Mapping and Categorizing Self-Help Agricultural Training Centers (SARTC) in South Sulawesi, Indonesia
Bibliographic record
Abstract
Self-Help Agricultural Training Centers (SARTC) is an institution established by advanced farmers with a willingness to share their successful farming experiences and create a learning community with peers.Mapping and classifying SARTC informs farming excellence and training service capability standards so that governments, communities, and farmers can obtain technologies that are more appropriate to the region's conditions.Therefore, this study aims to map and categorize SARTC in South Sulawesi, Indonesia.Data collection was conducted through interviews and observations by combining spatial analysis, interview results, and secondary data.The results showed that SARTC are spread across each geographical zone and classified based on their ability to provide training services independently.Based on this finding, SARTC have functioned as farmer-to-farmer extension institutions that are specifically organized and not individualized.The capability class of SARTC was found to be more dominant in the intermediate and primary classes.Therefore, the policy to be pursued is to upgrade the SARTC capability class to the primary class to make participatory extension more effective.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".