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Record W3195667686 · doi:10.1177/08295735211039944

Which Anxiety Symptoms are Associated with Perceived Ethnic Discrimination in Adolescents With an Immigrant Background?

2021· article· en· W3195667686 on OpenAlexafffundabout
Sophie St-Pierre, Kristel Tardif‐Grenier, Aude Villatte

Bibliographic record

VenueCanadian Journal of School Psychology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsUniversité du Québec en Outaouais
FundersFonds de Recherche du Québec-Société et Culture
KeywordsAnxietyEthnic groupPsychologyClinical psychologyContext (archaeology)PanicMental healthAssociation (psychology)ImmigrationIntervention (counseling)PsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

This study assesses the specific anxiety symptoms that are present in the context of perceived ethnic discrimination in 696 (M age = 13.3, σ = .77, 57% girls) seventh and eighth-grade students with immigrant backgrounds from four different Canadian high schools. Multiple hierarchical linear regressions were conducted to determine the association between perceived ethnic discrimination and specific anxiety symptoms. Results demonstrate that perceived ethnic discrimination is significantly associated with more anxiety symptoms, such as panic/somatic, generalized anxiety, social phobia, and school phobia. Findings provide a better understanding of the association between perceived ethnic discrimination and anxiety symptoms reported by adolescents with an immigrant background. These findings could help school-based mental health professionals in the implementation of prevention and intervention measures aimed at reducing specific anxiety symptoms that are often present in the context of perceived ethnic discrimination.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.372
Teacher spread0.309 · 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

Citations8
Published2021
Admission routes3
Has abstractyes

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Same venueCanadian Journal of School PsychologySame topicRacial and Ethnic Identity ResearchFrench-language works237,207