Belief-oriented segregation in policy networks

Procedia - Social and Behavioral Sciences

Volumn 22, Issue , 2011, Pages 14-25

  Henry, Adam Douglas ^a  

^a WEST VIRGINIA UNIVERSITY   (United States)

Author keywords

Advocacy Coalition Framework; Agent based simulation; Belief change; Network segregation; Policy networks; Social learning

Indexed keywords

EID: 80053612335     PISSN: 18770428     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/j.sbspro.2011.07.052     Document Type: Conference Paper

References (25)

1. Axelrod, R. (1997). The complexity of cooperation: Agent-based models of competition and collaboration. Princeton University Press.
2. Baldassarri, D., & Gelman, A. (2008). Partisans without constraint: Political polarization and trends in American public opinion. American Journal of Sociology, 114(2), 408-446.
3. Burt, R. S. (2004). Structural holes and good ideas. American Journal of Sociology, 110(2), 349-399.
4. Butts, C. T. (2006). sna: Tools for social network analysis. Retrieved from http://erzuli.ss.uci.edu/R.stuff.
5. Cash, D. W., Clark, W. C., Alcock, F., Dickson, N. M., Eckley, N., Guston, D. H., Jäger, J., et al. (2003). Knowledge systems for sustainable development. Proceedings of the National Academy of Sciences, 100(14), 8086-8091.
6. Dietz, T., & Henry, A. D. (2008). Context and the commons. Proceedings of the National Academy of Sciences, 105(36), 13189-13190.
7. Girvan, M., & Newman, M. E. J. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 99(12), 7821-7826.
8. Henry, A. D. (2007). Simulating the evolution of policy-relevant beliefs: Can rational learning lead to advocacy coalitions? The challenge of selfgovernance in complex, globalizing economies, IFE Working Paper Series 47 (pp. 135-160). Freiburg, Germany: Institute of Forestry Economics, University of Freiburg.
9. Henry, A. D. (2009). The challenge of learning for sustainability: A prolegomenon to theory. Human Ecology Review, 16(2), 131-140.
10. Henry, A. D., Lubell, M., & McCoy, M. (2010). Belief systems and social capital as drivers of policy network structure: The case of California regional planning. Journal of Public Administration Research and Theory, in press. doi:10.1093/jopart/muq042.
11. Henry, A. D., Pralat, P., & C.-Q. Zhang. (2011). Emergence of segregation in evolving social networks. Proceedings of the National Academy of Sciences, 108(21), 8605-8610.
12. Hong, L., & Page, S. E. (2004). Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proceedings of the National Academy of Sciences of the United States of America, 101(46), 16385-16389.
13. Innes, J. M. (1978). Selective exposure as a function of dogmatism and incentive. The Journal of Social Psychology, 106(2), 261-265.
14. Johnson, P. E., & Huckfeldt, R. (2005). Agent-based explanations for the survival of disagreement in social networks. The Social Logic of Politics (pp. 251-268). Philadelphia: Temple University Press.
15. Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37(11), 2098-2109.
16. McNie, E. C. (2007). Reconciling the supply of scientific information with user demands: An analysis of the problem and review of the literature. Environmental Science & Policy, 10(1), 17-38.
17. Munro, G. D., & Ditto, P. H. (1997). Biased assimilation, attitude polarization, and affect in reactions to stereotype-relevant scientific information. Personality and Social Psychology Bulletin, 23(6), 636-653.
18. Munro, G. D., Ditto, P. H., Lockhart, L. K., Fagerlin, A., Gready, M., & Peterson, E. (2002). Biased assimilation of sociopolitical arguments: Evaluating the 1996 U.S. presidential debate. Basic and Applied Social Psychology, 24(1), 15.
19. Ohtsuki, H., Hauert, C., Lieberman, E., & Nowak, M. A. (2006). A simple rule for the evolution of cooperation on graphs and social networks. Nature, 441(7092), 502-505.
20. R Development Core Team. (2006). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from http://www.r-project.org.
21. Sabatier, P. A., & Jenkins-Smith, H. C. (1999). The advocacy coalition framework: An assessment. Theories of the policy process (1st ed., pp. 117-166). Westview Press.
22. Sabatier, P. A., & Jenkins-Smith, H. C. (Eds.). (1993). Policy change and learning: An advocacy coalition approach. Westview Press.
23. Sabatier, P., Hunter, S., & McLaughlin, S. (1987). The devil shift: Perceptions and misperceptions of opponents. The Western Political Quarterly, 40(3), 449-476.
24. Schneider, M., Scholz, J., Lubell, M., Mindruta, D., & Edwardsen, M. (2003). Building consensual institutions: Networks and the national estuary program. American Journal of Political Science, 47(1), 143-158.
25. Weible, C. M., & Sabatier, P. A. (2005). Comparing policy networks: Marine protected areas in California. Policy Studies Journal, 33(2), 181-201.