L’appropriation des normes de participation dans les institutions internationales
Bibliographic record
Abstract
Le processus d’internalisation des normes au sein des institutions n’est pas homogène, variant selon divers facteurs. L’article se penche sur des acteurs, liés directement ou indirectement à la construction de grands barrages, peu sensibles aux enjeux sociaux du développement durable. Comment expliquer les différences entre ces institutions dans la prise en compte des critères sociaux ? L’hypothèse est que l’identité d’une organisation et sa capacité « disciplinaire » ou « idéologique » à tenir compte des facteurs sociaux déterminent la qualité de l’évaluation et de la gestion des impacts sociaux des grands barrages, rejoignant l’argument de Young voulant que la structure d’une institution internationale joue un rôle capital dans sa capacité à mettre en oeuvre et à promouvoir des normes.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".