Central Sulawesi Forest Park: A Pattern of Tenure Conflict Resolution
Bibliographic record
Abstract
Tenurial conflicts between the community and the administration of the Central Sulawesi Forest Park area have persisted for a very long period, leading to both tangible and intangible losses.Each side presents claims and justifications for land ownership in the region.This study investigates the pattern of tenure conflict resolution in the Central Sulawesi Forest Park area, aiming to contribute to the optimal management and use of forest resources.A process hierarchical analysis utilizing a quantitative descriptive approach is employed as the study methodology.Based on the Global Priority calculation, the pattern of tenure settlement with the highest alternative weight priority is the social forestry conservation partnership, with a score of 1.17; law enforcement with a value of 0.49 and settlement of land acquisition in forest areas on land for agrarian reform objects with a value of 0.28.There are three alternatives for resolving land tenure conflicts in the Tahura Area of Central Sulawesi: 1) Social forestry with conservation partnerships, 2) Law enforcement, and 3) Settlement of land tenure in forest areas for land objects of agrarian reform.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".