Well-being at work from a multilevel perspective: what is the role of personality traits?
Bibliographic record
Abstract
Purpose It is of great importance for organizations to identify what can influence employees’ well-being. The theoretical model that the authors propose combines psychological and social determinants of stress at work. The purpose of this paper is to evaluate the contribution of work organization conditions, personality traits and their interaction to well-being in a sample of Canadian workers and companies. Design/methodology/approach Multilevel regression analyses were performed on a sample of 1,957 workers employed in 63 Quebec firms. Work organization conditions included (skill utilization, decision authority, psychological demands, physical demands, job insecurity, irregular schedule, number of working hours, social support from colleagues and supervisors, job promotion, and recognition) and personality traits included (self-esteem, locus of control and Big Five). Findings Work organization conditions (psychological demands, number of hours worked and job insecurity) and personality (self-esteem, locus of control, extraversion, neuroticism and conscientiousness) were significantly associated with well-being. The results of the analysis show that none of the personality traits included in this study interacts with work organization conditions to explain workers’ level of well-being. Originality/value This study provides support for the implementation of human resource management (HRM) practices in order to diminish the presence of stressful working conditions as well as for the eventual development of training programs designed to raise personality traits.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".