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Record W4403404667 · doi:10.1177/02724316241288911

I Get by With a Little Help From My Friends: The Impact of a Gender-Tailored Group Mentoring Program on Peer Relationships

2024· article· en· W4403404667 on OpenAlexaffabout
Jessica Bouchard, Jennifer S. Wong

Bibliographic record

VenueThe Journal of Early Adolescence · 2024
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGroup (periodic table)PsychologyPeer groupPeer mentoringPeer effectsSocial psychologyPedagogy

Abstract

fetched live from OpenAlex

Adolescents face many difficulties when transitioning to high school, particularly when it comes to their social circles and maintaining friendships. As these challenges can have long-term consequences, providing support to youth during this period is essential. The YWCA Youth Education Programs (YEP) in Vancouver, BC offer group-based, after-school mentoring programs for 7 th grade students to help them navigate the transition to high school. Survey data from 668 students (233 treatment group and 435 control group) were used to examine the impacts of the YEP on friend support. Multilevel regression models show that the YEP is effective at improving perceptions of friend support in the long term. More research is needed to explore potential gender differences in the experience of supportive friendships after youth transition to high school, as well as the impact of group-based mentoring for youth transitioning to the high school environment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.053
GPT teacher head0.337
Teacher spread0.284 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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