The impact of leadership on employee presenteeism: A comparison between police and non-police samples
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Leader support is an essential factor influencing worker health and stress. Police officers are part of a class of workers who must deal with a high level of stress. Significant stress can lead to the onset of symptoms of psychological distress, which can lead to presenteeism (employees are present but suffer from mental health symptoms). However, we note that few studies focus on police leadership and job-related-stress presenteeism. Therefore, the current research is relevant and aims to demonstrate the link between the leadership style (Multifactor Leadership Questionnaire) on presenteeism (Job-Stress-Related Presenteeism measure) for police and non-police samples. A total of 252 employees, police officers (municipal organization) and blue-collar workers (public organization) completed the questionnaires. The results indicated that, for both samples, transformational leadership did not significantly influence job-stress presenteeism. Laissez-faire leadership had a strong negative effect on police and non-police employees’ job-related stress presenteeism scores. Finally, a transactional leadership style predicted higher levels of job-related-stress presenteeism for our non-police (blue-collar) sample; it did not significantly influence job-stress-related presenteeism for our police sample. These results highlight the importance of leadership style on employee well-being, and the implications of these results are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it