Legal Standards and Dispute Resolution in Exclusive Economic Zone Delimitation: A Critical Analysis of Article 74 of the United Nations Convention on the Law of the Sea
Bibliographic record
Abstract
This paper critically examines the legal standards and dispute resolution mechanisms for the delimitation of Exclusive Economic Zones (EEZs) as outlined in Article 74 of the United Nations Convention on the Law of the Sea (UNCLOS). It explores the challenges associated with the application of the equity principle, highlighting its inherent ambiguity and the difficulties it poses in achieving consistent and fair outcomes. The paper also analyzes the limitations of voluntary dispute resolution mechanisms, such as negotiation and conciliation, particularly in cases involving significant power imbalances between states. Furthermore, the procedural complexities and costs associated with formal legal processes, such as arbitration and adjudication, are discussed as barriers to effective dispute resolution. The analysis underscores the need for reform and greater clarity in the application of Article 74, advocating for the development of more precise guidelines and the enhancement of regional cooperation frameworks to ensure equitable and sustainable resolutions to maritime boundary 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 | 0.097 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.017 | 0.064 |
| Scholarly communication | 0.022 | 0.018 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".