Assissing land-use governance systems as potential OECMs in Iceland
Bibliographic record
Abstract
Protected areas (PAs) and Other Effective Area-based Conservation Measures (OECMs) are nation states’ key conservation strategies to meet the 30 per cent area-based conservation target of the Global Biodiversity Framework (GBF). Iceland is updating its biodiversity strategy, aligning with the GBF targets. The objective of this study is to progress the development of OECMs and to examine their potential in Iceland. Iceland has multiple area-based governance systems with various objectives, additional to its formal PA estate. We identify and analyse relevant area-based governance systems in the country, employing a stepwise approach based on institutional analysis and application of the IUCN-WCPA OECM site-level tool. The study identifies eleven area types for consideration while the analysis reveals their different qualities and challenges and suggests eight of these as potential OECMs. This first study of terrestrial OECMs in Iceland illustrates a considerable potential to expand such area-based conservation efforts. OECMs are not yet included in Iceland’s nature conservation policy framework, highlighting a need for national policy guidance, for which we provide recommendations
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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 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".