Firms’ Integration into Value Chains and Compliance with Adverse WTO Panel Rulings
Bibliographic record
Abstract
Abstract This article aims to account for the variation in the time it takes for WTO Members to bring compliance following adverse panel rulings. It seeks to answer the question: under what conditions do defendants swiftly implement adverse rulings of WTO panels? I demonstrate that defendants are more likely to comply without delay when the targeted measures involve firms that are integrated into regional and global value chains. When a dispute touches upon the interests of these firms and targets import-restricting measures, they are triggered to mobilize and press for compliance because they rely on foreign imports. In effect, the mobilization of these firms changes the domestic political conditions in favor of timely implementation. I show the plausibility of my argument in a comparative design with four case studies in which the US and Canada acted as defendants in WTO disputes. I control for a number of political factors and also consider legal sources of variation – i.e. the complexity of the form of implementation – that may impact WTO Members’ record of compliance.
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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 | 0.027 | 0.122 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".