Search

This paper expands the Narrative Policy Framework (NPF) by employing an exploratory case study approach to examine the construction of narratives temporally. A large‐N Twitter dataset concerning the Bears Ears and Grand Staircase‐Escalante monuments controversy is utilized to examine the question: how does the use of narrative strategies change over time? Through the application of change‐point analysis, we determine time points of significant shifts towards use of the devil‐angel shift, scope of the conflict, and causal mechanism strategies. Overall, we find that organizations do not vary their use of narrative strategies over the course of a policy conflict but instead demonstrate discrete changes in response to certain policy events. Based on our findings, we conclude with suggestions for refining and expanding NPF hypotheses. Specifically, we recommend a more contextual analysis of shifts in narrative strategy use in response to specific events over time. [ABSTRACT FROM AUTHOR]

Networks are an important part of the environmental policy process as they influence the ability of actors to synthesize information and learn to manage complex risks. According to the Advocacy Coalition Framework, the dynamics of policy network formation lead to structures exhibiting belief‐oriented segregation—that is, a high correspondence between shared beliefs and policy‐relevant interactions. These structures may be produced through at least two pathways: belief homophily, where actors actively seek out connections with others sharing their belief system, and policy‐oriented learning, where connected actors become more similar in their beliefs. The cross‐sectional design of much policy research does not allow an examination of these potentially complementary forces that shape belief systems and networks. These dynamics are studied using data on policy beliefs and networking in the U.S. environmental risk policy subsystem across two time periods, 1985 and 2000 (N = 223). Results indicate strong homophily effects, but relatively weak learning effects in the evolution of this policy network. This study helps pave the way for additional research on the dynamics shaping policy networks and beliefs, and helps to clarify the differences between individual versus organizational contributions to policy network evolution. [ABSTRACT FROM AUTHOR]