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Record W2108163104 · doi:10.1177/0022219412436977

Friendship Predictors of Global Self-Worth and Domain-Specific Self-Concepts in University Students With and Without Learning Disability

2012· article· en· W2108163104 on OpenAlexaff
Michal Shany, Judith Wiener, Michal Assido

Bibliographic record

VenueJournal of Learning Disabilities · 2012
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFriendshipPsychologyLearning disabilitySelf-conceptDevelopmental psychologySocial psychologyPerceptionInterpersonal relationship

Abstract

fetched live from OpenAlex

This study investigated the association among friendship, global self-worth, and domain-specific self-concepts in 102 university students with and without learning disabilities (LD). Students with LD reported lower global self-worth and academic self-concept than students without LD, and this difference was greater for women. Students with LD also reported that they had more stable friendships than students without LD. Students with LD were more likely to have higher global self-worth and self-perceptions of social acceptance if they had stable friendships and had relationships where they communicated spontaneously and frankly. None of the friendship variables predicted academic self-concept. Thus, having stable and intimate friendships is a protective factor in relation to global self-worth and social self-concept in university students with LD.

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)0.004
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.276
Teacher spread0.264 · 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

Citations49
Published2012
Admission routes1
Has abstractyes

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