TELEWORKING TO SUPPORT ACCOMMODATION, INCLUSION, AND HEALTH OF OLDER WORKERS: ISSUES FACED BY MANAGERS
Bibliographic record
Abstract
Abstract Telework is increasingly present and has the potential to be used as an accommodation modality to facilitate inclusion and healthy participation in the workplace for older workers (i.e. aged 55 and over). However, there is a need for a practical tool to guide the application of telework with this population. This poster presents the first stage of a study aiming to develop a reflective guide for applying telework to support the accommodation, inclusion, and health of older workers. Following a three-stage developmental research design, this first stage consists in conducting individual interviews with older teleworkers and managers to gather qualitative data on their experience. During the second stage, the issues, considerations, and good practices that emerged from the first stage are compiled into a guide. In the third stage, this guide will be validated by workers and managers to ensure its acceptability and applicability. Preliminary results from the first stage allowed to identify issues faced by managers concerning accommodation (n=8, e.g. ensuring that accommodating older workers does not add extra pressure on colleagues), inclusion (n=5, e.g. difficulty to mobilize older teleworkers for face-to-face social gatherings), and health (n=2, e.g. managers feel powerless to manage older teleworkers’ emotions). Managers play a key role in implementing practices that promote the accommodation and inclusion of older workers through teleworking, but they have few tools to support them. The reflective application guide that will be created during this study represents an innovative tool likely to have positive impacts at individual, organizational and societal levels.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".