Mare Liberum to Mare Curare: The IMO’s Prospective Role in Implementing Area-Based Management Tools for the BBNJ Agreement
Bibliographic record
Abstract
Abstract for Scopus Indexing: With the long-awaited Biodiversity beyond National Jurisdiction ( BBNJ ) Agreement finally opened for signature, discussion turns towards what tools and systems the BBNJ Agreement will utilize in the future. This article discusses the potential implementation of MPA s and ABMT s by the BBNJ Agreement through the utilization of the International Maritime Organization’s ( IMO ) existing tools and processes. It considers the IMO ’s experience in environmental protection in both national waters and areas beyond national jurisdiction. The criteria for establishing ABMT s under the BBNJ Agreement are compared to MARPOL and the PSSA processes utilized by IMO , and each of the tools that could be utilized under these processes are discussed for their relevance to protecting areas beyond national jurisdiction. Finally, the article ends with a discussion of how certain methods of monitoring and control used by IMO may provide assistance and guidance to enforcement of the BBNJ Agreement and review of MPA s that it may implement in the future.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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".