How do policymakers and think tank stakeholders prioritize the risks of the nuclear fuel cycle? A semantic network analysis

Nan Li, Dominique Brossard, Ashley A. Anderson, Dietram A. Scheufele, Kathleen M. Rose

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

In recent years, the importance of stakeholder involvement and of integrating diverse perspectives into risk management has gained increasing recognition. However, it remains a challenging task to identify all potentially relevant stakeholders and to reliably describe their deeply held beliefs regarding the risks associated with complex industrial systems. For example, the development of advanced nuclear fuel cycles presents such a case. Based on a review of policy-making literatures and a content analysis of congressional records, we identify federal agencies and nonprofit policy institutes (also known as ‘think tanks’) as key stakeholders that are representative of those actively involved in making high-level decisions on the US nuclear energy policy. Using a semantic network analysis approach, we visually delineate the thematic areas of each party’s perceptions concerning fuel cycle risks. The results show that although governmental and think tank stakeholders share common concerns in areas such as nuclear waste management, the economics of nuclear facilities, and proliferation, they tend to focus on distinct aspects of each area. Moreover, while governmental stakeholders are primarily concerned with the environmental and local impacts of nuclear fuel cycles, think tank stakeholders focus more on the relative advantages and disadvantages of nuclear energy compared to other alternative energy options. Implications for risk management and risk communication are discussed.

Original languageEnglish
Pages (from-to)599-621
Number of pages23
JournalJournal of Risk Research
Volume21
Issue number5
DOIs
StatePublished - May 4 2018

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Keywords

  • mental model
  • nuclear power
  • risk communication
  • risk management
  • semantic network analysis

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