Settling Disputes in Regional Fisheries Management Organisations: Dealing with Objections
Bibliographic record
Abstract
The essential purpose of Regional Fisheries Management Organisations is to provide an effective forum within which states can agree on fisheries conservation and management measures. Discussions on these measures are at the very heart of the work of rfmo s and can raise complex issues giving rise to disputes that may threaten to undermine the objectives of an rfmo, particularly where opt-out or objection procedures are invoked by parties seeking to avoid application of the measures. Jurisdictional hurdles to the resolution of disputes among rfmo members under Part xv of the 1982 Law of the Sea Convention, as seen in the Southern Bluefin Tuna, and Fisheries Jurisdiction (Spain v Canada) cases, are increasingly being overcome by the adoption by rfmo s of more comprehensive dispute settlement provisions which effectively incorporate Part xv requirements into their mandates. In addition, new and expeditious ad-hoc panel procedures are emerging in rfmo s to deal with the issues of opt-outs and objections. This chapter examines this emerging practice and assesses the efficacy of these procedures both in providing guidance to the states concerned and in strengthening the ability of rfmo s to conserve and sustainably manage the fish stocks under their control.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".