Conclusions: The prospects for ageing labour forces
Bibliographic record
Abstract
Older workers have borne the brunt of industrialized nations' efforts to grapple with the effects of economic restructuring and population ageing. Although a trend towards early retirement has been a common feature of all the industrialized nations as industry restructured at the end of the twentieth century, the extent of this has varied markedly. This volume contains examples of where the participation of older workers declined, but not markedly so (Japan and the USA), and extreme examples of early exit (France, Germany and the Netherlands). But quickly, early retirement has been abandoned as its costs escalated, deficiencies were identified and new priorities associated with population ageing emerged. It is an unpalatable truth that many European governments in particular have been forced to accept that ageing populations and large scale early retirement are incompatible. Although early retirement is a tool that, it seems, industry defaults to, and while a period of almost a quarter of a century out of the workplace is attractive to many individuals, current thinking is that this is not tenable if industrialized economies are to remain competitive (European Commission, 2005a). The European Commission (2003) has estimated that an increase in the effective age of retirement of one year would reduce the expected increase in expenditure on public pensions by between 0.6 and 1 percentage points of GDP. The economic gains alone resulting from 'active ageing' could be enormous. However, there is some pessimism among authors in this volume, particularly those from countries where early exit went deepest, that active ageing is realizable, at least in the near future, and without the risk of hardship for older workers.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.075 | 0.024 |
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".