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Shifting boundaries: religion, medicine, nursing and domestic service in mid‐nineteenth‐century Britain

2009· article· en· W2146815041 on OpenAlexfundno aff
Carol Helmstadter

Bibliographic record

VenueNursing Inquiry · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsnot available
FundersAssociated Medical Services
KeywordsPoliticsGovernment (linguistics)Working classNursingProsopographyService (business)MedicineGender studiesSociologyPolitical scienceHistoryLawAncient history

Abstract

fetched live from OpenAlex

The boundaries between medicine, religion, nursing and domestic service were fluid in mid-nineteenth-century England. The traditional religious understanding of illness conflicted with the newer understanding of anatomically based disease, the Anglican sisters were drawing a line between professional nursing and the traditional role of nurses as domestic servants who looked after sick people as one of their many duties, and doctors were looking for more knowledgeable nurses who could carry out their orders competently. This prosopographical study of the over 200 women who served as government nurses during the Crimean War 1854-56 describes the status of nursing and provides a picture of the religious and social structure of Britain in the 1850s. It also illustrates how religious, political and social factors affected the development of the new nursing. The Crimean War nurses can be divided into four major groups: volunteer secular ladies, Roman Catholic nuns, Anglican sisters and working-class hospital nurses. Of these four groups I conclude that it was the experienced working-class nurses who had the greatest influence on the organization of the new nursing.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.063
GPT teacher head0.322
Teacher spread0.259 · 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 teacher head, not a consensus.

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

Citations3
Published2009
Admission routes1
Has abstractyes

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