Penyuluhan dan Pendampingan Pemetaan Partisipatif di Kecamatan Anggeraja Kabupaten Enrekang
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Maps are presented to provide information in the form of boundaries, facilities, buildings, land use and roads. Regional boundaries are one element of the village map so that it needs to be mapped in detail as a document in development planning. Enrekang Regency, which has a majority of its elders as protected areas, is still very limited in the ownership of mapping documents. The community still does not have knowledge about this mapping so that the problem of regional boundaries, regional boundaries and land use limits is still a trigger for problems in the community. Participatory mapping is a method that is needed in order to provide spatial information so that the mapping process and the resulting map are aimed at the interests of the community. In this case, counseling and mentoring activities are the beginning of the development of competence and capacity for the community in making mapping documents in Enrekang District. It is expected that this community service activity will continue in partnership activities between Unhas and the Enrekang District Government, both in training, formal education in regional and city development master programs, and assistance in planning and implementing the development of Enrekang Regency, in line with the tridharma activities of higher education.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it