A Contrast of Criteria for Special Places Important for Biodiversity Outcomes
Bibliographic record
Abstract
This paper contrasts seven spatial biodiversity conservation area designations by six different bodies: Other Effective Area-Based Conservation Measures (OECMs), and the Ecologically and Biologically Significant Areas (EBSAs) of the Convention on Biological Diversity (CBD); the Vulnerable Marine Ecosystems (VMEs) of the Food And Agriculture Organization (FAO); the Key Biodiversity Areas (KBAs) under criteria developed by the IUCN; the Areas of Particular Environmental Interest (APEIs) of the International Seabed Authority (ISA); the Particularly Sensitive Sea Areas (PSSAs) of the International Maritime Organization (IMO); and the Locally Managed Marine Areas (LMMAs) used by small island States in the Pacific Ocean; on five themes: biological and ecological features, functions served by areas receiving these labels, governance, threats and pressures, and other considerations. The seven different labels for such areas were generally similar in the biologically and ecological criteria to be met, and the functions typically served by these areas. Differences among the labels increased when considering governance, threat and pressures, and other considerations. Implications of these similarities and differences for policy development and outcomes are discussed. Performance reviews of the various labels under these themes could provide insight into both the effectiveness of the provisions in the Agreements and Decisions and how evidence is acquired and used to inform their application, allowing improvements to each approach to learn from experiences with other labels.
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 | 0.036 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".