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Record W1700113156 · doi:10.3138/cbmh.21.2.229

“They Gave Their Care, but We Gave Loving Care”: Defining and Defending Boundaries of Skill and Craft in the Nursing Service of a Manitoba Mental Hospital during the Great Depression

2004· article· en· W1700113156 on OpenAlexvenueaboutno aff
Chris Dooley

Bibliographic record

VenueCanadian Journal of Health History · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsCraftNursingService (business)General hospitalCredentialMental healthPsychologyMedicineFamily medicinePsychiatryPolitical scienceBusiness

Abstract

fetched live from OpenAlex

The School of Nursing at the Brandon Hospital for Mental Diseases was established in 1921 to equip the hospital with a corps of nurses equal to those found in urban general hospitals. While the school replicated the form of the general hospital training school, its credential was rejected by the national association of graduate nurses. Without the possibility of registration the mental nurses of the 1920s evolved a culture of resistance to the strictures of the training school, one which included affiliation with a trade union. Although still shut-out by the general nursing community, the nurses of the 1930s, arriving with a different sense of their occupational and social mobility, were more disposed to embrace the professional ideology of the training school. By invoking their superior ability to care and their learned capacity to function in the unpredictable environment of the mental hospital, they constructed mental nursing as a skilled craft based on proprietary knowledge, different from the work of both the general hospital nurse and the untrained ward attendant.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.720

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0640.051
Scholarly communication0.0110.004
Open science0.0030.012
Research integrity0.0050.014
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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.

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

Citations12
Published2004
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Health HistorySame topicCanadian Identity and HistoryFrench-language works237,207