Authority and leadership: the evolution of nursing management in 19th century teaching hospitals
Bibliographic record
Abstract
AIM: This study shows why some 19th century nursing managers were successful and some were not. BACKGROUND: With the exception of Florence Nightingale, almost nothing has been written about 19th century nursing managers. METHOD: Classical historical method is used. Extensive use is made of secondary sources. Primary sources are found in the archives of the 12 London teaching hospitals, the Radcliffe Infirmary, the Convents of St John the Divine and the All Saints Sisters, and 16,000 Nightingale documents in the Collected Works of Florence Nightingale. RESULTS: Success in delivering a highly competent nursing service depended on the matron's leadership and legitimate authority but she also had to have the support of her hospital board to gain access to allocation of scarce resources. IMPLICATIONS FOR NURSING MANAGEMENT: While the 19th century hospital environment was very different, how nurses directed under different circumstances clarifies our knowledge of successful nursing management in 2007.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".