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Record W4400921908 · doi:10.1177/02724316241265457

Social Support Among Adolescents Across Immigrant Generations: A Mixed-Methods Study

2024· article· en· W4400921908 on OpenAlexafffundabout
Teodora Vigu, Kristel Tardif‐Grenier

Bibliographic record

VenueThe Journal of Early Adolescence · 2024
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversité du Québec en Outaouais
FundersSocial Sciences and Humanities Research Council of CanadaCentre de recherche universitaire sur les jeunes et les famillesUniversité du Québec en Outaouais
KeywordsImmigrationPsychologySociologyDevelopmental psychologyGeography

Abstract

fetched live from OpenAlex

The present mixed methods study explored perceived differences in social support across three immigrant generations of early adolescents residing in Canada. A total of 960 first-generation ( n = 249, M age = 13.02, σ = .69, 54.2% girls), second-generation ( n = 327, M age = 12.88, σ = .69, 57.5% girls) and third-plus-generation ( n = 384, M age = 12.81, σ = .69, 57.3% girls) early adolescent immigrants completed the self-reported Child and Adolescent Social Support Scale, and 16 of them participated in individual interviews on social support. Multivariate analyses of covariance (MANCOVA), in which we controlled for sex, mother tongue, and socioeconomic status (SES), showed that second-generation early adolescents perceived significantly less social support from their mother, teachers, school personnel, and classmates compared to their first- and/or third-plus-generation counterparts. Our mixed methods analysis revealed that these second-generation youth perceived several barriers to social support, such as an unsatisfactory quality of their relationships with these sources, a negative attitude from these sources, their limited availability or involvement, and their ineffectiveness in providing certain types of support. These findings highlight the importance of better understanding the unique challenges facing second-generation early adolescents in order to provide social support adapted to their needs.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.421
Teacher spread0.387 · 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

Citations1
Published2024
Admission routes3
Has abstractyes

Explore more

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