Praktik Pengembangan Program Perhutanan Sosial Sebagai Strategi Pelestarian Kawasan Hutan di Desa Yehembang Kangin
Bibliographic record
Abstract
Along with the pace of development and economic growth in a region, it cannot be separated from various kinds of activities that are at risk of environmental destruction, one of which is forests. Where, this has concretely occurred in the increasing cases of encroachment on forest areas in Jembrana Regency. This encroachment was triggered by "ngawen" activities and illegal logging which caused environmental damage and loss of biodiversity. Here, PT Pertamina Patra Niaga Aviation Fuel Terminal (AFT) Ngurah Rai plays a role in assisting the development of social forestry programs in Yehembang Kangin Village, Mendoyo District, Jembrana Regency, Bali Province to be able to increase public awareness of the importance of protecting forests and empowering the communities who are members of it. Banu Giri Lestari Forest Farmers Group in a sustainable manner. This research uses a descriptive qualitative approach supported by data collection techniques using purposive sampling. The results of the research show that the social forestry development program in Yehembang Kangin Village provides positive changes for the transformation of group behavior in forest conservation. Producing local heroes and their regeneration who are expected to be able to become agents of change in managing forests wisely and responsibly. Apart from that, the group has also been able to take the initiative in cultivating wood and fruit forest plants independently by practicing the "tanem tuwuh" pattern to support ecosystem sustainability and increase the diversity of flora and fauna in the forest.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".