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Record W2070017124 · doi:10.1258/1355819053559074

Health status and health care of immigrants in Canada: a longitudinal analysis

2005· article· en· W2070017124 on OpenAlexafffundabout
K. Bruce Newbold

Bibliographic record

VenueJournal of Health Services Research & Policy · 2005
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsImmigrationHealth carePopulationMedicineGerontologyDemographyEnvironmental healthGeographyEconomic growthSociology

Abstract

fetched live from OpenAlex

OBJECTIVES: This paper focuses upon health status, need for care, and use of health care from 1994/95 to 2000/01 in the Canadian foreign-born population. METHODS: Using Statistics Canada's longitudinal National Population Health Survey, descriptive and survival analyses are used to explore immigrant health status and health care. RESULTS: The health status of immigrants quickly declines after arrival, with a concomitant increase in use of health care services. However, survival analysis of the risk of a change to poor health indicates no difference between immigrants and the native-born. Similarly, there is no difference in the risk of hospital use between the two populations. CONCLUSIONS: The health status of recent immigrant arrivals is observed to decline towards that of the native-born population, while health care utilization increases. However, increased use may not be sufficient to offset declines in health, meaning that need for health care within the immigrant population may be unmet.

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 score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.062
GPT teacher head0.482
Teacher spread0.420 · 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

Citations137
Published2005
Admission routes3
Has abstractyes

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