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The risks for adolescents of negatively biased self‐evaluations of social competence: The mediating role of social support

2014· article· en· W2091806376 on OpenAlexaff
Karine Bédard, Thérèse Bouffard, Pascal Pansu

Bibliographic record

VenueJournal of Adolescence · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologySocial competenceSocial anxietyDevelopmental psychologySocial supportAnxietyCompetence (human resources)Clinical psychologySocial psychologySocial changePsychiatry

Abstract

fetched live from OpenAlex

This study conducted among 544 adolescents (M = 15.1 years, SD = .82) examined whether perceived social support from parents and peers mediated the relationship between biased self-evaluations of social competence and internalizing problems. The results showed negative links between bias in self-evaluation and depressive symptoms, social anxiety and social avoidance. Bias in self-evaluation of social competence was more strongly related to perceived peer support than perceived parental support. Gender differences were observed in the mediating role of social support. Among boys, parental support was a partial mediator only of the link between bias in self-evaluation and depressive symptoms. While perceived peer support was a partial mediator of the links between bias in self-evaluation and depressive symptoms, social anxiety and social avoidance in girls, this was the case only for social avoidance in boys. These findings suggest that girls may show vulnerability to peer emotional support at an earlier age than boys.

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)0.006
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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 science0.0000.001
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 head0.036
GPT teacher head0.344
Teacher spread0.308 · 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

Citations39
Published2014
Admission routes1
Has abstractyes

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