Edukasi Tanggap Bencana Melalui Kegiatan Sosialisasi Guna Mewujudkan Masyarakat Desa Pijot Yang Tangguh
Bibliographic record
Abstract
Desa Pijot secara administratif merupakan salah satu dari 15 desa di Kecamatan Keruak, yang teletak pada radius 3 kilometer sebelah timur Ibu Kota Kecamatan Keruak. Desa Pijot memiliki luas wilayah 715 hektar, tersebar pada 8 kepala dusun, dengan jumlah penduduk di Desa Pijot sebanyak 6113 jiwa. Jumlah penduduk yang banyak dan letak daerah yang berada di pesisir pantai dengan tinggi tempat dari permukaan laut sebesar 500 mdpl dan tingkat curah hujan 491 mm. Kondisi Desa Pijot yang secara geografis, geologis, hidrologis dan demografis yang rawan terhadap bencana dengan frekuensi yang cukup tinggi, serta fakta bahwa kesadaran dan pengetahuan masyarakat yang minim dalam melakukan penanggulangan bencana. Untuk itu pengabdi merasa perlu menanamkan pemahaman dan pembelajaran khusus kepada masyarakat melalui kegiatan sosialisasi tanggap bencana darurat. Tujuan kegiatan ini agar masyarakat memiliki pengetahuan terkait penanggulangan bencana dan selalu siap siaga saat terjadi bencana yang sewaktu-waktu bisa terjadi, sehingga dapat mewujudkan masyarakat Desa Pijot yang tangguh dan tanggap bencana.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.004 |
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".