Public Organizational Culture’s Association With Quality of Working Life: The Mediating Role of Satisfaction With HRM Practices
Bibliographic record
Abstract
Drawing on the Culture-Work-Health model, this research aims to determine public organizational culture profiles and assess the mediating role of HRM satisfaction in the relationship between public cultures and quality of working life (QWL). To achieve these objectives, a content analysis of the value statements of 26 public organizations in Quebec (Canada) was carried out, and an online survey of 784 public servants working in these organizations was conducted. The coupling of qualitative and quantitative data enabled cluster analyses and structural equation models to be performed. In Study 1, 51 public values were identified and grouped into seven categories. Cluster analysis revealed five public culture profiles: agile excellence, ethical benevolence, new public management (NPM), public interest protector , and sustainable benevolence . In Study 2, the associations between these profiles, satisfaction with HRM practices, and QWL were examined using the sample of civil servants. The results show that some types of public culture have a direct effect on QWL, while others have an indirect effect via satisfaction with HRM practices. In any case, public administrators should formulate their value statement with great interest since the articulation of the displayed values has significant implications for civil servants’ QWL.
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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 | 0.002 | 0.008 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".