A Comparative View of Advocacy Coalitions: Exploring Shale Development Politics in the United States, Argentina, and China

Abstract

Political mobilization of policy actors into advocacy coalitions is a defining feature of policy subsystems. Nonetheless, knowledge about the particularities of advocacy coalitions across different political systems remains limited. This paper offers insights for comparative analysis of advocacy coalitions by exploring the issue of shale development in the United States, Argentina, and China using media content analysis. Methodologically, it advances the study of coalitions by introducing a standardized approach for measuring coalition attributes across countries. Empirically, it explores how coalitions vary in their composition across countries with different political opportunity structures.

Keywords:

• advocacy coalitions
• shale oil and gas
• fracking
• comparative policy process
• environmental policy

Supplemental data

Supplemental data for this article can be accessed at https://doi.org/10.1080/13876988.2017.1405551.

Notes

1. The ACF’s definition of coalitions includes both shared beliefs and coordination patterns. We measure coalitions based on shared policy positions and instances of agreement and disagreement between policy actors. These measures of coalitions are typical in the ACF literature (Weible and Sabatier 2009; Leifeld 2013).

2. There are other possible ways to describe the structure of coalitions including identifying brokers or influential actors. The structural features of coalitions used in this paper (positions, (dis)agreements, affiliations, insularity) are chosen because we consider them more fundamental to the definition of a coalition.

3. These capacities are reflected in measures of democratization. According to the Polity IV Index (2016), the US ranks in the highest level of democratization, Argentina ranks as moderately democratic, and China ranks as autocratic.

4. Coverage on shale oil and gas began in 2008 in The Denver Post, 2011 in La Mañana de Neuquén, and 2013 in Chongqing Daily.

5. The full codebook for this study is available from the authors. Editorials, opinion pieces, and letters to the editor were not included in the dataset.

6. We did not include references to generic actors such as “voters” and the “public”. If an actor has two titles or roles, we coded this person twice if the person expressed positions in both roles.

7. Within the dataset, there are 178 unique organizations from the Denver Post articles, 280 unique organizations from La Mañana de Neuquén, and 68 unique organizations from Chongqing Daily.

8. We aggregated positions in newspaper articles based on organizational ID. In other words, if two individuals whose opinions are showcased in different articles belong to the same organization, then their answers were aggregated to perform the network analysis. We found no instance in the 1,064 observations where the positions of individuals in the same organization were in direct opposition. We did, however, find instances in which anti and pro positions coexisted with either “neutral/mixed” or “not specified” values. In these cases, we took the majority of responses and assigned that as the organizational value. In cases in which there was a tie between either pro or anti and any of the other two categories, we assigned the organization either the pro or anti value. For instance, if an organization is depicted with an anti position in one article and a mixed/neutral position in another, we assign that organization an anti position in the network analysis.

9. When an actor was mentioned by an article without indication of agreement or disagreement with other actors, it will show up in the network as an isolate. As the newspapers mention many organizations without indicating their relationship with other organizations, this leads to a large number of isolates in the network.

10. Cross-tabulations between just Argentina and China were also run separately and Chi-square tests within organizational affiliation types confirm that significant differences between the two countries exist (sig. < 0.05) in the engagement of the following organization types: environmental/citizen groups (Chi-square = 3.59), industry (Chi-square = 7.12) and political party involvement (Chi-square = 3.48).

11. Homophily is the tendency of nodes with similar characteristics in a network to form ties with each other. In a network in which multiple groups exist that share a given attribute, a tendency toward homophily would mean that the groups are more insular than not.

Additional information

Funding

Funding support was provided by the U.S. National Science Foundation’s Partnerships in International Research and Education (grant number 1243535).

Notes on contributors

Tanya Heikkila

Tanya Heikkila is a professor in the School of Public Affairs at the University of Colorado Denver and co-directs the Workshop on Policy Process Research. Her research explores natural resources conflict and collaboration.

Ramiro Berardo

Ramiro Berardo is an assistant professor in the School of Environment and Natural Resources at The Ohio State University. His research focuses on collective action problems in the use and management of common-pool resources.

Christopher M. Weible

Christopher M. Weible is a professor in the School of Public Affairs at the University of Colorado Denver. He co-directs the Workshop on Policy Process Research and studies conflict and concord in policy processes.

Hongtao Yi

Hongtao Yi is an assistant professor in the John Glenn College of Public Affairs at The Ohio State University. His research investigates policy networks and energy and environmental policy.