Nursing Ethics in the United Kingdom, 1888 to the 1960s (with a Nod to Canada)
Bibliographic record
Abstract
Early nursing leaders had a prodigious written output in letters, articles, curricular standards, books, alumnae newsletters, and more. The degree of interchange and exchange between and among nursing leaders internationally is astonishing, even by today’s standards. They shared freely across national journals in ways that display shared concerns, values and sentiments. While the UK journals devote a considerable amount of attention to concerns for registration, title protection, educational standardization, and so forth, the content of concern in this chapter is that which is specifically ethical in nature. The paged journal review and content analysis of the early nursing journals ( The Nursing Record , British Journal of Nursing , The Nursing Times ) from their inception, and the UK ethics textbooks, indicate several persisting, large domains of ethical concern and themes in UK nursing that are explored in this chapter.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".