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Record W2395002830 · doi:10.1108/ijmhsc-06-2014-0027

Access to and utilization of health care services among Canada’s immigrants

2016· article· en· W2395002830 on OpenAlexaffabout
Raaj Tiagi

Bibliographic record

VenueInternational Journal of Migration Health and Social Care · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsVancouver Community College
Fundersnot available
KeywordsImmigrationOriginalityMedicineHealth careDemographic economicsCommunity healthOrdered logitLogistic regressionDemographyGeographyNursingEconomic growthPsychologySociologyEconomicsPublic healthSocial psychology

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to analyze patterns of health services utilization – visits to family practitioner and visits to an emergency room – by recent immigrants (those who have lived in Canada for less than ten years) and “established” immigrants (those who have resided in Canada for ten years or longer) relative to their Canadian-born counterparts. Design/methodology/approach – The 2009/2010 files of the Canadian Community Health Survey were used for the analysis. A logit model was used to analyze utilization while a zero-inflated negative binomial model was used to measure the intensity of health services utilization. Findings – Results suggest that relative to native-born Canadians, recent immigrants are more likely to visit an emergency room and are less likely to visit a family/general practitioner. The opposite effect is observed for “established” immigrants. In terms of intensity of use, native-born Canadians are more likely to use physicians’ services intensively compared with either recent or established immigrants. Originality/value – The paper’s findings suggest that provincial governments in Canada will need to focus effort to ensure that recent immigrants have access to a family/general practitioner. This will be necessary given the recent primary care reform initiatives introduced across Canada that emphasize the physician as the first point-of-contact with the health system.

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)0.000
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 score0.018
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.341
Teacher spread0.283 · 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

Citations17
Published2016
Admission routes2
Has abstractyes

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