Educational Gradients in Disability among Asia’s Future Elderly: Projections for the Republic of Korea and Singapore
Bibliographic record
Abstract
Asia is home to the most rapidly aging populations in the world. This study focuses on two countries in Asia that are advanced in terms of their demographic transition: the Republic of Korea and Singapore. We developed a demographic and economic state-transition microsimulation model based on the Korean Longitudinal Study of Aging and the Singapore Chinese Health Study. The model was employed to compare projections of functional status and disability among future cohorts of older adults, including disparities in disability prevalence by educational attainment. The model also projects increasing disparities in the prevalence of activities-of-daily-living disability and other chronic diseases between those with low and high educational attainment. Despite overall increases in educational attainment, all elderly, including those with a college degree, experience an increased burden of functional disability and chronic diseases because of survival to older ages. These increases have significant economic and social implications, including increased medical and long-term care expenditures, and an increased caregiver burden.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".