Boomerangs over Lac Léman: Transnational Lobbying and Foreign Venue Shopping in WTO Dispute Settlement
Bibliographic record
Abstract
Abstract In this article, we explore the conditions under which firms engage in transnational lobbying and foreign venue shopping in the framework of WTO dispute settlement. Classical World Trade Organization (WTO) dispute settlement cases mostly originate in domestic firms instigating their public authorities to bring a complaint against foreign trade barriers incompatible with WTO law. In recent years, however, we have witnessed the rise of WTO cases in which firms get a foreign government to file a case against its own authorities. By analysing transnational lobbying by EU firms in the WTO footwear case filed by China against the EU, and by US firms in the WTO gambling case Antigua brought against the US, we highlight the increasing resemblance between trade disputes and investment disputes.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".