Bibliographic record
Abstract
Narrative Inquiry is a research methodology that we adapted over the past two decades from Canadian higher education and curriculum studies to nursing research, education, and health-care practice. The Narrative Inquiry we use originated from Connelly and Clandinin in the 1990s, and rests on John Dewey's philosophy that experience is relational, temporal, and situational, and as such, if intentionally explored, has the potential to be educational. More specifically, it is only when experience is reflected upon and reconstructed that it has the potential to reveal the construction of identity, knowledge, and the humanness of care. Congruent with the expectation that nurses are reflective practitioners and knowledge-makers, Narrative Inquiry provides a means to enhance, not only quality of care, but quality of experience of those in our care: in education, our students, and in practice, our patients. In this article, we explicate how Narrative Inquiry may be lived in health-care education and practice, with a primary focus on nursing. We illuminate how we support our graduate students, the next generation of narrative inquirers, through a Narrative Inquiry Works-in-Progress group.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".