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Record W4200056619 · doi:10.1177/00914150211065408

Physical Health of Older Canadians: Do Intersections Between Immigrant and Refugee Status, Racialized Status, and Socioeconomic Position Matter?

2021· article· en· W4200056619 on OpenAlexafffundabout
Alyssa McAlpine, Usha George, Karen Kobayashi, Esme Fuller‐Thomson

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2021
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of VictoriaToronto Metropolitan UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsImmigrationAcculturationSocioeconomic statusOddsHealth equityGerontologyDisadvantageDemographyPsychologyMedicineSociologyGeographyPublic healthLogistic regressionPopulationPolitical science

Abstract

fetched live from OpenAlex

It is unclear whether racial or nativity health disparities exist among older Canadians and what social and economic disadvantages may contribute to these differences. Secondary analysis of data collected from respondents aged 55 and older in the Canadian General Social Survey 27 was performed. The outcome variable was self-reported physical health. Compared to racialized immigrants, white immigrant and Canadian-born respondents had approximately 35% higher odds of good health. Among racialized older adults, the odds of good health were better if they were younger than 75, more affluent, better educated, had a confidant, had not experienced discrimination in the past five years, and were more acculturated. Racialized immigrants are at a health disadvantage compared to white groups in Canada; however, greater acculturation, social support, and lower experiences of discrimination contribute to better health among racialized older adults.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.369
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.330
Teacher spread0.315 · 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".

Quick stats

Citations10
Published2021
Admission routes3
Has abstractyes

Explore more

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