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Record W2020468567 · doi:10.1155/2011/813270

The Nurse in the University: A History of University Education for South African Nurses: A Case Study of the University of the Witwatersrand

2011· article· en· W2020468567 on OpenAlexaff
Simonne Horwitz

Bibliographic record

VenueNursing Research and Practice · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsProfessionalizationNurse educationWork (physics)NursingUniversity educationService (business)SociologyHigher educationMedicineMedical educationPolitical scienceSocial scienceEngineering

Abstract

fetched live from OpenAlex

This paper charts the history and debates surrounding the introduction of academic, university-based training of nurses in South Africa. This was a process that was drawn out over five decades, beginning in the late 1930s. For nurses, university training was an important part of a process of professionalization; however, for other members of the medical community, nursing was seen as being linked to women's service work. Using the case-study of the University of the Witwatersrand, one of South Africa's premier universities and the place in the country to offer a university-based nursing program, we argue that an historical understanding of the ways in which nursing education was integrated into the university system tells us a great deal about the professionalization of nursing. This paper also recognises, for the first time, the pioneers of this important process.

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)0.004
metaresearch head score (Gemma)0.014
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 score0.043
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0380.015
Scholarly communication0.0090.010
Open science0.0020.008
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.176
GPT teacher head0.423
Teacher spread0.247 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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