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Record W7095326694

Permission to reproduce is granted. Please acknowledge the Canadian Nurses Association.

2015· article· en· W7095326694 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationSocioeconomic statusHealth servicesPublic healthHierarchyOccupational safety and healthPosition (finance)State (computer science)
DOInot available

Abstract

fetched live from OpenAlex

What’s the issue? In all countries, it is well-established that poorer people have substantially shorter life expectancies and more illnesses than the rich. This phenomenon has been observed since at least the nineteenth century when Chadwick (1965) investigated the health of the working classes in Victorian England. Two contemporary British studies have been very influential in their documentation of the relationship between socioeconomic factors and health status. The Whitehall civil service study compared the health status of individuals over time with their position in a well-defined job hierarchy. Those lower in the hierarchy experienced three times the risk of death from heart disease, stroke, cancer, gastrointestinal disease, accident and suicide compared with those at the top of the hierarchy. These differences could not be explained by differences in medical care. The Secretary of State for Health in Britain was concerned about why – 30 years after the establishment of the National Health Service (which made health serves available to all, regardless of income) – significant differences in mortality between social classes persisted. The Black Report, released in 1980 (Townsend et al., 1992) concluded that these differences in health status were not the result of individual differences, but rather of structural differences in the way members of these different classes led their lives. This included a wide

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.350
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.054
GPT teacher head0.356
Teacher spread0.302 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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