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Record W2890564363 · doi:10.23889/ijpds.v3i4.720

Social Class and Hospitalization in Canada

2018· article· en· W2890564363 on OpenAlexaffabout
Jenny Godley, Karen Tang, William A. Ghali

Bibliographic record

VenueInternational Journal for Population Data Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCensusOperationalizationSocial classRecord linkageDemographyPopulationHealth careMedicineGeographyEnvironmental healthEconomic growthSociologyPolitical science

Abstract

fetched live from OpenAlex

IntroductionDespite the existence of a universal health care system in Canada, there remains an inverse relationship between social class and health (Frohlich 2006). Those who identify as lower social class (operationalized with various indicators, including education, income, and occupation) have poorer outcomes across multiple health measures (Tang 2016).
 Objectives and ApproachThis study examines the link between social class and health care utilization, specifically hospitalization, in Canada. First, we examine the relationship between different indicators of social class and rates of hospitalization; next, we look at cause-specific hospitalizations. Using the unique dataset that contains the linked data for the 2006 Census with the Discharge Abstract Database for 2006-9, we explore the following research questions:
 
 Are the three main indicators of social class, education, income, and occupation, individually correlated with hospitalization rates overall, controlling for age and gender?
 Are certain indicators of social class more highly correlated with hospitalization rates, controlling for other indicators?
 
 ResultsWe access the linked files provided by Statistics Canada in the Prairie Research Data Centre. The long-form Census represents approximately 20\% of the Canadian population. The DAD includes data on hospitalizations in acute care facilities in Canada, with the exception of those in the province of Quebec. Approximately 4,650,000 long-form respondents were eligible for linkage to the DAD, and approximately 5.3\% of Census respondents were linked to at least one DAD record between 2006 and 2009. Our analyses are ongoing, but initial results suggest an inverse relationship between hospitalization and various measures of social class. Full results will be made available for presentation following vetting by Statistics Canada personnel.
 Conclusion/ImplicationsThis data provides us with a unique opportunity to examine the relationship between the detailed and rich measures of social class collected in the long-form Census and the comprehensive hospitalization data provided by the DAD records. Results will have implications for hospital health care provision across Canada.

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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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.074
GPT teacher head0.447
Teacher spread0.372 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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