Contribution de l’Accord économique et commercial entre le Canada et l’Union européenne (AECG) au débat sur la contestation de l’arbitrage investisseur État
Bibliographic record
Abstract
Malgre les contestations de plus en plus vives de l’arbitrage investisseur Etat dans le cadre de relations economiques entre des Etats dits developpes, les parties a l’AECG ont choisi de conserver ce mode prive de reglement des differends et cela en a intrigue et decu plus d’un observateur. Pourtant, l’auteur de cet article opine que le rejet en bloc de ce mecanisme releve davantage d’opinions essentiellement politiques compte tenu des avancees substantielles operees par le chapitre de l’AECG portant sur les investissements etrangers. Axe sur la transparence et la confiance reciproque, le mecanisme d’arbitrage investisseur Etat tel que concu dans l’AECG tente avec un certain succes le pari difficile de l’equilibre entre preservation des interets nationaux et securisation des investissements etrangers. Mieux, l’auteur considere que les innovations introduites par ce mecanisme tant sur le plan procedural que sur le plan du droit substantiel devraient servir de cadre de reference pour les negociations futures notamment celles du Partenariat transatlantique de commerce et d’investissement en cours entre l’Union europeenne et les Etats-Unis (TTIP).
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| 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".