Statistical analysis on population ageing
Bibliographic record
Abstract
The ageing process affects the lives of all of us throughout its duration and on all levels. At the moment, Europe is facing a new challenge. Europeans, in unprecedented numbers, are very long-lived. In the last 50 years, the life expectancy at birth has increased by about 10 years, for both men and women. For the first time in the history of Europe there are so many people who have such a long and healthy life. At the same time, the working age population in the European Union has been declining for a decade and this trend is expected to continue. As the total population remains constant, the risk of labour shortages will increase, with an increase in the burden on older people to cover the social costs needed for the elderly population for a range of services associated with it. In recent years, Romania is facing a major problem, namely the alarming decline in the country's population, while exacerbating the ageing phenomenon. Thus, the population over 65 years increased, while the number of young people decreased. Also, this article analyses the evolution of the average number of pensioners and the average monthly pension in Romania, in the fourth quarter of 2020 compared to the fourth quarter of 2019, using, in this regard, a series of statistical indicators and graphs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".