Diagnosing scaling bottlenecks in ten community conservation initiatives in South and East Africa
Bibliographic record
Abstract
Scaling area-based conservation, including through initiatives ed or co-managed by Indigenous Peoples and local communities, is a flagship goal of the Kunming-Montreal Global Biodiversity Framework. Conservationists often aspire to scale initiatives, but this is rarely achieved in practice. Identifying and addressing “bottlenecks” – factors that limit initiative adoption – could help shape more effective scaling strategies. Therefore, we integrate insights from 84 experts with existing evidence to identify potential risk factors and bottlenecks to scaling ten community area-based initiatives in South and East Africa. The number of reported potential risk factors and bottlenecks varied among initiatives. However, governance and distributional issues – including unfair benefit sharing, unequal decision-making, inflexible rules, and “top-down” leadership – were frequently highlighted as bottlenecks. Furthermore, adopting initiatives often presented costs (e.g., increased local conflict, reduced access to natural resources and cropland) but most experts believed these costs were offset by other benefits and thus did not constitute bottlenecks. While these results do not capture local perspectives, our findings suggest that scaling strategies that strengthen environmental governance may support more socially just and durable approaches to meeting area-based conservation goals.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".