Implementation of a participatory management model: analysis from a political perspective
Bibliographic record
Abstract
AIM: To analyse experiences of managers and nursing staff in the implementation of participatory management, specifically processes of decision-making, communication and power in a Canadian hospital. BACKGROUND: Implementing a Participatory Management Model involves change because it is focused on the needs of patients and encourages decentralisation of power and shared decisions. METHODS: The study design is qualitative using observational sessions and content analysis for data analysis. We used Bolman and Deal's four-frame theoretical framework to interpret our findings. RESULTS: Participatory management led to advances in care, because it allowed for more dialogue and shared decision making. However, the biggest challenge has been that all major changes are still being decided centrally by the provincial executive board. CONCLUSIONS: Managers and directors are facing difficulties related to this change process, such as the resistance to change by some employees and limited input to decision-making affecting their areas of responsibility; however, they and their teams are working to utilise the values and principles underlying participatory management in their daily work practices. IMPLICATIONS FOR NURSING MANAGEMENT: Innovative management models encourage accountability, increased motivation and satisfaction of nursing staff, and improve the quality of care.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".