Bibliographic record
Abstract
Little has been written about nursing in the period 1870-1960 within the geographical boundaries and surrounding areas of Halifax and Huddersfield. This thesis aims to explore the development of nursing within these towns. The focus is on general nurses in hospital and community roles. Rosenberg’s eight areas of importance were used allowing the construction of an historical analysis of both nursing and nurses locally. Archival sources were found in twenty-five main archives and twelve of these were investigated further. Primary documents belonging to local retired nurses such as personal documents, photographs and memorabilia were included. In total 1493 individual items were subjected to documentary analysis. The second stage of data collection involved conducting oral history interviews to capture memories and experiences of local retired nurses. A total of 373 named nurses were identified, sixty-eight contacted, forty-four agreed to participate and twenty-one were interviewed. A life story approach recorded their personal lives and nursing careers. This approach required the ethical issues of biographical research methods and interviewing to be addressed. Interviews were recorded on audio tape and transcribed ready to be deposited in the University of Huddersfield archives. Data was subjected to analysis using NVivo computer software and Rosenberg’s eight areas of importance used as a priori themes. Nursing in these two provincial towns changed during the ninety years under study often in response to local or national issues such as professional registration. Nurse education occurred in all but the early years and developed alongside the increasing specialization of nurses and as each nursing branch emerged. Nurses in West Yorkshire were subject to particular local issues such as its geography, environment and industrial heritage. The merits of this research are it provides a unique account of the local development of nursing adding to the professions history and presenting implications for present day practice.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".