Aging, Economic Insecurity, and Employment: Which Measures Would Encourage Older Workers to Stay Longer in the Labour Market?
Bibliographic record
Abstract
In the present context of aging populations, the question of how to support older workers who want to stay in employment longer is of particular importance, especially from a social justice perspective with regards to income. The challenges faced by organizations and governments are unprecedented. Interesting conclusions can be drawn from our research with regard to these challenges. First of all, the perception of retirement appears more or less unchanged over the years and remains very positive. Consequently, one of the barriers to the employment of older workers may be the image of retirement itself, since it is still perceived as a gift or a right. Secondly, our results confirm that forcing people to stay longer in the labour market is a largely unpopular measure. Consequently, if public retirement plans offer limited income, governments and organizations should adopt a more voluntary approach to encourage older workers to stay in employment longer for a better income. Our results highlight the importance of the sector and type of job in the measures or incentives that could encourage older workers to stay in employment longer. Consequently, governments and organizations will probably have to adopt a contingent approach; i.e., all incentives do not necessarily fit all jobs or all sectors and social justice would require this be taken into account. We identified three sets of measures that could encourage older workers to stay in employment longer, and thus have access to better economic security: the reduction of working time, the flexibility of working time, and the individualization of retirement options and working time. The progressive reduction of their working time appears most interesting to our respondents. These measures appear to favour social justice in terms of income and right to employment at the end of active careers.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".