A proposal to introduce an Advocate General's position into WTO dispute settlement
Bibliographic record
Abstract
Introduction Thanks to the legal statesmanship of members of the World Trade Organisation (WTO) Appellate Body and to support of WTO members, the legal procedures established under the Understanding on Rules and Procedures Governing the Settlement of Disputes (DSU) have enjoyed very considerable success. But the DSU remains a work in progress. Much can still be done to develop and refine this process. A host of issues, some reflecting policy choices, some more strictly legal, remain to be resolved. By no means have all the concerns of negotiators in 1994 been answered. Some have proven to be well-founded, and new problems have arisen which challenge both the procedures and the rules of the DSU. As a contribution to the search for solutions, this chapter proposes the creation of a new position attached to the DSU process – that of the Advocate General. The Advocate General (AG) would participate in WTO dispute settlement procedures. A roster of Advocates General should be created to serve both panels and the Appellate Body. Given the nature of the function, the roster should be composed exclusively of jurists, knowledgeable in WTO procedure and law, and would be selected by the Dispute Settlement Body (DSB). An AG would be designated to follow each dispute. His or her principal function would be to participate in the dispute settlement procedures from the point that a panel is constituted to the point that the Appellate Body has rendered its decision.
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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 | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.027 | 0.019 |
| Insufficient payload (model declined to judge) | 0.009 | 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".