Asistensi Penyusunan Rancangan Teknokratik Rencana Pembangunan Jangka Menengah Daerah Kota Kediri
Bibliographic record
Abstract
Pembangunan daerah merupakan proses kompleks yang mencakup berbagai aspek sosial, ekonomi, dan kebijakan publik. Kegiatan pengabdian ini bertujuan memberikan asistensi kepada Pemerintah Kota Kediri dalam menyusun Rancangan Teknokratik RPJMD 2025–2029 sebagai dasar perencanaan pembangunan yang berbasis data, inklusif, dan berkelanjutan. Pendekatan teknokratik digunakan melalui pengumpulan data primer dan sekunder terkait geografi, demografi, dan kondisi sosial-ekonomi Kota Kediri. Proses ini dilengkapi dengan workshop dan diskusi panel yang melibatkan berbagai pemangku kepentingan untuk memvalidasi temuan dan merumuskan visi pembangunan. Evaluasi dilakukan melalui analisis isu strategis serta penyusunan indikator SMART untuk memperkuat implementasi kebijakan. Kegiatan ini meningkatkan kualitas perencanaan daerah dan memperkaya kajian dalam ilmu perencanaan wilayah. Melalui pengabdian ini, Pemerintah Kota Kediri diharapkan dapat menghasilkan kebijakan yang responsif terhadap tantangan lokal dan mendukung tujuan pembangunan berkelanjutan.
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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.059 | 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; 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".