Rehabilitation of degraded forests to improve livelihoods of poor farmers in South China
Bibliographic record
Abstract
Degradation of forests and forest lands is a problem in many parts of the world and is particularly serious in south China. Chinese forest policy reforms in recent years have enabled rural households to generate income from forests, to own the trees they have planted, and have offered new opportunities to manage forests sustainably. Rehabilitation of degraded forests and forest lands is one of the possible pathways to improve livelihoods of poor farmers and others in the rural communities. This report documents the results of four case studies in south China in which farmers, local officials and ressearchers anlysed the problems of degraded forests and forest lands, and formulated options for their solution. Opportunities to improve forest management and people's livelihoods are dependent on overcoming a range of biophysical, socioeconomic and political constraints. Action research was used to implement and test some of the options identified. The experience and analysis should be of value for researchers, resource managers and government officials in China and elsewhere to address poverty and environmental concerns through a multidisciplinary, participatory and holistic approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".