MétaCan
Menu
Back to cohort
Record W2104433153 · doi:10.1177/0022146510395027

The Impact of Generation and Country of Origin on the Mental Health of Children of Immigrants

2011· article· en· W2104433153 on OpenAlexaffabout
Shirin Montazer, Blair Wheaton

Bibliographic record

VenueJournal of Health and Social Behavior · 2011
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDisadvantageImmigrationMental healthPsychologyAdaptation (eye)Sample (material)Demographic economicsDevelopmental psychologyDemographyGeographySociologyPolitical scienceEconomicsPsychiatry

Abstract

fetched live from OpenAlex

The authors reexamine the study of generational differences in adjustment among the children of immigrants by arguing that the country of origin defines and shapes the adaptation process across generations. Using a sample of children in Toronto, the authors demonstrate that generational differences in the mental health of children occur only in families from countries of origin at the lowest levels of economic development. Among those at the lowest levels of economic development, a mental health advantage in the first generation evolves to a disadvantage in the 2.5 generation relative to third or later generational children. Children from backgrounds characterized by higher economic development show no initial or eventual differences from the native born. Using data from the Toronto Study of Intact Families, the authors are able to explain differences among children from low economic development backgrounds specifically in terms of increasing family conflict and decreasing school involvement across generations.

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)0.004
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 score0.055
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.002
Research integrity0.0000.001
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 head0.065
GPT teacher head0.398
Teacher spread0.334 · 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

Citations60
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Health and Social BehaviorSame topicMigration, Health and TraumaFrench-language works237,207