrumental decisions of policy implementation, we
assert that in a policy narrative, the secondary political strategies (not necessarily
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 89
4. beliefs) include rhetorical devices outlined by Deborah Stone (2002), among others.
Political strategies are an important and perhaps underdeveloped element of the
ACF. As Brown and Stewart (1993, p. 101) argue, the study of policy change must
focus on “tactics employed by policy advocates.” As found in narratives, these tactics
or strategies shift depending on whether or not the coalition perceives itself as
winning. Competing policy narratives incorporate strategies such as identification of
winners and losers, framing who benefits and who sustains costs in the policy
conflict, the use of condensation symbols, the wrapping of issues in larger policy
surrogates, and the use of scientific uncertainty. In turn, the choice of narrative
strategy is driven by the group’s perception of whether it is winning or losing on the
policy issue. The analysis of both primary beliefs as defined by Sabatier and Jenkins-
Smith (1999, p. 122) and political strategies (as informed by Stone) is an unexplored
area in which the two fields intersect and strengthen each other. While traditional
policy change theory can show that groups act strategically, our methodology draws
on NPA to show how groups act strategically through narratives.
Political Narrative Strategies
Five narrative strategies are defined in the succeeding discussion. These political
strategies are hypothesized to contain the issue if the group is winning or to expand
the issue if the group is losing.
1. Identifying Winners and Losers. As part of issue containment and expansion, inter-
est groups will strategically include or exclude mention of specific winners and
losers. Interest groups that perceive themselves as winning on a policy issue are
more likely to identify specific winners in their policy narratives, whereas interest
groups that perceive that they are losing on a policy issue are more likely to identify
specific losers. Winning strategies attempt to contain the issue by illustrating that
the status quo is positive and no change is necessary. In Baumgartner and Jones’s
(1993) terminology, these groups attempt to preserve the current image of a policy
problem simply because this policy frame has helped to achieve the status of a policy
monopoly. The goal is to maintain a “minimum winning coalition” (Riker, 1962);
expanding the coalition would necessarily entail compromises in policy beliefs and
outcomes, which, in turn, weakens the power of the members of the policy
monopoly. On the other hand, losing groups identify losers in the policy conflict in
the hope of mobilizing opposition in order to change the status quo. Stone (2002,
p. 228) argues that “both sides try to amass the most power” and that it is the loser
“who seeks to bring in outside help.”
2. Construction of Benefits and Costs. Baumgartner and Jones (1993, p. 19) contend
that losing groups seek to redefine issues in ways that will mobilize indifferent
citizens and groups in the hope that this mobilization will destabilize policy equi-
librium. This expansion of an issue to “heightened general attention” is pivotal in
policy change (Jones & Baumgartner, 1993, p. 20). In terms of narrative theory, when
a competing interest group is losing, they use their policy narratives to attempt to
90 Policy Studies Journal, 35:1
5. reallocate attention and expand the issue by diffusing costs and concentrating ben-
efits. This strategy makes it appear that only a few (if any) groups are benefiting from
the status quo while many groups are paying the costs. This tactic attempts to
mobilize the public and bring new players into a coalition. Conversely, when a group
is winning, they are much more likely to contain the issue by diffusing benefits and
concentrating costs on a small group. This narrative strategy seeks to maintain the
status quo and to restrict a wide-scale mobilization.
3. The Use of Condensation Symbols. Jones and Baumgartner (1993, p. 26) argue that
“every public policy problem is usually understood, even by the politically sophis-
ticated, in simplified and symbolic terms.” Stone (2002, p. 137) asserts more directly
that “symbolic representation is the essence of problem definition in politics.” Thus,
we can hypothesize that interest groups that are winning or losing on a policy issue
will use “condensation symbols” or a language that “reduce[s] complicated concepts
into simple, manageable, or memorable forms” (Achter, 2004, p. 315). Interest groups
will use condensation symbols to define the policy issue and to characterize their
opponents. We argue that winning groups have fewer incentives to use condensation
symbols because doing so might invoke unintended consequences such as riling of
the opposition. Losing groups, however, have tremendous incentives to negatively
portray both the issue and their opponents through the use of condensation symbols.
Again, their goal is to both rally their troops and call in additional reinforcements by
expanding the scope of the conflict.
4. The Policy Surrogate. In his discussion of the many causes of wicked resource-
based policy conflict, Nie (2003) suggests that a key cause of conflict is the “policy
surrogate.” Nie (p. 314) argues that “relatively straightforward policy problems can
be turned wicked when they are used by political actors as a surrogate to debate
larger and more controversial problems.” For environmental policy issues in the
Western United States, this means that issues like bison management and snowmo-
bile access are wrapped in larger persistent controversies of Western communities:
concerns about federalism, the role of public lands, and the fear of outsiders, to name
a few. Our argument is that losing groups strategically entangle policy issues in
larger, emotionally charged debates in an effort to gain a competitive advantage by
expanding the scope of the policy issue. In short, these policy surrogates are used to
ignite the larger controversies already simmering in the political culture and to
mobilize opposition.
5. Scientific Certainty and Disagreement. Nie (2003, p. 323) argues that scientific dis-
agreement is also a major cause of intractable natural resource-based political con-
flict. Furthermore, Nie (p. 323) notes that environmental policies have increasingly
become disputes over science and concludes that political actors “frame value and
interest based political conflict as scientific ones” and that they “escape responsibil-
ity for making the tough choices required of them.” Thus, this driver, contradictory
to the policy surrogate driver, suggests that policy actors intentionally reduce the
scope of policy issues, ignoring the larger normative and cultural issues that invari-
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 91
6. ably surround resource-based environmental conflict. We argue that groups that are
winning in a policy issue are likely to define the issue in terms of scientific certainty,
thus ignoring the larger normative issues involved in the controversy. Such a cer-
tainty attempts to bring closure to debates surrounding policy issues, maintains the
status quo and the minimum winning coalition, and simultaneously hopes to demo-
bilize the opposition. Conversely, losing groups attack scientific results and present
a scientific disagreement in an attempt to open up the issue for a continued
deliberation.
Research Questions
This study addresses three research questions. First, we attempt to methodologi-
cally demonstrate the useful intersection of NPA and policy change theory. Can such
ontologically opposing theories be legitimately brought together in the study of
policy change? Second, we operationalize NPA into measurable tools to examine how
groups expand or contain policy issues, not just that they do. Do policy narrative
strategies of interest groups explain how these groups expand or contain policy
issues despite divergent core policy beliefs? Third, how does this new method of
analysis add to the existing literature on policy change?
The Case Study
The systematic analysis of different interest groups’ narrative political strategies
is conducted as a case study in the turbulent policy arena of the Greater Yellowstone
Area (GYA). The 19 million acres of the GYA, with Yellowstone National Park (YNP)
comprising 2.2 million acres of the region, are not only a world famous area for
geysers, wildlife, and scenic wonders but a well documented hotbed of political
conflict (e.g., Cawley & Freemuth, 1993; Tierney & Frasure, 1998; Wilson, 1997). In
fact, environmental policymaking in the region is often intractable or wicked (Rittel
& Webber, 1973). To use the terminology of Jenkins-Smith and Sabatier (1993, p. 49),
the conflict is intense and highly political since core policy beliefs (e.g., federalism,
the relationship between humans and nature, science) are disputed and competing
sides ground their arguments in myth (Tierney & Frasure, 1998).
Environmental groups and scientists have sought to redefine Yellowstone’s
image from that of an isolated national park with definitive boundaries to that of the
only intact ecosystem left in the continental United States (Clark & Minta, 1994). To
use the theory of Baumgartner and Jones (1993), environmental groups have sought
to redefine the image of the area from “Yellowstone as zoo” to “Yellowstone as an
open ecological system.” Such an effort at image redefinition has intensified the
political conflict in the past decade. Two interest groups have dominated efforts by
competing advocacy coalitions to define the policy images of GYA. The Blue Ribbon
Coalition (BRC) represents motorized recreation users (wise use coalition) and is
based in Pocatello, Idaho.1
The Greater Yellowstone Coalition (GYC), based in
Bozeman, Montana, represents the environmental coalition.2
These two groups are
“purposive” interest groups, for those who join pursue ideological and issue-
92 Policy Studies Journal, 35:1
7. oriented goals without material rewards (Berry, 1989, p. 47). This is important given
the Sabatier and Jenkins-Smith (1999, p. 134) hypothesis that purposive groups are
more constrained in their willingness to compromise beliefs and policy positions.
From 1997 through 2004, the politics of the GYA have been characterized by
continuous changes in public policy, instability, and policy wickedness. Policy
monopolies have collapsed for short periods of time only to find resurgence and an
ability to regain political power. During the years of the Clinton administration,
environmental groups pushed large policy initiatives into effect. The policy issues
that demonstrated newfound environmental power in the GYA included wolf rein-
troduction in 1995, regulations that ended snowmobiling inside YNP in 2000, and a
national roadless initiative in national forests in 1999.
There is one exception to the wave of Clinton GYA environmental policy success,
where the wise use coalition retained their monopoly: the management of free-
ranging bison. In the winter of 1996–97, over 1,100 bison were killed by the Montana
State Livestock Department with assistance from the National Park Service because
of concern over the potential role of bison in brucellosis transmission to cattle. Efforts
by the Clinton administration and environmentalists to end the killing failed as a
powerful subsystem of ranchers, federal and state elected officials, and the U.S.
Department of Agriculture Animal, Plant, Health, Inspection Services retained its
historic hegemonic stance.
Yet again, with the exception of the bison controversy, the policy changes in the
1990s were overwhelmingly in the direction of the GYA environmental advocacy
coalition. The election of George W. Bush in 2000, however, led to a large-scale
resurgence of the wise use coalition in at least two policy areas. Bush’s first term saw
the dramatic reversal of the Clinton era snowmobile ban in YNP. The president’s
second term saw the overturning of the roadless rule in favor of state control over the
use of national forests. It is in the context of this turbulent policy arena from 1997
through 2004 that the BRC and the GYC both generated strategic political narratives.
Research Methodology
A content analysis was performed on one hundred five documents produced by
the GYC (52 documents) and the BRC (53 documents) over eight years (January 1,
1997 through December 31, 2004). The documents address one of three policy issues
in the GYA: (i) bison and brucellosis (14 documents); (ii) snowmobile access in YNP
(70 documents); and (iii) the roadless initiative (21 documents). Our choice of content
analysis was straightforward. Content analysis is unobtrusive, allows for a reliability
analysis, permits a longitudinal analysis, and is efficient and inexpensive. The docu-
ments analyzed were readily archived and complete, thereby avoiding some of the
disadvantages of using content analysis (Johnson & Reynolds, 2005, pp. 232–34).
Based on NPA and policy change theory, we propose seven hypotheses predicting
an association between use of a winning or losing narrative frame (independent
variable, see Table 1) and seven different narrative political strategies (dependent
variables, see Table 1).
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 93
8. Hypotheses
For the following seven alternative hypotheses, each has a null hypothesis that
asserts no association between winning or losing policy narrative frames and the
attending narrative political strategy. Because these are nominal-level variables, no
direction is predicted.
Hypothesis 1a: There is an association between winning policy narrative frames
and identification of winners in the narrative.
Hypothesis 1b: There is an association between losing policy narrative frames and
identification of losers in the narrative.
Hypothesis 2: There is an association between winning policy narrative frames and
the diffusion of benefits in the narrative; similarly, there is an association between
losing policy narrative frames and concentration of benefits in the narrative.3
Hypothesis 3: There is an association between winning policy narrative frames and
the concentration of costs in the narrative; similarly, there is an association between
losing policy narrative frames and diffusion of costs in the narrative.
Hypothesis 4: There is an association between losing policy narrative frames and
use of condensation symbols.
Table 1. Operationalization of Dependent, Independent, and Control Variables
Variables Definition n
Dependent Variables
Identification of winner Identify a winner of policy objective
0 = none identified (no); 1 = winner (yes)
105
Identification of loser Identify a loser of policy objective
0 = none identified (no); 1 = loser (yes)
105
Benefits Concentrate or diffuse benefits of policy objective
0 = concentrated; 1 = diffused
61
Costs Concentrate or diffuse costs of policy objective
0 = concentrated; 1 = diffused
85
Condensation symbol Reduces issue into loaded, dichotomous symbol
0 = no use; 1 = used condensation symbol
105
Policy surrogate Wraps a specific issue in larger normative issues
0 = no use; 1 = used policy surrogate
105
Science Use of scientific certainty or disagreement
0 = scientific certainty; 1 = scientific disagreement
54
Independent Variable
Winning–losing The narrative frame regarding policy objective
0 = losing; 1 = winning
105
Control Variables
Presidential administration President at the time the narrative was written
0 = Clinton; 1 = Bush
105
Use of science Whether the narrative used science or not
0 = no science used; 1 = used science
105
Source: Greater Yellowstone Coalition and Blue Ribbon Coalition documents, 1997–2004.
94 Policy Studies Journal, 35:1
9. Hypothesis 5: There is an association between losing policy narrative frames and
use of policy surrogates.
Hypothesis 6: There is an association between winning policy narrative frames and
the use of scientific certainty in the narrative; similarly, there is an association
between losing policy narrative frames and the use of scientific uncertainty in the
narrative.
Dependent Variables
Temporally, whether the policy narrative is winning or losing precedes the
political strategies used; thus, the dependent variables in this study are the political
strategies (see Table 1). Using content analysis, a series of questions was developed
to operationalize the dependent variables for the seven hypotheses (see Appendix A,
questions 1–8 on the codebook).
Independent Variable
Whether a policy narrative is winning or losing explains what political strategies
are employed. The problem of how to operationalize whether an interest group was
winning or losing invoked much discussion among research team members. At one
point, an objective measure was going to be utilized. In other words, based on
executive, judicial, and administrative decisions, the interest group would be deter-
mined to be winning or not. Interestingly, this proved difficult because of the vola-
tility of Yellowstone policy issues during the time period under study. No interest
group could be said to enjoy a true policy monopoly throughout the period (the
bison issue is the most likely exception) because governmental decisions on these
issues rarely achieved a permanent or stable status. Thus, the team decided that what
was important in narrative terms was not objective winning or losing, but rather the
perceptions of the interest group on whether they were winning on an issue (the
group supported the status quo) or losing (the group felt that they were under attack
in the policy environment). Question 9 of the code book in Appendix A measures
this perception of winning and losing.
Control Variables
ACF controls of coalitional resources (i.e., presidential administration) and coa-
litional policy learning (i.e., whether or not scientific evidence was used) were used.
The ACF theory asserts that over time, policy change is, in part, a function of
changing governing coalitions (affecting coalitional resources) and coalitional tech-
nical expertise (impacting policy learning). To better assess the relationship between
political strategies and winning—losing narrative frames, each Chi-square test (in
succeeding discussions) was subsequently controlled for presidential administration
and whether or not the narrative used science.
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 95
10. The content analysis was conducted by three coders. Ten documents were pre-
tested using an initial codebook. The documents were coded independently by the
coders who then met periodically after coding every 25–35 documents. At their
meetings, the coders discussed their results, redefined and narrowed rules, and
ultimately reconciled their disagreements. The reliability of the three coders was
evaluated by comparing them in three pairs on their coding of all questions. The
reliability ratings range from a low of 78 percent to a high of 93 percent, with an
average of agreeing 84 percent of the time (see Appendix B), thus reasonably estab-
lishing intercoder reliability.
Given that the narrative strategies were operationalized as nominal-level vari-
ables, a Chi-square test of significance was conducted for each hypothesis to in-
vestigate the statistical difference between the occurrence of narrative frame
(winning–losing) and that of political narrative strategy or if the strategies utilized
are attributed to chance alone. A continuity correction was applied with the occur-
rence of small cells (n Յ 5); a Fisher’s Exact Test was used to determine the statis-
tical significance (Ramsey & Schafer, 1997, pp. 547–51). The magnitude of the
Chi-square results was assessed with a Cramér’s V, the preferred Chi-square
measure of association (McClendon, 2004, p. 455). Odds ratios (ORs) were calcu-
lated as a cross-product ratio (Knoke, Bohrnstedt, & Mee, 2002, p. 161) and were
used to indicate the odds of a specific political strategy occurring with a winning
or losing narrative.
Research Results
Table 2 provides descriptive statistics of the one hundred five narratives coded.
Note that of the winning and losing narratives, 71 of the 105 documents (68 percent)
were coded as losing narratives, whereas only 34 (32 percent) were coded as
winning. There are at least two reasons for this. First, groups may well be more likely
to articulate and distribute a policy narrative when they are losing as their goal is to
change the status quo, and their narrative is a form of both political defense and
attack. Second, as discussed earlier, there were no clear policy monopolies in this
time period. Instead, both interest groups experienced back-and-forth short-term
wins and losses characteristic of wicked problems. Thus, both interest groups felt
under attack consistently from nonfriendly forces. This is evidenced by the fact that
both groups produced more losing policy narratives than winning across all three
policy issues regardless of presidential administration.
Hypotheses 1a and b: Identification of Winners and Losers
Table 3 indicates statistically significant associations between winning narrative
frames and the identification of a specific winner (c2
[d.f. = 1] = 13.049, p < 0.001) and
losing narrative frames and identification of a specific loser (c2
[d.f. = 1] = 23.134,
p < 0.001). In winning narrative frames, a specific winner was identified 82.4 percent
of the time (fo = 28; fe = 19.4), compared with that of losing narrative frames identi-
fying a winner 45.1 percent of the time (fo = 32; fe = 40.6). The odds ratio of a winning
96 Policy Studies Journal, 35:1
11. Table 2. Descriptive Statistics of Interest Group Narratives by Winning or Losing Frame, Policy Issue,
and Presidential Administration
Interest
Group
Total
Documents
Winning
Narratives
Losing
Narratives
Policy Issue Presidential
Administration
GYC 52 (100%) 14 (27%) 38 (73%) Bison Clinton
Winning 3 (30%) Winning 4 (31%)
Losing 7 (70%) Losing 9 (69%)
Total 10 (100%) Total 13 (100%)
Snowmobiles Bush
Winning 7 (22%) Winning 10 (26%)
Losing 25 (78%) Losing 29 (74%)
Total 32 (100%) Total 39 (100%)
Roadless
Winning 4 (40%)
Losing 6 (60%)
Total 10 (100%)
BRC 53 (100%) 20 (38%) 33 (62%) Bison Clinton
Winning 0 (0%) Winning 6 (26%)
Losing 4 (100%) Losing 17 (74%)
Total 4 (100%) Total 23 (100%)
Snowmobiles Bush
Winning 18 (47%) Winning 14 (47%)
Losing 20 (53%) Losing 16 (53%)
Total 38 (100%) Total 30 (100%)
Roadless
Winning 2 (18%)
Losing 6 (82%)
Total 8 (100%)
Total 105 (100%) 34 (32%) 71 (68%)
Source: GYC and BRC documents, 1997–2004.
GYC, Greater Yellowstone Coalition; BRC, Blue Ribbon Coalition.
Table 3. Chi-Square Results for Identification of Winners and Losers by Narrative Frame
Losing Narrative Winning Narrative Total
Identification of winner Yes 45.1%
(32)
82.4%
(28)
60
No 54.9%
(39)
17.6%
(6)
45
Total 100.0%
(71)
100.0%
(34)
105
c2
(d.f. = 1) = 13.049, p < 0.001; Cramér’s V = 0.353, p < 0.001; ORWW
= 5.69
Identification of loser Yes 95.8%
(68)
58.8%
(20)
88
No 4.2%
(3)
41.2%
(14)
17
Total 100.0%
(71)
100.0%
(34)
105
c2
(d.f. = 1) = 23.134, p < 0.001; Cramér’s V = 0.469, p < 0.001; ORLL
= 15.87
Source: Greater Yellowstone Coalition and Blue Ribbon Coalition documents, 1997–2004.
OR, odds ratio; ORWW
, odds ratio of a winning frame; ORLL
, odds ratio of a losing narrative frame.
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 97
12. frame identifying a specific winner is 5.69; thus, winning policy narratives are five
times more likely than losing narrative frames to identify a winner. Losing narrative
frames contained a specific loser 95.8 percent of the time (fo = 68; fe = 59.5), compared
with winning narrative frames identifying a loser 58.8 percent of the time (fo = 20;
fe = 28.5). The odds ratio of a losing narrative frame identifying a specific loser is
15.87; thus, losing narrative frames are fifteen times more likely than winning frames
to identify a loser. The magnitude of these relationships is strong, with Cramér’s
V = 0.353 (p < 0.001) and 0.469 (p < 0.001) for winning and losing policy frames,
respectively. We can accept hypotheses 1a and b.
The strategy of winning narratives is to maintain the status quo; the BRC often
cites local communities and small business owners as winners while the GYC cites
Yellowstone visitors. Interestingly, the BRC and the GYC see the maintenance of the
status quo in the hands of local vs. national constituencies, respectively. Yet their
strategy is keenly predictable here. Losing narratives identify losers in an attempt to
grow a coalition and change the status quo. The BRC invokes a wide coalition of
potential losers in trying to debunk what they view as environmental propaganda:
the public, visitors to YNP, snowmobile riders, and the snowmobile industry
(Eggers, 1999). Similarly, in arguing for snowmobile regulation, the GYC identifies
wildlife, park employees, public safety, American families, and the taxpayer as losers
in the status quo of YNP snowmobile use (Catton & Buffington, 2002). The political
strategy is the same despite divergent policy beliefs.
Hypothesis 2: Concentration or Diffusion of Benefits
Table 4 also reveals a statistically significant association between the occurrence
of concentration or diffusion of benefits in policy narrative frames
(c2
[d.f. = 1] = 6.959, p < 0.01), with an indication of a strong measure of association:
Cramér’s V = 0.338 (p < 0.01). Losing narratives diffuse benefits 18.2 percent of the
Table 4. Chi-Square Results for Benefits and Costs by Narrative Frame
Losing Narrative Winning Narrative Total
Benefits Concentrated benefits 81.8%
(27)
50.0%
(14)
41
Diffuse benefits 18.2%
(6)
50.0%
(14)
20
Total 100.0%
(33)
100.0%
(28)
61
c2
(d.f. = 1) = 6.959, p < 0.01; Cramér’s V = 0.338, p < 0.01; OR = 4.5
Costs Concentrated costs 16.4%
(11)
55.6%
(10)
21
Diffuse costs 83.6%
(56)
44.4%
(8)
64
Total 100.0%
(67)
100.0%
(18)
85
c2
(d.f. = 1) = 11.683, p < 0.001; Cramér’s V = 0.371, p < 0.001; OR = 6.36
Source: Greater Yellowstone Coalition and Blue Ribbon Coalition documents, 1997–2004.
OR, odds ratio.
98 Policy Studies Journal, 35:1
13. time (fo = 6; fe = 10.8), compared with winning narratives that do so 50 percent of the
time (fo = 14; fe = 9.2). Losing narratives concentrate benefits 81.8% of the time
(fo = 27; fe = 22.2), compared with winning narratives that do so 50 percent of the time
(fo = 14; fe = 18.8). Losing narratives are 4.5 times more likely to concentrate benefits,
whereas winning narratives are 4.5 times more likely to diffuse benefits (OR = 4.5).
We can accept hypothesis 2.
The association between (i) winning narratives and diffusing benefits and (ii)
losing narratives and concentrating benefits is a political strategy used by interest
groups to influence policy outcome. For example, the GYC applauded the success of
the Clinton era snowmobile reductions by citing the improved National Park Service
employees’ health as well as that of all visitors (Scott, 2004); thus, they diffused the
benefits of the ban to many people. Similarly, the BRC presented the diffuse distri-
bution of the benefits of snowmobile use to local economies, residents, and snow-
mobile riders (Collins, 1998). Examples of concentrating benefits when losing are
found as a political strategy in both the BRC and the GYC narratives. In a time when
snowmobiling was under attack in the courts, the BRC contended that the only
beneficiary from snowmobile regulation was the environmental group Fund for
Animals (Cook, 1997). Similarly, the GYC concentrated benefits by claiming that
President Bush was ignoring larger national interests and instead was “bowing to
intense lobbying by the snowmobile industry and the park’s border towns” (GYC,
2002). Concentrating or diffusing the benefits of a policy proposal is a political
narrative strategy employed to influence policy outcome.
Hypothesis 3: Concentration and Diffusion of Costs
Table 4 also indicates a statistically significant association between the concen-
tration and diffusion of costs of the narrative frame (c2
[d.f. = 1] = 11.683, p < 0.001).
The measure of association is strong, with Cramér’s V = 0.371, p < 0.001. Winning
narrative frames concentrate costs 55.6 percent of the time (fo = 10; fe = 4.4) compared
to 16.4 percent for groups with losing frames (fo = 11; fe = 16.6). As hypothesized,
losing narrative frames diffuse costs 83.6 percent of the time (fo = 56; fe = 50.4) com-
pared to 44.4 percent of the time for winning frames (fo = 8; fe = 13.6). Losing narra-
tives are six times more likely to concentrate costs, whereas winning narratives are
six times more likely to diffuse costs (OR = 6.36). We can accept hypothesis 3.
Losing narratives are thought to diffuse costs of the proposed policy as a way
to expand the issue, whereas winning narratives contain the issue by concentrating
the costs on a few. When losing, the BRC tended to diffuse costs by focusing on
how snowmobile riders and the snowmobile community would pay the costs in
time, enjoyment, and recreational access, which would negatively impact tourism
and gateway communities. Similarly, the GYC diffused costs over stressed wildlife,
human health, visitor enjoyment, deteriorating ecosystems, nonmotorized recre-
ationists, and public safety. Finally, when concentrating costs, winning narratives
construct narrow entities to endure costs, such as “commercial logging” (GYC,
2001a) or narrow special interest groups (Welch, 2000).
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 99
14. Hypothesis 4: Use of Condensation Symbols
There is a statistically significant association between the use of condensation
symbols and narrative frames (c2
[d.f. = 1] = 3.490, p < 0.10); this is asserted with the
acceptance of a higher risk of making a Type I error, with p < 0.10 (see Table 5). The
measure of association is weak, with Cramér’s V = 0.182, p < 0.10. As hypothesized,
losing narrative frames use condensation symbols more frequently than winning
narratives, that of 42.3 percent of the time (fo = 30; fe = 25.7) compared to 23.5 percent
of the time (fo = 8; fe = 12.3), respectively. Losing narratives are approximately
2.4 times more likely to use condensation symbols (ORLCS
= 2.39). We can accept
hypothesis 4.
The effect of condensation symbols is to heighten emotions and create a Hob-
son’s choice in policy preference. Interestingly, the BRC was more likely to use
characterization symbols (n = 9 for the BRC or 17 percent of the time; n = 4 for the
GYC or 7.7 percent of the time), whereas the GYC was much more likely to use issue
symbols (n = 19 for GYC or 36.5 percent of the time; n = 9 for the BRC or 17 percent
of the time). For example, while on the losing end of policy disputes, the BRC
characterized their opponents as “school yard bullies” with “hit lists” and “hate
mail” (Collins, 1998) and “out in left field” (Eggers, 1999), while the GYC refers to a
Yellowstone with snowmobiling as a “noisy speedway” (GYC, 2001b).
Hypothesis 5: Use of Surrogates
Table 5 reveals a statistically significant association between use of policy sur-
rogates and narrative frames (c2
[d.f. = 1] = 5.122, p < 0.05), with a Cramér’s V
measure of association of 0.221 (p < 0.05). Policy surrogates are used by losing nar-
ratives 32.4 percent of the time (fo = 23; fe = 18.3), whereas they are used by winning
Table 5. Chi-Square Results for Condensation Symbols and Policy Surrogates by Narrative Frame
Losing Narrative Winning Narrative Total
Condensation symbols Yes 42.3%
(30)
23.5%
(8)
38
No 57.7%
(41)
76.5%
(26)
67
Total 100.0%
(71)
100.0%
(34)
105
c2
(d.f. = 1) = 3.490, p < 0.10; Cramér’s V = 0.182, p < 0.10; ORLCS
= 2.39
Policy surrogate Yes 32.4%
(23)
11.8%
(4)
27
No 67.6%
(48)
88.2%
(30)
78
Total 100.0%
(71)
100.0%
(34)
105
c2
(d.f. = 1) = 5.122, p < 0.05; Cramér’s V = 0.221, p < 0.05; ORLPS
= 3.59
Source: Greater Yellowstone Coalition and Blue Ribbon Coalition documents, 1997–2004.
ORLCS
, odds ratio of losing narratives’ use of condensation symbols.
ORLPS
, odds ratio of losing narratives’ use of policy surrogates.
100 Policy Studies Journal, 35:1
15. narratives only 11.8 percent of the time (fo = 4; fe = 8.7). Losing narratives are more
than three times more likely to use a policy surrogate than a winning narrative
(ORLPS
= 3.59). We can accept hypothesis 5.
In political narratives, losing groups are more likely to strategically wrap the
issue in the larger contentious cultural context by using policy surrogates. This use
of a policy surrogate is again consistent with Baumgartner’s and Jones (1993) theory
of issue expansion when a group is losing and with the research of Nie (2003) on
environmental policy conflict. The BRC’s policy surrogates tend to focus on either
federalism or environmental elitism, arguing, “we can’t rely on the federal govern-
ment to represent the public’s interest” (Cook, 1997). Furthermore, the BRC argued
that policy was needed to “see our natural resources protected FOR the people
instead of FROM the people” (Eggers, 1999). The GYC almost exclusively used
surrogates when they were losing, only using a surrogate once when they were
winning on an issue. Their surrogates focused on corruption by special interests, as
exemplified in this statement from one of their articles: “National interest is being
sacrificed to the special interest of the snowmobile industry in of all places, Ameri-
ca’s first national park” (Sieck, 2002).
Hypothesis 6: Scientific Certainty or Uncertainty
As revealed in Table 6, there is no statistical association between winning–losing
narrative frames and how science is used, either to show certainty or uncertainty. We
reject hypothesis 6. Approximately 50 percent of both winning and losing narratives
use science in their narratives; of those, both narrative frames used scientific cer-
tainty at high rates, 89.5 and 85.7 percent, respectively.
When both interest groups used science regardless of whether they were
winning or losing, they tended to use it in terms of scientific certainty to back up
their policy preference. Nie (2003, p. 323) concludes that competing groups in envi-
ronmental policy controversies use science to “forward their preferred policy objec-
tives.” The focus of science used in the two groups’ narratives is different; the GYC
uses a conservation biology approach whereas the BRC uses a more technological
approach (McBeth et al., 2005, p. 422). In general, the conflict over science between
competing interest groups is usually a battle over the stable policy core beliefs
embedded in the science rather than part of a dynamic narrative political strategy.
Table 6. Chi-Square Results for Science by Narrative Frame
Losing Narrative Winning Narrative Total
Science Certainty 85.7%
(30)
89.5%
(17)
47
Uncertainty 14.3%
(5)
10.5%
(2)
7
Total 100.0%
(35)
100.0%
(19)
54
c2
(d.f. = 1) = 0.154, ns; Cramér’s V = 0.053, ns
Source: Greater Yellowstone Coalition and Blue Ribbon Coalition documents, 1997–2004.
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 101
16. Controlling for Presidential Administration and Use of Science
The ACF theory asserts that changes in governing coalitions affect policy change
in that coalitional resources expand or contract, depending on whether the admin-
istration aligns itself with a group’s core beliefs or not. For example, the Bush
administration’s shared policy beliefs added resources (power) to the BRC. Not
surprisingly, controlling for presidential administration resulted in additive relation-
ships among all six statistically significant political strategies. The relationship
between political strategies and narrative frame persisted in direction and varied
only somewhat in each control table. Thus, in understanding policy change, changes
in governing coalitions and political strategies are critical.
Additionally, the ACF theory differentiates between policy learning within a
belief system and across belief systems (Jenkins-Smith & Sabatier, 1993, p. 48). In the
former, science is used to bolster a group’s core beliefs; in the latter, scientific
evidence and coalitional technical expertise can alter core beliefs over time. Given the
wicked-problem nature of the GYA, when groups use science, it is used within a
belief system to reify a group’s policy beliefs. In controlling for those narratives that
used science, five of the six political strategies remained virtually unchanged; thus,
use of science is not related to winning or losing strategies. However, controlling for
use of science led to the evaporation of any relationship between condensation
symbols and narrative frame, thus weakening the interpretation of the use of con-
densation symbols as a narrative political strategy.
Discussion
In this study, we seek to present a new methodological approach to the under-
standing of the policy change process by integrating NPA and policy change theory
while upholding the standards of traditional social science research. Our first
research question—whether or not NPA can be used appropriately within the
context of traditional policy change theory—is answered affirmatively. In this study,
issue expansion and containment in the turbulent GYA policy arena is empirically
tested through coding interest group narratives. We systematically test whether or
not winning narrative frames attempt to contain the issue with predictable narrative
strategies (identification of winners, diffusion of benefits and concentration of costs
of policy success, and use of scientific certainty) and whether or not losing narrative
frames attempt to expand the issue with predictable narrative strategies (identifica-
tion of losers, concentration of benefits and diffusion of costs of policy failure, use of
condensation symbols and policy surrogates, and use of scientific uncertainty).
While advocacy coalitions embed stable policy core beliefs in narratives, they also
use those narratives to further dynamic political strategies.
Our second research question—whether or not operationalized narrative strat-
egies reflect how groups attempt to contain or expand the policy issue—is also
answered affirmatively. When using the ACF controls, five of the seven hypotheses
are supported. The data provide evidence for the notion that interest group narra-
tives are indicators of a group’s political strategies and tactics and are tied to whether
102 Policy Studies Journal, 35:1
17. a group is winning (and trying to contain an issue) or losing (and trying to expand
an issue). Importantly, these strategies are not tied to core beliefs, nor are they
ideologically based or reflective of writing ability or style. These strategies cut across
ideological lines, are used by both sides in the policy dispute, and are connected to
how a group perceives its position in the policy battle. Thus, narratives as a source of
study are strategic, predictable, and testable and are an appropriate unit of analysis
for scholars interested in studying policy change.
Finally, our third research question explores the additions to the literature. This
method of analysis integrates NPA with policy change theory and adds to the
existing literature. The contribution here addresses Brown and Stewart’s (1993,
p. 101) criticism of the ACF. We argue that narratives as political strategies are a
valuable source of study for researchers. The activity in the GYA occurred in periods
of alternating victories and losses. Although several external subsystem events (e.g.,
court opinions, well-publicized media events, changes in presidential administra-
tions) could have swung the policy battles toward one group or another by produc-
ing shifts in coalitional resources, the two interest groups consistently perceived
themselves as losing 67.6 percent of the time. Losing narratives, as we have seen, are
more confrontational and seek to expand conflict to additional parties. In wicked
policy problems, interest group narratives only reinforce and exacerbate policy
intractability. Short-term wins are quickly replaced by the perception of losing and
the need to retaliate. The effect is that the narratives almost continually expand the
scope of the conflict, thus drawing in more groups to the policy dispute. As seen in
the eight-year course of this study, the result is long periods of protracted conflict.
The GYA policymaking meets the conditions of what Sabatier and Jenkins-Smith
(1999, p. 132) call the “devil shift” or the situation where opposing coalitions
“remember losses more than victories” and inflate the evilness and power of oppos-
ing groups. In addition, this research involved two purposive interest groups, and
these groups, as hypothesized by Sabatier and Jenkins-Smith (1999, p. 134), maintain
a tight script and thus resist alterations to their scripts that would move dialogues
toward policy learning.
In policy environments where there is both a clear policy monopoly and a clear
out-of-power coalition, we would assume that the minimal coalition of a policy
monopoly would rarely perceive that they are losing and that their narratives would
consistently reflect the theory of issue containment. Research on narratives in stable
policy environments might provide initial signs for policy researchers that the policy
equilibrium had been punctuated.
Conclusion
This work has used a case study of environmental policy making in the GYA to
examine the interest group use of narrative political strategies in defending existing
policies or advocating new policies. Grounded in the theories of Sabatier, Jenkins-
Smith, Baumgartner, Jones, Schattschneider, Stone, and others, the methodological
model is generalizable to any policy subsystem in such policy areas as economic
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 103
18. development, energy, crime, and foreign policy. The intersection of policy change
theory and NPA prompts theory building.
In determining the extent to which our work contributes to this theory building,
we turn to Sabatier (1999, pp. 266–70), who argues that there are seven guidelines for
theory development. First, our analysis is empirical with testable hypotheses.
Second, our method allows for testing of our hypotheses in a variety of policy
settings. Third, we found a causal relationship between perception of winning and
losing and policy narrative strategies and have accounted for some ACF controls.
Fourth, our study suggests that individuals are political, seek to win, and intention-
ally and strategically use narratives to either contain or diffuse a policy issue. Fifth,
we have shown a consistency among five of our seven hypotheses. Sixth, our aim is
to build a long-term research agenda and invite others to build upon our method-
ology. Finally, our research uses principles from the ACF, punctuated equilibrium,
and three streams of policy change and enhances these works with NPA. We con-
clude that narrative political strategies are a vital source for analyzing policy change
in a complex political environment.
Mark K. McBeth is a professor of political science at Idaho State University.
Elizabeth A. Shanahan is an assistant professor of political science at Montana State
University.
Ruth J. Arnell is a doctoral student in political science at Idaho State University.
Paul L. Hathaway is a doctoral student in political science at Idaho State University.
Notes
A different version of this paper was presented at the 2005 Western Political Science Conference in
Albuquerque, New Mexico. The authors wish to thank Teri Peterson for her statistical consultations.
1. The BRC is part of a larger advocacy coalition (the wise use coalition) that includes ranchers, local
business elites, snowmobile, ATV, and motorcycle manufacturers, elected officials, and scientists.
2. The GYC is part of a larger advocacy coalition (the environmental coalition) that includes national
environmental groups, local business elites, elected officials, and scientists.
3. The identification of benefits as diffuse or concentrated resulted in mutually exclusive coded responses;
in other words, when benefits were coded, they were either concentrated or diffused. Hence, they are
included in the same hypothesis. The same is true for concentrated—diffuse costs (hypothesis 3) and
uncertainty—certainty in use of science (hypothesis 6).
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Appendix A: Abbreviated Code Book
1. Does the narrative identify a specific winner (entity that benefits) of a policy
decision or potential decision? For example, “anti-recreationists will rejoice over
this policy decision” or “the snowmobile industry is clearly rooting for this
lawsuit to be thrown out of court.”
A-Yes (go to question #2) B-No (skip to question #3)
2. What best describes how the narrative constructs the benefits of the policy
decision?
A-The narrative is constructed as providing concentrated benefits (a few
gain). For example, “the wealthy environmentalists will have YNP as
their personal playground” or “this decision benefits the snowmobile
industry.”
Paragraph number(s) and group:
B-The narrative is constructed as providing diffused benefits (many gain).
For example, “the American people will benefit from the closing of YNP to
snowmobiles” or “snowmobile enthusiasts from throughout the country
applauded this decision.”
Paragraph number(s) and group:
3. Does the narrative identify a specific loser (entity that pays the costs) of a policy
decision? For example, “the American people are the losers when industry
controls government” or “local businesses are hurt by these actions of the NPS.”
106 Policy Studies Journal, 35:1
21. A-Yes (go to question #4) B-No (skip to question #5)
4. What best describes how the narrative constructs the costs of the policy decision?
A-The narrative is constructed as providing concentrated costs (a few pay).
For example, “This regulation will harm only a small number of greedy
business owners who fail to adapt to changing times” or “The throwing out
of this policy will only harm the sensibilities of a few extremists.”
Paragraph number(s) and group:
B-The narrative is constructed as providing diffused costs (the many pay).
For example, “this plan protects bison while projecting costs over many
differing groups” or “this plan protects snowmobiling with only minor
adjustments required of business owners who must now be licensed guides
and use cleaner machines.”
Paragraph number(s) and group:
5. Does the narrative contain at least one condensation symbol? The definition of a
condensation symbol is a word or phrase that “shrinks and reduces complicated
concepts into simple, manageable, or memorable forms.”
A-Yes, list and identify paragraph(s) B-No
6. Does this narrative use a policy surrogate? For example, policy surrogate =
“greedy snowmobile corporations exploit Yellowstone for their own purposes
while the pollution gets worse and worse” or “this issue is all about people in
Washington, DC telling people in our small towns about how to live their lives.”
A-Yes, list and identify paragraph(s) B-No
7. Does the narrative use science to define a problem, counter a problem definition,
or justify a policy approach?
A-Yes. (go to question #8) B-No (go to question #9)
8. Is the mention of science used in the context of:
A-Disputing science B-Establishing scientific certainty
9. What is the stance of the narrative towards the policy being discussed?
A. Winning (supports the policy environment and actions discussed in the
narrative)
B. Losing (the group is under attack even if they are partially winning)
McBeth et al: Narrative Policy Analysis and Policy Change Theory Intersection 107
22. Appendix B: Intercoder Reliability
Question Agreement (%) Disagreement (%) Total Codings
1 243 (78%) 72 (22%) 315
2 23 (93%) 9 (7%) 132
3 275 (87%) 40 (13%) 315
4 210 (89%) 25 (11%) 235
5 268 (85%) 47 (85%) 315
6 259 (82%) 56 (18%) 315
7 156 (84%) 30 (16%) 186
8 156 (96%) 6 (4%) 162
9 251 (80%) 64 (20%) 315
TOTAL 1,941 (85%) 349 (15%) 2,290 (100%)
Note. Questions 1, 3, 5, 6, and 9 are paired codings comparing the three coders to each other. All coders
coded this screening questions. These questions all sum to 315 (105 documents ¥ 3 coders). Questions 2
and 4 are also paired codings but have smaller numbers because of screenings. The first 75 documents for
question #7 were coded by only two coders. Because there were only 2 coders there was only 1 paired
coding instead of 3 on this question. Thus the total number of codings for question 7 equals only 186.
108 Policy Studies Journal, 35:1
