Putting reflective practice into action: A case study
Bibliographic record
Abstract
The McGill University Health Centre Reflective Practice Program, which began in 2003, provides a theory and structure for reflection and is the basis of an ongoing professional development program for nurses in leadership positions. It is designed to improve their knowledge and skills, and to provide support to nurse leaders who are continually facing difficult interpersonal situations involving staff, patients, families and the interdisciplinary team. It is based on a well-developed theoretical framework, a theory-of-action approach to reflective practice (RP). This approach is described in some detail, together with the training program for RP facilitators. This RP program involves regular monthly small group meetings to discuss challenging interpersonal situations. To date, 37 facilitators have been trained and currently about 120 nurses are participating regularly in RP groups. To illustrate this approach a detailed example of a typical RP session is presented, together with some illustrative feedback data collected over several years. We conclude with recommendations for implementing this type of RP program and describe how our theoretical approach has spread beyond the nursing department and has been introduced to some students and faculty in the School of Nursing and to interprofessional staff in one of the clinical groupings.
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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 | 0.032 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.021 | 0.015 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".