Towards a Regional MPA Network in the South China Sea: General Perspectives and Specific Challenges
Bibliographic record
Abstract
Devoted to assessing the state of ocean and coastal governance, knowledge, and management, the Ocean Yearbook Online provides information in one convenient resource. Articles provide multidisciplinary expert perspectives on contemporary issues. Each new volume draws on policy studies, international relations, international and comparative law, management, marine sciences, economics, and social sciences. Each volume contains key legal and policy instruments and an annually updated global directory of ocean-related organizations. The Yearbook is a collaborative initiative of the International Ocean Institute in Malta and the Marine & Environmental Law Institute at the Schulich School of Law, Dalhousie University, Halifax, NS, Canada. The Yearbook is also available in print. We are pleased to announce that the Ocean Yearbook is part of a new Research4Life program launched in March 2018, providing online access to academic legal content in developing economy countries. Researchers, librarians, policy-makers, judges and legal experts from more than 115 low- and middle-income countries will receive free or low-cost online access to law and law-related academic and professional peer-reviewed content through their institutions. Access is provided by a new program, Global Online Access to Legal Information (GOALI), a multi-stakeholder initiative of the Research4Life partnership. Eligibility access to Research4Life. How to Register.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".