Testing International Legal Regimes: The Advent of Automated Commercial Vessels
Bibliographic record
Abstract
International shipping is on the eve of a new era where remotely controlled and partially or fully automated and unmanned Maritime Autonomous Surface Ships (MASS) will be carrying international trade. The regulation of navigation and shipping in the contemporary international law of the sea and international maritime law are premised on human presence and control on-board ships. Provisions of the United Nations Convention on the Law of the Sea of 1982 and several maritime conventions will need to be revisited to determine how MASS may be accommodated and, where not possible, what further legal development may be needed. Recently, the International Maritime Organization (IMO) decided to address the expected regulatory impacts of these ships and to prepare an agenda for their proactive regulation. This article explores regulatory impacts that would need to be considered and argues that MASS have the potential to provide new directions for international law and the IMO.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".