The Caribbean Landscape Conservation Cooperative: a new framework for effective conservation of natural and cultural resources in the Caribbean
Bibliographic record
Abstract
Governmental and nongovernmental organizations charged with managing natural resources increasingly emphasize the need to work across jurisdictional boundaries. Their challenge is to manage shifting resources under rapidly changing climate and land-use scenarios. Scientists, resource managers, and conservation planners, and their organizations and agencies routinely collaborate on projects to solve specific problems. Cooperative frameworks to programmatically address complex social–environmental issues and develop shared research, planning, and implementation priorities are relatively new. One such framework includes 22 Landscape Conservation Cooperatives that encompass the US, Caribbean countries, and bordering regions of Mexico and Canada. The most recently established collaboration is the Caribbean Landscape Conservation Cooperative, which is intended to provide land managers with the best available scientific data and to assist them in developing shared conservation priorities and implementing conservation actions.
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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 | 0.041 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.024 | 0.010 |
| Open science | 0.007 | 0.018 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 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".