Inclusive conservation and the Post-2020 Global Biodiversity Framework: Tensions and prospects
Bibliographic record
Abstract
The draft Post-2020 Global Biodiversity Framework commits to achievement of equity and justice outcomes and represents a "relational turn" in how we understand inclusive conservation. Although "inclusivity" is drawn on as a means to engage diverse stakeholders, widening the framing of inclusivity can create new tensions with regard to how to manage protected areas. We first offer a set of tensions that emerge in the light of the relational turn in biodiversity conservation. Drawing on global case examples applying multiple methods of inclusive conservation, we then demonstrate that, by actively engaging in the interdependent phases of recognizing hybridity, enabling conditions for reflexivity and partnership building, tensions can not only be acknowledged but softened and, in some cases, reframed when managing for biodiversity, equity, and justice goals. The results can improve stakeholder engagement in protected area management, ultimately supporting better implementation of global biodiversity targets.
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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 | 0.036 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.039 |
| Scholarly communication | 0.018 | 0.018 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".