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Record W2145501738 · doi:10.1111/dar.12250

Alcohol use among immigrants in <scp>O</scp>ntario, <scp>C</scp>anada

2015· article· en· W2145501738 on OpenAlexaffabout
Branka Agic, Robert E. Mann, Andrew Tuck, Anca Ialomiteanu, Susan J. Bondy, Laura Simich, G. Ilie

Bibliographic record

VenueDrug and Alcohol Review · 2015
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsSt. Michael's HospitalPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsEthnic groupResidenceImmigrationDemographyAlcoholMedicineAlcohol consumptionNative-BornAddictionEnvironmental healthGeographyPsychiatryPopulationChemistrySociology

Abstract

fetched live from OpenAlex

INTRODUCTION AND AIMS: This study examined prevalence of alcohol consumption among immigrants and the Canadian-born populations of Ontario by ethnic origin, and the association between ethnicity, country of birth, age at arrival, length of residence in Canada and drinking measures. DESIGN AND METHODS: Data were derived from the Centre for Addiction and Mental Health (CAMH) Monitor, a cross-sectional survey of Ontario adults, conducted between January 2005 and December 2010 (n = 13,557). RESULTS: The prevalence of alcohol consumption and risk drinking was generally lower among foreign-born than Canadian-born respondents, but significant variations across ethnic groups were found. In general, foreign-born respondents of European descent reported higher rates of alcohol use and risk drinking than foreign-born respondents from other ethnic groups. We also observed that ethnicity effects varied by whether or not respondents were born in Canada, and by the age at which they arrived in Canada. DISCUSSION AND CONCLUSIONS: While previous studies generally found an increase in immigrants' alcohol consumption with years in Canada, our data suggest that longer duration of residence may have either positive or negative effects on immigrants' alcohol use, depending on the country of origin/traditional drinking pattern. More research is needed to explore determinants of alcohol use and risk drinking among immigrants and to identify those groups at highest risk.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.058
GPT teacher head0.304
Teacher spread0.246 · 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.

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

Citations26
Published2015
Admission routes2
Has abstractyes

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