Bibliographic record
Abstract
Is WTO dispute settlement a success story? Most scholars hold a positive opinion. However, the author has tried to move beyond the general Western consensus and focus on some areas where the effectiveness of WTO dispute settlement can be questioned the areas of remedies and sanctions, the question of access to dispute settlement and the treatment of complex factual, economic and scientific evidence.The author proposes to look at how the effectiveness of dispute settlement might be measured in the light of the objectives of WTO dispute settlement. The WTO dispute settlement system provides not only punishing, but also bringing the measure into conformity. Since the WTO dispute settlement fits more closely to the civil remedy model, sanctioning would arise only if there was a failure to cease the wrongful conduct or failure to pay the required compensation. But compensation under the WTO is designed only to provide an incentive for a Member to remove any offending measure and bring its laws into compliance.Making an assessment, the WTO dispute settlement has limited effectiveness in respect of remedies because it does not provide any remedy for the complaining Member other than removal of the offending measure and the forms of sanctioning that are provided, compensation and retaliation, are largely ineffective.There is reluctance for some members to engage in WTO dispute settlement because the process takes too long or lacks an effective remedy at the end of the process, cost, cultural differences, the strength of these factors depends on what the available alternatives are and the political implications of bringing another WTO Member to dispute settlement.Therefore, in order to understand the reasons why WTO Members are not using the system, we need information on what issues they face. Sometimes it is a problem of the WTO rules themselves, this is not appropriate for dispute settlement.Finally the author assesses as well the capacity of panels to assess both factual and expert evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.193 | 0.325 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.020 | 0.023 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".