Accommodating the Interest of Local Community in Resolving Conflicts: A Case in Bentayan’s Wildlife Area, South Sumatra, Indonesia
Bibliographic record
Abstract
The developments of forest conservation Wildlife (SM) in Bentayan as flora and fauna ecology has created a conflict within the society and has negatively affected the wellbeing of the community in the area. The communities have used a lot of natural resources for their life. A development of Bentayan’s Wildlife Centre has been opposed by the community as the usage of various natural resources have been restricted after the development of the wildlife centre started. In order to solve the conflicts, many strategies have been employed. However, the expected outcome has not yet been achieved. Therefore, the current study provides a conflict resolution model approach to accommodate the interests of all parties, both society and government through the Natural Resources Conservation Center. The model was developed from narrative data that was collected through series of dialogues and negotiation process with both parties (community and agency/Centre) involving stakeholders and community members. This proposed model can be used as a framework for managing forestry and wildlife centre.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".