The functions and challenges of grass-roots local governments in fulfilling the Kunming-Montreal Global Biodiversity Framework—A comparative analysis with the objectives of the United Nations Framework Convention on Climate Change
Bibliographic record
Abstract
Backgrounds: To achieve the Kunming-Montreal Global Biodiversity Framework (KMGBF) within the Chinese context, grass-roots local government are key players, as they implement or oversee most actionable measures.China's system excels at mobilizing collective efforts for national tasks like biodiversity management and climate change response.Challenges: Nevertheless, in the execution of top-down directives, grass-roots local government are inclined to prioritize and exhaustively implement initiatives that are tied to performance evaluation metrics.The comparative •保护与治理对策• 昆蒙框架如何在中国体制下成为主流工作目标专题 顾婧婧等: 基层地方政府在完成《昆蒙框架》中的作用和难点: 基于《联合国气候变化框架公约》任务的比较 2025年
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".