Community forestry in Cameroon: Insights on state institutional deficits
Bibliographic record
Abstract
Community forestry (CF) was set-up in Cameroon about 20 years ago to enable better environmental, economic, and social benefits for communities. Since then, 430 community forests have been attributed, covering an area of almost 1.7M ha. However, less than a quarter (10%) are in active management or enterprise. Weak institutions have been widely cited as a leading cause of poor performance in the community forestry process. This paper examines the current state of institutional deficits in Cameroon and identifies pathways for overcoming the deficits. Our analysis is based on a rigorous review of documented experiences so far. Results obtained revealed that emerging deficits revolve around form and functions. Legal; power, authority and rights; and size and biophysical potential deficits were grouped under the realm of form while resources; capacity; and governance deficits were grouped under the realm of functions. Proposed solutions to these deficits point to the need to recognize and manage inter-dependencies between challenges and corresponding potential solutions. Hence a system or integrated approach is needed to tackle the problems identified.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".