KAJIAN REVITALISASI PASAR TRADISIONAL SRIWANGI KECAMATAN SEMENDAWAI SUKU III SEBAGAI UPAYA MENINGKATKAN KUALITAS HIDUP MASYARAKAT
Bibliographic record
Abstract
Kabupaten Ogan Komering Ulu Timur sebagai salah satu daerah otonom hasil pemekaran mempunyai fungsi strategis sebagai daerah transit, karena letaknya yang merupakan simpul arus transportasi yang menghubungkan beberapa daerah seperti berbatasan dengan provinsi lampung, Kabupaten Ogan Komering Ulu Selatan, Kabupaten Ogan Komering Ulu, Kabupaten Ogan Komering Ilir serta dilewati oleh jalur lintas tengah Sumatera.
 Berdasarkan fungsi dan letak tersebut, maka laju perkembangan dan pertumbuhan ekonomi Kabupaten Ogan Komering Ulu Timur cukup cepat. Kabupaten Ogan Komering Ulu Timur mempunyai pasar tradisional, baik yang di kelola oleh Pemerintah Kabupaten maupun Pemerintah Desa lebih kurang berjumlah 70 unit. Sebagian besar kondisi pasar tradisional tersebut belum memadai dan merupakan bangunan lama, sarana dan prasarana yang belum bisa menampung seluruh pedagang, sehingga banyak pedagang yang masih berjualan di dasaran/tenda-tenda darurat.
 Oleh sebab itu, pemerintah daerah mempunyai program prioritas untuk merevitalisasi pasar-pasar tradisional yang ada sebagai pusat penyediaan bahan pokok dan barang strategis lainnya sehingga menjaga ketersediaan bahan pokok dan penguatan jaringan distribusi.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.076 | 0.025 |
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".