103 Staying at work while ageing: barriers and facilitators for workers over 55 years of age
Bibliographic record
Abstract
Introduction While ageing workers (AWs) (≥55 years) constitute a growing portion of the labour force, they tend to be absent for health reasons more often than other workers. However, implementing mechanisms that facilitate their staying at work implies first understanding the contributing factors and dynamics. Methods A multimethod approach was used, combining a literature review and a series of group discussions with stakeholders in work disability. First, a rapid review of mixed studies (qualitative, quantitative, mixed) was carried out between 2006 and 2016 using main databases (e.g.: CINAHL, PsycInfo, Sociological Index). We identified 30 articles on AWs and various causes of disability, then analysed the article content using a predefined extraction grid. Four focus groups representing various stakeholders (n=35) concerned by the ageing of workers in Quebec, Canada, were formed (insurers, employers, unions, health professionals). The discussions were transcribed and content analysis was performed. Results Combined results revealed that the relationship between ageing and the likelihood of staying at work is largely influenced by the interactions between workers’ personal systems and the organisation’s (workplace) system. The gap between workers’ representations, capacities and resources, on the one hand, and employers’ expectations and requirements and the conditions they provide, on the other, significantly impacts the likelihood of AWs staying at work. Discussion The likelihood of AWs staying at work appears closely linked to the workplace’s dynamic capacity to take into account their specific health conditions and needs. This presupposes, however, recognition of AWs’ added value, in a market characterised by ever-growing concern with maximising performance. The actions associated with the different systems (e.g. compensation and healthcare systems) also need to be harmonised to maximise the stay-at-work potential of this segment of the labour force.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".