Raising Awareness and Appreciation: Employee Perspectives on Disability Management in Swiss Companies
Bibliographic record
Abstract
Abstract In Western countries, an increasing number of companies has difficulties with recruiting and retaining employees, along with growing employer responsibilities in the workplace. Therefore, companies’ interest in disability management programs has increased. This article examines employee perspectives of disability management and how it is related to job satisfaction, physical and mental health, workplace morale and sickness absence. Employees from seven Swiss companies (N=482), from the private and public sector, participated in either an online and paper-and-pencil survey for this present study. The survey asked employees to report their views of how disability management is related to job satisfaction, mental health, physical health, workplace morale and absenteeism. The Swiss employees participating in the study knew about disability management and related programs, which are implemented in their company. They valued them as moderately helpful for a variety of factors related to workplace wellbeing, and regarded the programs generally as high quality and wanted them to continue, because they contribute to job satisfaction, mental health, physical health, workplace morale and reduced sickness absence. However, employees also saw more value in disability prevention (DP) and stay at work (SAW) programs than in return to work (RTW) programs. Male employees and those working for public organisations saw more benefit in disability management programs than female employees and those working in the private sector.
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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 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".