Convention on Biological Diversity and its protocols: Negotiation, challenges and recommendations on the “capacity-building and development”
Bibliographic record
Abstract
Background & Aim: Capacity-building and development (CDD) is an integral part to implementing the protocols of the Convention on Biological Diversity (CBD), and an effective means to put the new Kunming-Montreal Global Biodiversity Framework (GBF) into action. CDD is crucial, in developing countries, for promoting the implementation of the CBD and achieve positive results. This paper aims to provide guidance for effective implementation of the Kunming-Montreal GBF and completion of its goals, and further explore policy priorities that could potentially address the issue. Review Results: It is known that none of the "Aichi Targets" have been fully achieved at the global level. Furthermore, the international community realizes the need to alter past approaches that were largely focused towards setting targets than taking actions. Here, we systematically review the policy decisions adopted by the Conferences of the Parties (COPs) to the CBD and its protocols in regard to CDD. The findings show that due to the increasing concerns for the CDD under CBD, the COPs recommend a reorienting of priorities from the long-term focus on information exchange
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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 | 0.141 | 0.131 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.018 | 0.016 |
| Open science | 0.010 | 0.010 |
| Research integrity | 0.019 | 0.022 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".