MétaCan
Menu
Back to cohort
Record W2550233919

General hospital nursing in Sheffield during the early years of the NHS, 1948-1974.

2006· dissertation· en· W2550233919 on OpenAlexaboutno aff
Judith Hilary Redman

Bibliographic record

VenueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · 2006
Typedissertation
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsnot available
Fundersnot available
KeywordsNursingQuarter (Canadian coin)General hospitalMedicineWork (physics)Health careService (business)BusinessFamily medicinePolitical scienceGeographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

This study examines the history of general hospital nursing in Sheffield between approximately 1948 and 1974 – the first 26 years of the operation of the National Health Service (NHS) in England. The availability of nurses in quantity and in quality, their knowledge and skills, working practices and organisation, are themes that endured during this quarter-century. This was a period when administrative and therapeutic innovation was juxtaposed with – and constrained by – resource limitations. In particular, the inability to match nursing availability to patient needs caused operational and strategic problems in developing and delivering hospital-based health care. These problems were exacerbated when innovations in nursing and medical care required new approaches to the organisation of hospital beds and equipment, which also had to be implemented in nineteenth century buildings with inadequate basic facilities. Making extensive use of archived records of Sheffield’s hospitals, the present study explores how the coalescence of these factors influenced nurses and their work, and how this contributed to continuity and change in nursing in the city’s general hospitals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.005
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.011
GPT teacher head0.236
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)Same topicHistorical Psychiatry and Medical PracticesFrench-language works237,207