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Record W4284709698 · doi:10.1177/02724316221113349

Pathways From Prosocial Behaviour to Emotional Health and Academic Achievement in Early Adolescence

2022· article· en· W4284709698 on OpenAlexaffabout
Eva Oberle, Xuejun Ryan Ji, Tonje M. Molyneux

Bibliographic record

VenueThe Journal of Early Adolescence · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsLearning PartnershipUniversity of British Columbia
FundersSpencer Foundation
KeywordsProsocial behaviorPsychologyDevelopmental psychologyPsychological interventionAcademic achievementAssociation (psychology)OptimismPeer acceptanceCompetence (human resources)Peer groupSocial psychology

Abstract

fetched live from OpenAlex

This study examined pathways from prosocial behaviour in the beginning of the school year to emotional health and academic achievement in the end of the year, taking into account the mediating role of peer acceptance. Participants were 734 grade 4 to 7 students in public elementary schools (51% female) in Western Canada. As expected, pathway analyses taking into account the clustered structure of the data indicated that self-reported prosocial behaviour in the beginning of the school year was significantly related higher levels of self-reported optimism, lower levels of depressive symptoms, and better grades in the end of the year; the association was mediated by peer-reported peer acceptance in the classroom. Findings support the role of peer acceptance as an underlying mechanism involved in the association between prosocial behaviour and positive developmental health outcomes in early adolescence. Findings are also practically relevant as they inform school-based social-emotional competence promotion through interventions.

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)0.002
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 score0.107
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.038
GPT teacher head0.313
Teacher spread0.274 · 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

Citations35
Published2022
Admission routes2
Has abstractyes

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