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Public Participation in Decision-Making on Energy Policy: The Case of the “National Discussion” After the Fukushima Accident

  • Naoyuki MikamiEmail author
Chapter

Abstract

The summer of 2012 was a significant period for Japan’s nuclear and energy policy in that, in response to the Fukushima nuclear accident, the government decided to undertake, what it termed, a “National Discussion” on energy policy. This was the first time that Deliberative Polling had been introduced in Japan on a policy level. This DP included 285 randomly selected participants from across Japan, asking them to deliberate on three nuclear energy policy options with the assistance of a panel of eight specially selected experts. The participants were asked to fill out a questionnaire at three points during the process, and their support for the three options (zero, 15, and 20–25 % nuclear dependency scenarios) were recorded and later analyzed. What was particularly interesting was the participants’ desire not merely for information but also to challenge the panelists’ individual viewpoints and to question the very framework of the discussion. Significant changes in the level of support for the three scenarios were observed, with approximately 50 % of the participants eventually choosing a shift away from nuclear dependency. An examination of the government’s response to the National Discussion , including the DP, demonstrated that the results had a significant impact on nuclear policy , with the government explicitly stating that nuclear dependency should be phased out by the 2030s. A subsequent change in government led to the abandonment of this policy decision, but did not totally undermine the value of Japan’s first attempt at combining a public participatory process with actual national policymaking in the field of science and technology.

Keywords

Nuclear Energy Policy Option Nuclear Power Station Plenary Session Public Hearing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The work of this chapter was supported by JSPS KAKENHI Grant Number 24501085, 26340111.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Hokkaido UniversityHokkaidoJapan

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