Setting the Terms of Reference in Environmental Assessments: Canadian Nuclear Fuel Waste Management
Bibliographic record
Abstract
Although ostensibly a technical issue, the environmental assessment of the proposed concept to dispose of nuclear fuel waste (NFW) deep in igneous rock of the Canadian Shield, caused considerable debate regarding the social, ethical, and political dimensions of the issue. Among other things, those embroiled in the debate, including government, industry and non-governmental organizations disagreed about how to define the problem of NFW management. However, since the current procedure for setting the terms of reference involves only limited public consultation, the full range of alternative definitions was not considered. We deconstruct the negotiations that led to the setting of the terms of reference. Throughout the environmental assessment hearing process, and subsequent to its completion in 1998, the terms of reference were a source of controversy and conflict amongst stakeholders. At the end of the process, the final Environmental Assessment Panel report transcended the scope of the terms of reference and provided both technical and social definitions of the safety and acceptability of the NFW disposal concept. The ramifications of this report will reverberate in all future assessments of complex technological and major resource management projects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.042 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.040 | 0.026 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".