COP16 and the process of consolidating an inclusive conservation paradigm
Bibliographic record
Abstract
The Convention on Biological Diversity’s (CBD) 15th Conference of the Parties (COP15) approved the Kunming-Montreal Global Biodiversity Framework (GBF), legitimizing a paradigm shift for conservation to link decisions and outcomes with diverse social actors (CBD, 2022). For example, target 3 aims to protect 30% of the planet by 2030. However, this 30×30 target must be met via equitable governance that recognizes and respects the rights and values of Indigenous peoples and local communities (IPs&LCs). Furthermore, the GBF incorporates non-Western understandings of nature and people−nature relationships (e.g., Mother Earth, nature’s gifts, living in harmony with nature). Recently, COP16 was to implement this inclusive vision, but parties did not reach a consensus on a new financing mechanism besides the Global Environmental Facility and a comprehensive monitoring system for national biodiversity strategies and action plans (NBSAPs) (Affinito et al., 2024). So, was COP16 a failure?...
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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 | 0.088 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.028 |
| Scholarly communication | 0.025 | 0.015 |
| Open science | 0.006 | 0.033 |
| Research integrity | 0.023 | 0.034 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".