Governance on provision of ecosystem and its services in Nepal: Lessons from appraisal of policy, legislation, and institution
Bibliographic record
Abstract
Ecosystem degradation and the loss of ecosystem services stem from multiple causes, requiring coordinated and diverse policies, legislation, and institutional responses to effectively address them. An understanding of the policies, legislation, and institutions governing ecosystem services can enhance the sustained management and provision of ecosystem services. Therefore, this work appraises the policies, legislation and institutional provisions made by the government of Nepal. In addition, this study analyzes policy implications and identifies gaps and barriers that hinder future improvements in the management of ecosystem services. Altogether, 63 documents comprising 45 policies and 18 legislations promulgated by the government of Nepal have been assessed for content analysis. Twenty Key Informant Interviews (KIIs) have also been conducted to obtain expert insights about the gaps in policy formulation and implementation. The results indicate that though several sectoral policies and legislations have made provision on management of ecosystem and its services implicitly or explicitly, still there is lacking of overarching framework to deal with ecosystem services. Overlapping roles and responsibilities outlined in the constitution, policies, and legislation, coupled with weak enforcement and lack of multisectoral coordination mechanism, are significant obstacles to effective policy implementation. Therefore, there is a need to develop an overarching national framework backed up by legislation with a strong multisectoral coordination mechanism that will adopt a holistic and multidisciplinary approach to the sustained management and provision of the ecosystem and its services.
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 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".