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Record W2810442827 · doi:10.1177/2329496518780922

Economic Development of Origin-countries, Life-stage at Immigration, and Length of Residence Effects on Psychological Distress

2018· article· en· W2810442827 on OpenAlexfundaboutno aff
Shirin Montazer

Bibliographic record

VenueSocial Currents · 2018
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchSocial Science Research Council
KeywordsImmigrationResidenceStressorDistressPsychological distressMental healthDemographyDemographic economicsPsychologyGeographySociologyEconomicsClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

This article reexamines the healthy immigrant effect in mental health—as measured by psychological distress—by incorporating the modifying roles of the level of economic development of origin-country and life-stage at arrival among a sample of immigrants to Toronto, Canada—as compared to the native-born. The analytic sample included 2,157 adults, of which 31 percent were immigrants. Multivariate results point to a healthy immigrant effect in distress, but only among immigrants from less developed origin-countries who migrated to Canada in mid-adulthood (between 25 and 34 years of age). Further, this health advantage deteriorates with increase in length of residence only among this group of migrants, in large part because of an increase in chronic stressors. Immigrants from more developed origin-countries do not experience a healthy immigrant effect, as compared to the native-born, nor an increase in distress with tenure in Canada, irrespective of the life-stage at immigration.

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)0.003
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 score0.265
Threshold uncertainty score0.526

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.039
GPT teacher head0.383
Teacher spread0.344 · 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

Citations7
Published2018
Admission routes2
Has abstractyes

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