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Canadian Military Nurse Deaths in the First World War

2017· article· en· W2559774247 on OpenAlexaffvenueabout
Dianne Dodd

Bibliographic record

VenueCanadian Journal of Health History · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsParks Canada
Fundersnot available
KeywordsMedicineSpanish Civil WarMilitary medicineHealth careFirst world warDemographyGerontologyFamily medicineNursingPsychiatryHistorySociologyPolitical scienceLawAncient history

Abstract

fetched live from OpenAlex

This paper examines the lives of sixty-one Canadian Nursing Sisters who served during the First World War, and whose deaths were attributed, more or less equally, to three categories: general illness, Spanish Influenza, and killed in action. The response by Canadian Army Medical Corps (CAMC) physicians to the loss of these early female officers who were, in fact, Canada's first female war casualties, suggests a gendered construction of illness at work in the CAMC. While nurses tried to prove themselves good soldiers, military physicians were quick to attribute their illnesses and deaths to horrific war conditions deemed unsuitable for women. This gendered response is particularly evident in how CAMC physicians invoked a causal role for neurasthenia or shell shock for the nurses' poor health. The health profile of these women also suggests that some of these deaths might have occurred had these women stayed in Canada, and it encourages future comparative research into death rates among physicians and orderlies.

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)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.910
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.290
Teacher spread0.262 · 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 designNot applicable
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

Citations1
Published2017
Admission routes3
Has abstractyes

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