What if subordinates took care of managers’ mental health at work?
Bibliographic record
Abstract
Managers’ mental health is increasingly a subject of concern. However, organizational interventions to reduce stress and promote mental health do not target managers, but rather employees. Numerous studies report a link between supervisory behaviors and subordinates’ mental health at work, and suggest that developing managers’ behavior is a promising avenue in enhancing subordinates’ mental health at work. Nonetheless, the literature has neglected the role and behaviors of subordinates in the prevention of their managers’ mental health problems. This article presents the results of a qualitative research study that inventories 38 specific work practices (observable behaviors) of subordinates, grouped into 12 competencies. Managers and subordinates identified these work practices as affecting work environmental stressors and promoting managers’ mental health at work. The results also point to a major gap between the specific working practices cited by managers and those cited by subordinates, who generally report practices in a passive way. The theoretical and practical repercussions and implications for organizational intervention and human resource management are discussed.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".