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Record W4388491426 · doi:10.1177/02724316231212559

Low Peer Acceptance and Classroom Engagement: The Protective Role of Elementary School Teacher-Student Relationships for Immigrant-Background Students

2023· article· en· W4388491426 on OpenAlexafffund
Isabelle Archambault, Sophie Lampron‐de Souza, Catherine Lamanque-Bélanger, Sophie Pascal, Linda S. Pagani, Véronique Dupéré

Bibliographic record

VenueThe Journal of Early Adolescence · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsClosenessPsychologyStudent engagementImmigrationAssociation (psychology)Multilevel modelIntervention (counseling)Diversity (politics)Developmental psychologySocial psychologyMathematics education

Abstract

fetched live from OpenAlex

The increasing cultural diversity in host society schools highlights the need to better understand the conditions supporting the integration of students with an immigrant background. This study examines whether peer acceptance enhances the association between student-teacher relationship closeness and classroom emotional engagement, and whether this association is moderated by student immigrant status. This study followed 251 fifth- and sixth-grade first- (34.3%), second- (49.4%), or third-generation-plus (16.3%) students across two school years (46.6% boys). Measures included child-reported classroom emotional engagement, student-teacher relationships, peer acceptance, and immigrant status. Using a hierarchical multiple linear regression model, this study demonstrates that positive relationships with teachers represent a protective factor for classroom emotional engagement among students who do not feel accepted by classmates, but only for first-generation students ( b = .46, p < .001). Our results underscore the importance of developing intervention strategies for building student-teacher relationships to benefit the classroom integration of first-generation students.

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)0.007
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 score0.091
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.072
GPT teacher head0.374
Teacher spread0.302 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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