The impact of flexible work arrangements on an older grieving population
Bibliographic record
Abstract
Purpose Age-inclusive management practices are crucial for addressing the needs of the older workforce, but there is limited research on these practices. One underexplored area is how workplaces can support older employees dealing with the loss of a loved one. The psychological process of loss differs for older employees and can have adverse effects on their ability to perform in the workplace. The purpose of this paper is to explore how workplaces can provide the necessary tools to support their older grieving employees. Design/methodology/approach This conceptual paper draws on the job-demand resource model and signaling theory to investigate how flexible work arrangements can support older employees after a bereavement and contribute to optimal employee performance. Findings Flexible work arrangements are theorized to lead to optimal performance via informational support. An ethical climate and stronger cultural competencies are proposed to strengthen this relationship. A theoretical framework is presented for a comprehensive research approach. Originality/value This paper advances the current understanding of age-inclusive management and offers a novel perspective on the benefits of flexible working arrangements.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".