Penguatan Ketangguhan Bencana Melalui Pendidikan Mitigasi Bencana Berbasis Traditional Ecological Knowledge (TEK) dan Optimalisasi Peran Social Capital (SC) bagi Masyarakat Nagari KBKA Pesisir Selatan
Bibliographic record
Abstract
Nagari Kampung Baru Korong nan Ampek (KBKA) Koto XI Tarusan District, Pesisir Selatan Regency has a high risk of natural disaster threats, namely earthquakes, tsunamis, landslides and floods. Meanwhile, Nagari KBKA is a potential village as one of the producers of Gambir in West Sumatra. The high threat of disaster risk and the impact of disasters on community activities, including economic activities, need serious attention. Many disaster mitigation education programs have been carried out, but have not touched on the empowerment of the KBKA natural local potential and the KBKA social system. This Community Service activity aims to strengthen community resilience to disasters by optimizing the existing natural resources and human resources in Nagari KBKA. This activity is carried out in 3 stages in the time span of July - November 2021 involving students, teachers, youth groups and housewives. The forms of activity consist of 1) Socialization on the potential, characteristics, symptoms and risks of disasters in coastal, hilly and mountainous areas and the importance of preparedness aspects, 2) Training to identify and utilize various social capital owned by the KBKA community, 3) Training to identify plants/vegetation potential in a disaster emergency period for preventing disasters, medicinal plants and alternative food), 4) Training to understand natural phenomena and changes in animal behavior before a disaster occurs, 5) Workshop on processing waste into ecoenzymes and 6) Planting Bungur Trees to reduce the risk of erosion in watersheds . The results of the activity show 1) an increase in the knowledge of students and teachers about natural phenomena, animal behavior, and potential disaster prevention plants, 2) an increase in the enthusiasm of the community for disaster preparedness, and 3) the acquisition of disaster prevention skills through waste processing into ecoenzymes.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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; both teacher heads agree on what is shown here.
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".