Ketahanan Bersekolah Anak Miskin Usia 10-18 Tahun di Provinsi Nusa Tenggara Timur Tahun 2021
Bibliographic record
Abstract
Capaian belajar pada beberapa provinsi di Indonesia masih cukup rendah. Hal ini ditunjukkan dengan terdapatnya beberapa provinsi dengan angka putus sekolah cukup tinggi salah satunya Provinsi Nusa Tenggara Timur. Anak yang berasal dari rumah tangga miskin memiliki risiko lebih besar untuk putus sekolah. Pada tahun 2021, Provinsi Nusa Tenggara Timur menjadi provinsi dengan jumlah penduduk miskin terbesar ke-3 dan persentase penduduk usia sekolah terbesar di Indonesia. penelitian ini bertujuan untuk melihat gambaran umum dari faktor internal dan eksternal penduduk miskin usia 10-18 tahun yang putus sekolah di Provinsi Nusa Tenggara Timur tahun 2021 serta variabel yang memengaruhinya. Metode penelitian menggunakan data survei seosial ekonomi nasional 2021 dan analisis ketahanan hidup dengan accelerated failure time model. Menghasilkan menghasilkan variabel status bekerja, pendidikan kepala rumah tangga, status kelengkapan orang tua, dan status memperoleh Program Indonesia Pintar memengaruhi ketahanan anak bersekolah serta variabel status bekerja anak yang paling cepat mengalami putus sekolah.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".