Social Security and Population Ageing in Vietnam: A Guarantee for the Elderly People’s Life
Bibliographic record
Abstract
Demographic change affects the socio-economic development of any country. In Vietnam, the population and housing censuses from 1989 to 2019 showed an appreciable increasing proportion of the elderly in the total population and fast ageing pace. Older people have many difficulties in their life. Among them, only 27% have pensions or stable incomes, and the rest 73% live without pensions, facing many difficulties. Vietnam is a developing country, and social security policies are in the process of completion. Therefore, improving the social security system, as well as creating opportunities for active ageing and wellbeing for older people, was one of the strategic goals of the Long-Term Development Plan that Vietnam’s government has been carried out for more than half a century. In this article, the issues of demographic change, population ageing, social security system, social assistance and pension benefits as the actual sociological problem are studied by using quantitative methods and comparative analysis approach to confirm the research questions; the proposals made by the authors can be helpful for today’s reforming social security system in Vietnam and social policy making in context of ageing in Vietnam where a large number of elderly people do not have any social benefits.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".