Global collaborative implementation of Kunming-Montreal Global Biodiversity Framework: An analysis of challenge and solutions based on the SFIC model
Bibliographic record
Abstract
朱旭 1,2* , 李嘉奇 1,2 1. 西安交通大学马克思主义学院, 西安 710049; 2. 西安交通大学亚欧研究中心, 西安 710049 摘要: 《昆明-蒙特利尔全球生物多样性框架》(简称《昆蒙框架》)的落实是新阶段全球生物多样性治理的重中之重。本文基 于相关文献资料查阅, 引入协同治理模型(Starting conditions-Facilitative leadership-Institutional design-Collaborative process, SFIC模型), 旨在以一种整体性、系统性思路考察《昆蒙框架》落实面临的挑战, 并分析总结应对策略, 以期为《昆蒙框架》 落实提供一定参考。首先, 根据《昆蒙框架》落实对全球协同的客观需要, 以及现有研究整体性分析思路缺乏的情况, 引出 本文使用的SFIC模型并说明适用性。然后, 根据SFIC模型运行的要素, 结合现实情况, 分析了《昆蒙框架》落实面临的发展 中国家与发达国家治理基础、合作关系、参与动机、信息沟通、信任建立、资金筹措、后续协商、制度设计、主体领导等方 面的挑战。
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".