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Record W2120854311 · doi:10.2190/hs.39.3.g

Health Care Use and the Canadian Immigrant Population

2009· article· en· W2120854311 on OpenAlexafffundabout
K. Bruce Newbold

Bibliographic record

VenueInternational Journal of Health Services · 2009
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchMcMaster University
KeywordsImmigrationHealth careSocioeconomic statusForeign bornPopulationIncidence (geometry)MedicineEnvironmental healthDemographyGerontologyGeographyEconomic growthSociology

Abstract

fetched live from OpenAlex

Set within the "determinants of health" framework and drawing on Statistics Canada's longitudinal National Population Health Survey, this article explores health care utilization by Canada's immigrant population. Given the observed "healthy immigrant effect", whereby the health status of immigrants at the time of arrival is high but subsequently declines and converges toward that of the native-born population, does the incidence of use of health care facilities reflect greater need for care? Similarly, does the use of health care facilities by the native- and the foreign-born differ, and if so, are these differences explained primarily by socioeconomic, sociodemographic, or lifestyle factors, which may point to problems in the Canadian health care system? This study identifies trends in the incidence of physician and hospital use, the factors that contribute to health care use, and differences in health care use between the native- and foreign-born.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.355
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations82
Published2009
Admission routes3
Has abstractyes

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