Dual Provisional Measures Prescribed by ITLOS and Annex VII Arbitral Tribunal: Reflections on the <i>“Enrica Lexie” Incident</i> Case
Bibliographic record
Abstract
Abstract In the “Enrica Lexie” Incident case between Italy and India, two judicial organs, i.e. the International Tribunal for the Law of the Sea (ITLOS) and the Annex VII Arbitral Tribunal prescribed provisional measures. It is rare that ITLOS and the Annex VII Arbitral Tribunal prescribed different provisional measures in the same dispute. The “Enrica Lexie” Incident case provides an insight into the procedural law governing provisional measures under the UN Convention on the Law of the Sea. This article examines the provisional measures prescribed by ITLOS and the Annex VII Arbitral Tribunal in the “Enrica Lexie” Incident case focusing particularly on three issues: (1) the relationship between the request by Italy submitted to ITLOS and that submitted to the Annex VII Arbitral Tribunal, respectively, (2) the existence of the urgency of the situation, and (3) the legal effect of considerations of humanity.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 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".