KORBAN ALIH FUNGSI LAHAN DI KELURAHAN SETIANAGARA, KECAMATAN CIBEUREUM, KOTA TASIKMALAYA, JAWA BARAT
Bibliographic record
Abstract
Cibeureum District is one of the four sub-districts in the City of Tasikmalaya with the highest reduction in paddy fields area. The study was conducted in Setianagara which is included in the LP2B (Sustainable Food Agricultural Land) area but is still experiencing lang conversion. This study aims to determine the profile of victims of land use change, push and pull factors switching land use, and the condition of the victims before and after land use change. The design in this study used a qualitative descriptive design and research techniques using case studies. The information obtained comes from interviews and observations. Informants in this study are victims of land use change. The results showed that the factors driving the conversion of land originated from self and coercion, while the pull factors came from the buyers of the paddy fields and coercion. The situation of farmers before and after land use change has changed for the worse, more stable, and better.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".