Decadal changes in international advocacy toward the conservation of highly migratory fishes
Bibliographic record
Abstract
Abstract Highly migratory fishes, such as tunas, present conservation challenges because their ranges span the high seas and jurisdictional waters of coastal states. Governments are mandated to manage tuna fisheries through Regional Fisheries Management Organizations (RFMOs), so RFMO meetings have subsequently become one focal point for non‐governmental organizations (NGOs) seeking to influence the management process. Here we ask: how have the agendas of NGOs at RFMO meetings changed over time and where are they currently most effective at reforming tuna fisheries management? We systematically analyzed 216 advocacy statements submitted by NGO observers to RFMOs from 1999–2019 and interviewed 26 meeting attendees. We find that target tuna stock management measures accounted for over 20% of total advocacy over time and there has been a 26‐fold increase in calls for science‐based harvest strategies since 2010. We also find that 77% of policymakers were receptive to RFMO advocacy, but 57% of interviewees believe the most effective way to influence RFMO decisions was through engagement external to RFMO meetings. Relations between industry and environmental NGO observers are also improving due to sustainable seafood movement collaborations and we suggest these emerging cross‐sectoral partnerships could substantially improve the management of pelagic species if their efforts remain credible and transparent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".