MétaCan
Menu
Back to cohort
Record W2140414896 · doi:10.2105/ajph.2010.196519

Epidemiology and Health Care Reform: The National Health Survey of 1935-1936

2011· article· en· W2140414896 on OpenAlex
George Weisz

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Public Health · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and modern epidemiology studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPovertyPublic healthHealth careEpidemiologyPopulationMedicineDepression (economics)Falling (accident)Survey data collectionWelfareEnvironmental healthDiseaseGerontologyEconomic growthPolitical scienceNursing

Abstract

fetched live from OpenAlex

The National Health Survey undertaken in 1935 and 1936 was the largest morbidity survey until that time. It was also the first national survey to focus on chronic disease and disability. The decision to conduct a survey of this magnitude was part of the larger strategy to reform health care in the United States. The focus on morbidity allowed reformers to argue that the health status of Americans was poor, despite falling mortality rates that suggested the opposite. The focus on chronic disease morbidity proved to be an especially effective way of demonstrating the poor health of the population and the strong links between poverty and illness. The survey, undertaken by a small group of reform-minded epidemiologists led by Edgar Sydenstricker, was made possible by the close interaction during the Depression of agencies and actors in the public health and social welfare sectors, a collaboration which produced new ways of thinking about disease burdens.

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.

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)0.045
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0450.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.476
GPT teacher head0.478
Teacher spread0.002 · 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