Forest Incomes after Uganda's Forest Sector: Are the Rural Poor Gaining?
Bibliographic record
Abstract
"Forest sector governance reform is frequently promoted as a policy tool for achieving favorable livelihood outcomes in the low income tropics. However, there is a dearth of empirical evidence to support this claim, particularly at the household level. Drawing on the case of a major forest sector governance reform implemented in Uganda in 2003, this study seeks to fill that gap. The research employs a quasi-experimental research design utilizing pre and post reform income portfolio data for a large sample of households surrounding three major forests in western Uganda; a control group is included in the design. \n \n"On private forest land overseen by the decentralized District Forestry Service there has been no significant change in average annual household income from forests, and the share of total income from forests has only slightly increased. For households living adjacent to Budongo Central Forest Reserve, overseen by the parastatal National Forestry Authority, there have been significant gains in average annual household income from forests, as well as the share of total income from forests. However, increases are limited to households in the highest income quartile and are primarily attributed to the sale of illegally harvest timber. The findings from this study challenge the view that governance reforms result in favorable livelihood outcomes for the poorest. Policy makers should carefully consider the incentives facing both forestry officials and local resource users with particular attention to increasing awareness of the value of trees and forests, and facilitating legal opportunities for rural smallholders across all income categories to sustainably engage in forest product harvesting and value addition."
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".