Allocation initiale et marché des permis négociables d’émission de gaz à effet de serre : quelle équité pour favoriser l’acceptabilité ?
Bibliographic record
Abstract
Les négociations internationales sur le changement climatique se sont organisées autour de l’allocation de permis négociables d’émissions de gaz à effet de serre. Ce travail se situe à l’horizon 2030 en supposant que tous les pays seront à cette date entrés dans un tel système de régulation. Il simule les enjeux quantitatifs qui pourraient être liés à différents critères d’allocation initiale des permis en distinguant des systèmes dits « purs » qui reposent sur un seul critère parmi un panel (population, PIB, selon la responsabilité, grandfathering, coûts d’abattement) des systèmes « hybrides » qui en combinent plusieurs selon des règles explicites issues des débats et de la littérature. Ces simulations mettent en évidence l’importance quantitative des enjeux liés à ces choix en termes de justice et essaie de discuter les conséquences qui peuvent être attendues pour des pays qui restent libres d’accepter ou non que ces critères soient utilisés dans les négociations.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".