A Systems View of Decision‐Making for Risky Technologies: From Global to Local and Local to Global
Bibliographic record
Abstract
Abstract The recent disaster at Japan's Fukushima nuclear power generation facility has caused concern on a global scale over the safety of nuclear power. In response to heightened risk perceptions caused by these crises, many stakeholders may find processes for voicing their concerns to be inadequate. For many years, an effective model for decision‐making which includes public input has been needed, a process that meets the needs of diverse stakeholders in a democratic setting. Many studies conclude that stakeholder interactions occur within a complex system, but do not articulate details of this system. This study combined case study with grounded theory methodology and utilized situational analysis. Data were mainly comprised of 30 one‐on‐one interviews with stakeholders involved in the decision‐making processes for the re‐licensing of two nuclear power generation facilities in Ontario, Canada. The purpose of this paper is to present findings from this qualitative study which illuminate the complex interactions between global, national, and local systems, such as the effect of nuclear incidents on global and local risk perceptions. The paper concludes with several recommendations for organizations concerned with protecting public safety.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".