Bibliographic record
Abstract
The ageing of the population has led policy-makers to put a high priority on extending working life. However, little attention has been paid to creating the conditions to enable people to work beyond retirement age. Traditional views about older workers still shape the attitudes of many employers. Our survey of the work aspirations of the over 50s, and the barriers facing them, reveals that many assumptions made about this age group are wrong: (1) the majority of workers over 50 (62 per cent of women and 59 per cent of men) want to continue working beyond state pension age; (2) more than twice as many (11 per cent) over 50s want promotion as want to downshift (four per cent); (3) instead of being unfit to work due to ageing and ill health, 62 per cent describe themselves as feeling as fit as ever, with structural and attitudinal barriers thwarting their ability to stay involved; (4) enthusiasm for learning persists: 44 per cent of 56-59 year-olds and a third of 60-64 year-olds have undertaken training in the past three years, and 21 per cent of the over 50s had trained to improve their job prospects; (5) responsibility for children continues, with nearly one-quarter of 56-59 year-olds and nine per cent of 70-75 year-olds still supporting their children financially; (6) working longer is not a burden borne purely out of necessity: those who have elected to work longer are happy and enjoying what they do; and (7) there is significant demand for greater flexibility in hours and location of work. Sixty-eight per cent of the over 50s unemployed below state pension age and 85 per cent of people inactive and over state pension age said that greater availability of flexible and part-time work would help them to find jobs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".