Bibliographic record
Abstract
In this edition of the Asia Pacific Journal of Ocean Law and Policy, authors deliver two important contributions from the reaches of the Bay of Bengal to the Arctic Ocean.Both of these contributions are highly relevant to the evolution of State Practice.Beginning in Bangladesh, Muhammed Farhad Hosen offers insight into the recently revised Territorial Waters and Maritime Zones Act that implements Bangladesh's obligations under the UN Convention of the Law of the Sea as well as creating a governance blueprint for implementing Blue Economy practices across a number of key economic sectors.In particular as described in the state practice report following, Bangladesh has made major revisions to prosecuting ocean-related crimes including authorizing the establishment of one or more Maritime Tribunals.As Mr. Hosen indicates, the next important step for the Bangladeshi government will be ensuring that the new law achieves full implementation through Bangladesh's administrative institutions.Travelling over to the Arctic Ocean, Professor Jeffrey Smith from Carleton University in Canada offers a significant contribution on Canada's cooperation with Denmark to resolve disputes over Hans Island with a 2022 signing of a land boundary treaty.He emphasizes that Canada and Denmark's cooperative resolution is an important global signal of the ability for two States to peacefully resolve differences over continental shelf and exclusive economic zone boundaries.As he underscores in his report, building and maintaining trust remains the key ingredient to successful national ocean cooperation.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.008 |
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".