Un malaise flou en héritage : la construction du savoir infirmier enseigné au Québec
Bibliographic record
Abstract
Introduction : A discussion paper based on a teaching experience, and presenting a reflective viewpoint developed as part of the university nursing course Theory in Nursing.Context : A critical look at the historiography and reference works used in nursing courses.Objectives : To shed new light on the foundations of the nursing discipline by seeking to better integrate the participation of religious communities in the development of nursing knowledge.Method : Analysis of articles from Recherche en soins infirmiers and a reflective approach influenced by an interdisciplinary perspective linking nursing science, history, and the contribution of Pierre Bourdieu’s work.Results : Observation of the complete absence of contributions to nursing knowledge before Florence Nightingale (1820-1910) and of a century-long silence after her.Discussion : Analysis of the observed reflex to disavow the legacy of nursing sisters in Quebec through the analysis of three aspects : the Nightingalian episteme, the historiographical positioning of nurses and historians, and the construction of knowledge based on the experience of the Sisters of Providence at the Hôpital Saint-Jean-de-Dieu.Conclusion : By ignoring the Franco-Catholic origin of the scientific field of nursing, this disciplinary knowledge deprives itself of a powerful nursing model.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".