Linking the Mountain Futures Action Plan to the Kunming-Montreal Global Biodiversity Framework
Bibliographic record
Abstract
Global mountains hold great value to many people, harbor great amounts of biodiversity and provide many ecosystems services. Yet they have not been well-represented in specific targets under international policy conventions including the UN Sustainable Development Goals and the Convention on Biological Diversity. This paper explores the efforts of one consortium of actors led by the Mountain Futures Initiative, to create and implement an action plan to link research and field projects at the Honghe Innovations Centre for Mountain Futures to targets in the new Kunming-Montreal Global Biodiversity Framework (GBF). This action plan will combine research on agroforestry, soil restoration, ecosystems restoration and connectivity, new green products and supply chains, and more in service of both healthy ecosystem outcomes and lifeways support for local smallholder farmers. Results show that connecting local research goals to GBF targets may leverage more positive outcomes for people and nature.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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 teacher head, 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".