Mereformasi Tata Kelola Sumber daya Aparatur Sipil Negara
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Penelitian ini dimaksudkan untuk menghasilkan sebuah rekomendasi dalam upaya meningkatkan kulitas sumber daya manusia hal ini diangkat berdasarkan permasalahan pada faktor-faktor yang mempengaruhi peningkatan kualitas sumber daya manusia dan keterkaitannya dengan pelaksanaan prinsip efektivitas dan efisiensi yang belum maksimal. pemberdayaan individu sangat penting karena untuk mampu menciptakan pengetahuan, produk, dan jasa melalui jaringan kerja yang inovatif baik didalam organisasi maupun diluar organisasi. Penerapan organisasi pembelajaran ini lebih dimaksudkan bagi pegawai agar mampu mengembangkan kapasitasnya secara berkelanjutan dalam mewujudkan optimalisasi dalam pelayanan terhadap masyarakat
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 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 it