ANALISIS IMPLEMENTASI KEBIJAKAN KETERBUKAAN INFORMASI PUBLIK PADA BADAN PERPUSTAKAAN DAN KEARSIPAN DAERAH PROVINSI JAWA BARAT
Bibliographic record
Abstract
ABSTRAK Penelitian ini mengangkat masalah implementasi kebijakan Keterbukaan Informasi Publik pada Badan Perpustakaan dan Kearsipan Daerah Provinsi Jawa Barat. Penelitian ini menggunakan pendekatan post positivist dengan metode kualitatif. Hasil penelitian ini menunjukkan bahwa (i) implementasi kebijakan KIP di Badan Perpustakaan dan Kearsipan Daerah Provinsi Jawa Barat belum berjalan efektif karena keterbatasan mempergunakan isi kebijakan dan konteks implementasi sehingga belum dapat terwujudnya keterbukaan informasi publik; (ii) untuk mendorong implementasi kebijakan KIP pada Badan Perpustakaan dan Kearsipan Daerah Provinsi Jawa Barat agar lebih efektif dapat mengacu tahapan pelaksanaan kebijakan informasi publik yang digagas oleh Open Government Partnership. Tindakan yang disarankan untuk memperbaiki implementasi kebijakan keterbukaan informasi publik adalah penyesuaian regulasi KIP di Kemendagri, penyusunan program yang jelas untuk implementasi kebijakan keterbukaan informasi publik, peningkatan kualitas pelayanan informasi publik, dan menciptakan sistem bank data dan informasi publik di Badan Perpustakaan dan Kearsipan Daerah Provinsi Jawa Barat. Kata kunci: implementasi kebijakan, kebijakan keterbukaan informasi publik.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.005 |
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".