PENDAMPINGAN LITERASI PEACEBUILDING DENGAN PENDEKATAN DAKWAH PERSUASIF PASCA KONFLIK SUKU DAYAK MADURA PADA KOMUNITAS MASYARAKAT PENGUNGSI SUKU MADURA
Bibliographic record
Abstract
Peace building literacy assistance to refugees of the Madurese conflict in Pamekasan Regency is an urgent step as a preventive measure for subsequent conflicts that continue to haunt Madurese refugees in Pamekasan. The refugees must obtain comprehensive knowledge about the diversity of the Republic of Indonesia through an approach that suits their characteristics, namely a persuasive da'wah approach as an effort to operationalize friendly Islamic teachings in a concrete form. This is because the refugees still have a high desire to return to Kalimantan someday. In fact, many of their family members had already returned to the island of Borneo to seek fortune as they had before the bloody events several decades ago which became a black record for the Indonesian nation. This mentoring activity uses a Word of Mouth approach, namely conveying messages by word of mouth as an individual approach and through "koloman" or halaqoh-halaqoh, namely group activities which have become a habit for Madurese people. Keywords: Peacebuilding Literacy, Word of Mouth dan “Koloman”
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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".