Research on the Issue of the Applicability of the Doctrine of the Forum Non Conveniens in the Article 33 of Montreal Convention
Bibliographic record
Abstract
For the unity of the rules of Jurisdiction in international air transport, article 33 of Montreal Convention 1999 inherited the article 28 of Warsaw Convention 1929, which prohibits the application of the doctrine of form non conveniens. For the purpose of protecting Americans, the fifth jurisdiction was incorporated in the MC99. In a recent case, U.S. court tried to separate the intrinsic link between the two conventions, holding that the doctrine of forum non conveniens could be applied in all of jurisdiction rules. From the perspective of treaty interpretation, there are four reasons which demonstrate such ruling was wrong. Firstly, the French version of MC99 on the different jurisdiction rules taking different words. Secondly, the purpose of unified jurisdiction and passenger protection and consumer protection show that the doctrine should not apply in four jurisdictions. Thirdly, Travaux Paratories indicated that codifying the doctrine was still suspending. All of the evidences show that the application room of the doctrine is limited to the fifth jurisdiction and can not extend to the other four jurisdictional rules. Thus, the practice of American courts is inconsistent with the MC99,which seriously derogated the unity of the treaty and the pursuit of protecting travelers.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 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".