PERCEPATAN PEMENUHAN TENAGA KESEHATAN DI PUSKESMAS UNTUK DAYA UNGKIT PEMBANGUNAN KESEHATAN
Bibliographic record
Abstract
Keberadaan tenaga kesehatan, dalam Sistem Informasi SDM Kesehatan per Februari 2024 diketahui bahwa masih terdapat 4.699 (46%) Puskesmas yang belum memiliki 9 (sembilan) jenis tenaga kesehatan sesuai standar. Rendahnya ketersediaan tenaga kesehatan di Puskesmas, khususnya di wilayah timur, tentunya membutuhkan langkah-langkah percepatan dalam pemenuhan tenaga kesehatan di Puskesmas, yaitu dengan pemenuhan tenaga kesehatan melalui skema Pegawai Pemerintah dengan Perjanjian Kerja (P3K), redistribusi tenaga kesehatan, pengaturan Surat Izin Praktik (SIP), pemberian insentif tenaga kesehatan, pengembangan karir tenaga kesehatan, kolaborasi lintas program dan lintas sektor (Pemerintah Daerah, perguruan tinggi, Kementerian/Lembaga, dll), pemenuhan fasilitas kesehatan satu paket dengan pemenuhan tenaga kesehatan.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.018 |
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".