La captation des ressources en eau douce : la notion de dette à la lumière des marchés d’eau internationaux
Bibliographic record
Abstract
Quelles sont les conséquences de la captation des ressources en eau douce en droit international ? Des dettes, sont-elles créées ? Les eaux captées, peuvent-elles être mises sur un marché ? Pour répondre à ces questions, le présent article analyse d’abord quelques notions de base, à savoir celles de ressource en eau douce, de créancier, de débiteur, d’offrant et de demandeur. Deux situations principales doivent être distinguées. Si la captation s’effectue à l’intérieur d’un bassin hydrographique international ou d’un aquifère transfrontière, l’idée d’un marché de l’eau est à rejeter. En revanche, lorsqu’il y a eu une captation conforme au droit et un transfert consécutif des eaux à l’extérieur de la zone hydrographique, à l’aide d’aqueducs ou de récipients artificiels ou biologiques (eaux virtuelles), l’idée de marché est déjà un fait en droit international.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".