Arts-Informed Narrative Inquiry into nurse-teachers’ legacy for the next generation
Bibliographic record
Abstract
Fewer teachers are available globally for nursing education positions, a fact exacerbated by retirement of ageing colleagues. As two late career nurse-teachers, we use Arts-Informed Narrative Inquiry to explore experiences of Canadian contemporaries to discern the legacy we have to share with nurse-teachers who come after us. Narrative Inquiry is a research process that reconstructs personal and professional experience to reveal learning and knowledge construction in researchers and teachers. It involves lifelines, stories, metaphors, collage-making and reflective dialogue to reveal what experienced nurse-teachers have learned about teaching-learning over their professional trajectories. As an outcome of this study, we offer a letter to new teachers as a legacy arising from conceptualizing teaching-learning practice as humanness of care; the creative processes for self-directed, site-specific faculty development are transferable to any professional and geographical contexts. The paper illuminates how research, education and practice are mutually informing and how emergent inquiry approaches are significant for faculty and curriculum development, as well as transformation of practices.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.047 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".