AGEING POPULATION AND ITS IMPLICATIONS FOR URBAN PLANNING IN SURABAYA CITY
Bibliographic record
Abstract
Surabaya is inevitably influenced by the global trend of an ageing population; thus, policymakers need to integrate this factor into the city's future planning. This research seeks to outline the forthcoming elderly demographic and suggest strategies that correspond with this emerging trend. This research employs a dual methodology, integrating numerical data analysis with descriptive insights. The methodology utilizes the cohort component projection approach alongside content analysis. Data was obtained through secondary surveys by extracting data from existing literature. The results indicate that by 2050, there will be a significant rise in the elderly demographic, which will directly impact the old-age dependency ratio, necessitating proactive measures to address this concern. The Surabaya City Government can pursue initiatives aligned with the Age-Friendly City concept, though enhancements across various dimensions of this framework are necessary beforehand. Keywords: Cohort Component Projection, Ageing Population, and Age-Friendly City.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".