Community Forestry in Nepal’s Terai Region: Local Resource Dependency and Perception on Institutional Attributes
Bibliographic record
Abstract
Since the 1970s, the implementation of community forestry (CF) programs in Nepal has recognized that local involvement is a prerequisite for sustainably managing forests and fulfilling local resource needs. Although this devolution policy of active local participation has halted and in many cases reversed forest degradation, a comprehensive research on attributes of CF and its impact on local community livelihoods, especially among the rural populations in the low-lying Terai region- is lacking. Hence, using an institutional analysis approach, this research attempts to understand changes in forest management and governance. More specifically, this paper explores major attributes of CF, i.e. the forest, dependency of local people on the forest, institutions that govern local people interaction with the forest and other actors as well as economic and tree cover outcomes. The overall results indicated that most respondents were highly dependent on local forests for economic, ecological and cultural purposes and were collectively involved in creating rules and regulations that defined access to and distribution of CF benefits. The results also indicated that locals’ main priorities were to improve their income generation capabilities, whereas CF management primarily emphasized forest protection and local development, as CF-generated funds were used to improve local infrastructure. Hence, the main constraints to CF sustainability were identified to be the CF committee’s lack of transparency in fund expenditure and the exclusion of poor and disadvantaged households in the decision-making process. The study concludes that CF implementation is feasible in the Terai region and that equal decision-making participation is critical toward future CF sustainability.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".