National contributions to global ecosystem values
Bibliographic record
Abstract
Current conservation templates prioritize biogeographic regions with high intensity ecosystem values, such as exceptional species richness or threat. Intensity-based targets are an important consideration in global efforts, but they do not capture all available opportunities to conserve ecosystem values, including those that accrue in low intensity over large areas. We assess six globally-significant ecosystem values-intact wilderness, freshwater availability, productive marine environments, breeding habitat for migratory wildlife, soil carbon storage, and latitudinal potential for range shift in the face of climate change-to highlight opportunities for high-impact broadly-distributed contributions to global conservation. Nations can serve as a cohesive block of policy that can profoundly influence conservation outcomes. Contributions to global ecosystem values that exceed what is predicted by a nation's area alone, can give rise to countries with the capacity to act as 'conservation superpowers', such as Canada and Russia. For these conservation superpowers, a relatively small number of national policies can have environmental repercussions for the rest of the world.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.048 | 0.021 |
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; both teacher heads agree on what is shown here.
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".