Kegiatan Pengembangan Koleksi Di Dinas Perpustakaan Dan Kearsipan Kabupaten Banyuasin Ditinjau Dari Teori G. Edwards Evans
Bibliographic record
Abstract
Kegiatan pengembangan koleksi merupakan hal yang penting untuk dilakukan, terlebih pada tahapan-tahapan pada kegiatan pengembangan yang harus diperhatikan dan dilakukan sebaik mungkin. Tahapan pengembangan koleksi penting diperhatikan agar kebutuhan informasi bagi pengguna dapat dilakukan dengan tepat sesuai kebutuhan. Tujuan dari penelitian ini adalah untuk mengetahui tahapan pengembangan koleksi yang dilakukan oleh Dinas Perpustakaan dan Kearsipan Kabupaten Banyuasin. Pada penelitian ini menggunakan metode kualitatif deskriptif teknik pengumpulan data melalui wawancara dan studi literature, wawancara melalui chat dan telpon whatsapp kepada dua orang pustakawan Dinas Perpustakaan dan Kearsipan Kabupaten Banyuasin. Hasil penelitian ini ialah tahapan pengembangan koleksi di Dinas Perpustakaan dan Kearsipan Kabupaten Banyuasin terdiri dari analisis awal, kebijakan koleksi, seleksi bahan pustaka, pengadaan, penyiangan dan evaluasi.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.006 |
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".