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Record W2106191929 · doi:10.1080/01650250444000289

Change and stability in children’s social network and self-perceptions during transition from elementary to junior high school

2004· article· en· W2106191929 on OpenAlexaff
Stéphane Cantin, Michel Boivin

Bibliographic record

VenueInternational Journal of Behavioral Development · 2004
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPsychologyDevelopmental psychologyPerceptionCompetence (human resources)Social competenceSocial acceptancePreadolescenceSocial changePeer groupSocial psychology

Abstract

fetched live from OpenAlex

This study examined the changes in children’s social network and specific self-perceptions during the transition from elementary school to junior high school (JHS). The participants were 200 preadolescent children (104 girls, 96 boys). Children’s self-perceptions (global self-worth, perceived academic competence, and perceived social acceptance) and social network characteristics (parents and peer-enacted support) were evaluated four consecutive times over a 2-year period. Despite a slight decrease in the size of children’s social network after the transition, the passage into JHS had no negative impact on the quality and functional aspects of their relationships with parents and school friends. The school transition was instead associated with an intensification of supportive relationships with school friends. Children’s perceived social acceptance also increased suddenly after the JHS transition, while children’s perceived scholastic competence decreased simultaneously during that time. Children’s general self-esteem was then observed to decline progressively over a longer period of time.

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)0.002
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.298
Teacher spread0.271 · 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

Citations143
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Behavioral DevelopmentSame topicChild and Adolescent Psychosocial and Emotional DevelopmentFrench-language works237,207