Marine protection targets: an updated assessment of global progress
Bibliographic record
Abstract
Abstract Despite the considerable expansion in the number and extent of marine protected areas during the past century, coverage remains limited amid concerns that many marine protected areas are failing to meet their objectives. New estimates of global marine protected area, based on the database maintained by Sea Around Us, revealed a degree of progress towards protecting at least 10% of the global ocean by 2020. It is estimated that > 6,000 marine protected areas, covering c. 3.27% (12 million km2) of the oceans, had been designated by the end of 2013. However, protection is generally weak, with c. one-sixth (1.9 million km2) of the combined area designated as no-take areas (i.e. fishing and other extractive activities are prohibited). Additional large tracts of ocean will need to be protected to reach the 10% target, and we investigate hypothetical scenarios for such expansion. Such scenarios offer a one-dimensional measure of progress as they do not address aspects of other global targets, such as Aichi Target 11, which will help to ensure that marine protected areas meet their objectives and achieve conservation outcomes.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".