The Framework which Aims at Improving Compatibility of the High-level Radioactive Waste Disposal Technology with Social Values and the Role of Risk Comnunication
Bibliographic record
Abstract
Public perception on safety is the key factor for achieving public acceptance of the high-level radioactive waste (HLW) disposal program. Past studies on public perception and HLW management have confirmed that the pubic do not share the confidence of the experts in safety and feasibility of HLW disposal. The importance of a more comprehensive approach to enhance acceptability of the HLW disposal technology is recognized.This paper proposes a framework for inducing the implementers and regulators to improve compatibility of the HLW disposal technology with social values. In this framework, the implementers and regulators identify technical components which are subject to substantial influence from public concerns. Then, they manage these components through the following actions: (1) establishing policies, targets and plans to make these components compatible with social values, (2) developing and utilizing the components based on the above policies, targets and plans, (3) cheking the extent of compatibility through intensive risk communication and (4) improving the process of developing and utilizing the components. This framework requires information disclosure and evaluation by an independent body which are expected to intensify the incentive to take the above actions. Canada's environmental assessment review process regarding the HLW disposal concept suggests that this framework could work effectively.
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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 | 0.022 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".