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Record W4404319767 · doi:10.1371/journal.pmen.0000113

Navigating (gendered) social worlds: A qualitative exploration of Canadian young people’s social relationships and mental health

2024· article· en· W4404319767 on OpenAlexafffundabout
Stephanie Wadge, Valerie Steeves, Kelly A. Pilato, Valerie Michaelson

Bibliographic record

VenuePLOS mental health. · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsUniversity of OttawaBrock University
FundersCanadian Institutes of Health ResearchBrock University
KeywordsMental healthQualitative researchSocial worldsSociologyPsychologyGender studiesSocial psychologyPsychotherapistSocial science

Abstract

fetched live from OpenAlex

The purpose of this qualitative study was to explore the gendered ways that youth in Canada are navigating their social relationships, and in turn, how this may be shaping their mental health experiences. Twenty young people between the ages of 11 and 17 (nine self-identified as girls, ten self-identified as boys, and one self-identified as non-binary) were recruited from across Canada and each participated in a virtual individual semi-structured interview. Social relationships were reported as highly important by all participants, and study findings illuminated the strong, persistent, and often implicit ways that these relationships are shaped by gender. This includes the ways that youth describe gender and social relationships influencing experiences and behaviours; how youth manage conflict; and the dissatisfaction that girls express regarding gendered stereotypes, expectations, and norms that they perceive their boy and non-binary peers to experience. Study findings provide context to understanding the gendered disparities that disadvantage all young people. Along with providing new evidence, this paper is a call to action to the adult duty bearers in society to lead changes in how young people are socialized so that they are better equipped to navigate relationships and conflict in positive and healthy ways.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.169
GPT teacher head0.442
Teacher spread0.274 · 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 teacher head, not a consensus.

Study designQualitative
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 routes3
Has abstractyes

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