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Record W2037719798 · doi:10.1353/bhm.2002.0016

Competent Professionals and Modern Methods: State Medicine in British Columbia during the 1930s

2002· article· en· W2037719798 on OpenAlexaboutno aff
Megan Davies

Bibliographic record

VenueBulletin of the history of medicine · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsRetrenchmentState (computer science)Government (linguistics)Public administrationPublic healthHealth careGreat DepressionEconomic growthPolitical scienceDepression (economics)MedicineLawNursingEconomics

Abstract

fetched live from OpenAlex

Little has been written about the formation of state medicine in early-twentieth-century Canada, particularly during the Depression era. Indeed, many historians and policy analysts have assumed that this was a time of stagnation and retrenchment in state health provision. To foster a more nuanced analysis of the formation of the Canadian medical state during the Depression decade, this article focuses on British Columbia and the public health initiatives brought in by the provincial Liberal government of T. D. Pattullo. In B.C., an energetic cadre of policymakers and bureaucrats sought to reform existing services by using professionally educated personnel, centralized administrative hierarchies, community education, and the surveillance of target health populations. Funding from the provincial government and the Rockefeller Foundation permitted considerable expansion in a range of public health sectors that included vital statistics, rural health centers, tuberculosis and venereal disease treatment schemes, and laboratory services. This article tells the story of this important period by bringing together details of the professional and personal lives of key individuals--the majority of whom were men--and exploring the new provincial health programs that were developed in B.C. during the interwar years.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.587
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.022
GPT teacher head0.253
Teacher spread0.231 · 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
GenreOther

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

Citations6
Published2002
Admission routes1
Has abstractyes

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