L'élaboration et le fonctionnement des mécanismes d'arbitrage au sein de I'ALE et de FALENA, du GATT et de l'OMC
Bibliographic record
Abstract
The increasing importance of international trade explains in great part the role that dispute resolution plays in trade agreement. Diversification, government's intervention in the economy, readiness of interest groups to defend their cause, all these elements make trade negotiations a much more difficult task today thon it used to be fifty years ago. Quarrels and dispute over international trade are therefore more likely to arise and it's impossible today to negotiate international trade agreements without dispute resolution mecanism. Success or failure of different type of arbitration lies in the definition of the substantive rules of trade agreements. For binding arbitration to work properly, such rules must be clear and precise. But this solution implies that independant countries renounce in part to their sovereignty. To do so, Canada and the United States decided to keep their own trade laws and accepted to submit them to binding arbitration. The same thing was done when free trade was extended to Mexico. At multilateral level, this type of arrangement would be much more difficult to implement.
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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 | 0.020 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".