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Record W1991528477 · doi:10.1037/a0017413

Links between friendship relations and early adolescents’ trajectories of depressed mood.

2010· article· en· W1991528477 on OpenAlexafffund
Mara Brendgen, Véronique Lamarche, Brigitte Wanner, Frank Vitaro

Bibliographic record

VenueDevelopmental Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsResearch Unit on Children's Psychosocial MaladjustmentUniversité de MontréalUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyFriendshipMoodDepressed moodDevelopmental psychologyLongitudinal studyLate childhoodDepression (economics)Clinical psychologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

The present study examined to what extent different types of friendship experiences (i.e., friendlessness, having depressed friends, and having nondepressed friends) are associated with early adolescents' longitudinal trajectories of depressed mood. On the basis of a sample of 201 youths (108 girls, 93 boys), we identified 3 distinct longitudinal profiles of depressed mood from Grade 5 (age 11) through Grade 7 (age 13): one group with consistently low levels of depressed mood, another group showing a sharp increase in depressed mood from late childhood through early adolescence, and a 3rd group with consistently high levels of depressed mood from late childhood through early adolescence. Subsequent analyses revealed that, compared to friendless youths, youths with nondepressed friends showed less elevated trajectories of depressed mood, whereas youths with depressed friends showed more elevated trajectories. The theoretical and practical implications of these findings are discussed.

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)0.003
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.024
GPT teacher head0.299
Teacher spread0.275 · 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

Citations57
Published2010
Admission routes2
Has abstractyes

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