Pola Segregasi Sosio-Spasial di Kawasan Permukiman Akibat Pembangunan Maluku City Mall (Studi Kasus: Desa Galala dan Negeri Hative Kecil)
Bibliographic record
Abstract
Pembangunan pusat perbelanjaan modern seperti Maluku City Mall (MCM) di Kota Ambon membawa perubahan signifikan terhadap dinamika sosial, ekonomi, dan spasial masyarakat di sekitarnya. Penelitian ini bertujuan untuk mengidentifikasi pola segregasi sosio-spasial serta menganalisis faktor-faktor yang memengaruhi terbentuknya segregasi pada kawasan permukiman Desa Galala dan Negeri Hative Kecil. Metode yang digunakan adalah mixed methods dengan kombinasi analisis Index of Dissimilarity (IoD), analisis diskriminan, serta analisis spasial berbasis GIS. Hasil penelitian menunjukkan bahwa segregasi pada aspek ekonomi dikategorikan rendah (IoD rata-rata 33,33%), sedangkan segregasi pada aspek sosial tergolong sedang (IoD 46,47%). Analisis diskriminan menegaskan bahwa strata masyarakat merupakan faktor dominan yang membedakan tingkat segregasi antar kelompok. Temuan ini mengindikasikan bahwa pembangunan MCM selain mendorong pertumbuhan ekonomi juga berpotensi memperlebar kesenjangan sosial. Oleh karena itu, pengelolaan ruang kota perlu diarahkan pada kebijakan zonasi dan tata ruang yang inklusif agar manfaat pembangunan dapat dirasakan secara merata, sekaligus mencegah fragmentasi sosial di kawasan perkotaan Ambon.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".