Bibliographic record
Abstract
The rapid growth in the number of older people worldwide has created an unprecedented global demographic revolution. Improvements in hygiene and water supply and control of infectious diseases during the past century have greatly reduced the risk of premature death. As a consequence the proportion of the world’s population aged 60 and over is increasing more rapidly than in any previous era. In 1950 there were about 200 million people aged 60 and over throughout the world. There are now about 580 million and by 2025 the number of people over the age of 60 is expected to reach 1.2 billion. For the first time in history the majority of those who have survived childhood in all countries can expect to live past 50 years of age. Even in the world’s poorest countries those who survive the diseases of infancy and childhood have a very good chance of living to be grandparents. This suggests that the number of older people in developing countries will more than double over the next quarter century reaching 850 million by 2025 that is 12 per cent of their total population. By 2050 the proportion of older people is expected to increase to 20 percent. (excerpt)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".