Work-based learning: a leadership development example from an action research study of shared governance implementation
Bibliographic record
Abstract
AIM: An empowering action research study was undertaken to evaluate and strengthen the implementation of shared governance. One aim was to identify factors that acted as aids or barriers to effective decision-making by clinical leaders. As a work-based learning approach, action research was expected to lead to integration of learning into practice by researcher and participants alike. BACKGROUND: Shared governance replaces traditional hierarchies and requires and develops clinical leaders. Strategies are needed to maximize learning from introduction of such initiatives at the individual, group and organizational level. METHODS: Participant-observations and interviews were undertaken with shared governance council members from one model in north-west England. RESULTS: Leadership skills and knowledge and shared governance practices were significantly enhanced. Preparation for council roles was considered inadequate. Increased structured time for reflection and action planning was indicated. CONCLUSIONS: Implementation of shared governance has succeeded in developing leadership capacity. Evaluation findings have led to improvements in the overall shared governance model. Action research has been found to have great utility at optimizing work-based learning. Nurse Managers need to develop their coaching and facilitating skills and recognize there is no "quick fix" for developing clinical leaders. Implications include the need to support learners in identifying and implementing changes arising from work-based learning activities, the significant resource implications and the need to optimize the organizational climate if work-based learning approaches to leadership and management development are to succeed.
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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 | 0.002 | 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 | 0.001 |
| 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".