Advancing equitable governance in area-based conservation
Bibliographic record
Abstract
This WCPA issues paper provides an overview of the equitable governance element of Target 3 of the Kunming Montreal Global Biodiversity Framework (GBF) agreed at COP15 of the Convention on Biological Diversity in December 2022, and strategies that could deliver real progress on this key element of what is also known as the “30x30” target. This paper focuses on five important developments in guidance and tools and in the context of area-based conservation since the earlier CBD-endorsed guidance of 2018. In terms of context, this paper covers the cross-cutting commitments in the GBF to a human-rights based approach, respecting and protecting IP & LCs rights, and recognising different value systems of different stakeholders and rightsholders, and better understanding of enabling conditions for advancing equity, and strategies to improve them. In terms of guidance and tools, this paper covers the role of social safeguards for both mitigating risks of future negative impacts on IPs & LCs and nature and for increasing benefits for people and nature, and monitoring progress on the equitable governance element of Target 3. Furthermore, we look at important linkages among Target 3 and Target 22 on procedural rights and Target 23 on gender equality
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".