Governance Reform in the Forest Sector: A Role for Community Forestry? Paper prepared for the XII World Forestry Congress: Quebec City
Bibliographic record
Abstract
Tropical forestry is at a cross-roads. Rarely, nowadays, can aid investments in the forest sector be justified solely in terms of sector-specific effects. The emphasis is rather on the part which forestry can play in broader processes of social and environmental change. An area of growing concern is governance reform. This case study considers the part which community forestry can play as an entry-point for governance reform. It shows how an approach focused on community management of revenues from forest exploitation can encourage what is – potentially at least – a quantum shift in social and economic relations. The case of community forestry in Cameroon demonstrates the mutually supportive roles that can be played by ‘supply-side ’ policy changes and ‘demand-side ’ means to build accountability from below. It illustrates the importance of macro- and micro-level connections in promoting pro-poor change, and the ways in which improved governance can be made to satisfy both a poverty reduction and governance agenda. It is not suggested that the particular dilemmas of governance in the sub-sector have all been resolved. The case study notes some of the challenges that remain, relating both to governance and livelihoods.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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 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".