The Efficacy Paradox Revisited: “Closing Up” Commitments in Nuclear Waste Governance
Bibliographic record
Abstract
It is well established in science and technology studies that participation and expert analysis should not be seen as contradictory. Key analytical questions include how both public and expert knowledge contribute to “closing down” and “opening up” appraisals and commitments, and how important these dynamics are in assessing the process and the conditions of democratizing technology. This article examines how the participatory turn has affected nuclear waste governance options in France and Canada. Through cross-case analysis, it describes how at each constitutive step of management programs, public and expert knowledge has followed a variety of pathways in (in)forming commitments, resulting in asymmetrical trade-offs. The term “closing up commitment” is introduced to refer to the way both national governments finally opted for closing the technological options at hand while introducing new conditions that might challenge future actions. We argue that paying attention to this mutation in nuclear governance allows for a more detailed analysis of power distributions in science and technology governance than a critical approach that rejects any closure because it can be (and often is) the result of an instrumental approach undertaken by the incumbent actors.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | Science and technology studies Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.035 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.054 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.008 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".