Teaching nursing history: The Santa Catarina, Brazil, experience
Bibliographic record
Abstract
Nursing history has been a much debated subject with a wide range of work from many countries discussing the profession's identity and questioning the nature of nursing and professional practice. Building upon a review of the recent developments in nursing history worldwide and on primary research that examined the structure of mandated nursing history courses in 14 nursing schools in the state of Santa Catarina, Brazil, this paper analyzes both the content and the pedagogical style applied. We postulate that the study of history offers an important opportunity for the development of student learning, and propose that more creative and dynamic teaching strategies be applied. We argue the need for professors to be active historical researchers, so they may meaningfully contribute to the development of local histories and enrich the professional identities of both nursing students and the profession. We conclude that historical education in nursing is limited by a traditional and universalist approach to nursing history, by the lack of relevant local sources or examples, and by the failure of historical education to be used as a vehicle to provide students with the intellectual tools for the development of professional understanding and self-identity.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".