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Record W2591761643 · doi:10.1111/pere.12180

Seeking help from a female friend: Girls' competencies, friendship features, and intentions

2017· article· en· W2591761643 on OpenAlexaffabout
Heather A. Sears, SUSAN M. MCAFEE

Bibliographic record

VenuePersonal Relationships · 2017
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsFriendshipClosenessPsychologyGirlCompetence (human resources)Developmental psychologySocial psychologySelf-disclosureCoping (psychology)Help-seekingInterpersonal relationshipClinical psychologyMental health

Abstract

fetched live from OpenAlex

Abstract Adolescent girls frequently manage problems by seeking help from friends. We examined girls' intentions of seeking help from a female friend and whether these intentions were related to their competencies (emotional competence, self‐disclosure) directly and/or indirectly via specific friendship features (companionship, closeness). Participants included 222 Canadian girls (Grades 9–12) who completed an anonymous survey at school. Results showed that girls had high intentions of seeking help from a female friend and that higher self‐disclosure competence was linked directly to higher intentions. Both competencies were linked indirectly to higher intentions mediated by friendship features. These findings indicate that competencies make help seeking by girls from girls likely in multiple ways and suggest how coping programs can address help seeking in girl–girl friendships.

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 score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.071
GPT teacher head0.304
Teacher spread0.233 · 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

Citations6
Published2017
Admission routes2
Has abstractyes

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