All Politics is Local: Judicial and Electoral Institutions' Role in Japan's Nuclear Restarts
Bibliographic record
Abstract
Since the 3/11 compounded disasters, Japanese energy policy, especially its nuclear policy, has been paralyzed. After the Fukushima disasters, public opinion turned against nuclear energy while the central government continued to push for restarts of the many offline reactors. Based on nearly thirty interviews with relevant actors and primary and secondary materials, we use qualitative comparative analysis (QCA) and Eve case studies to illuminate the impact of conditions influencing reactor restarts in Japan after 3/11. We investigate which local actors hold the greatest power to veto nuclear power policy, and why and when they choose to use it. Key decisions in nuclear power policy involve approval from multiple institutions with varying legal jurisdiction, making vetoes the result of multiple actors and conditions. Certain legal and political factors, such as court, regulator, and gubernatorial opposition (or support), matter more than technical factors (such as the age of the reactor or its size) and other political factors (such as town council or prefectural assembly opposition or support). Local politics can stymie a national government’s nuclear policy goals through combinations of specific physical conditions and vetoes from relevant actors, rather than through the actions of local opposition or single “heroic” governors. Our findings challenge the assumption that utilities unilaterally accept a governor’s vetoes, but reinforce the notion that specific judicial and electoral veto players are blocking an otherwise expected return to a pro-nuclear status quo.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".