Navigating (gendered) social worlds: A qualitative exploration of Canadian young people’s social relationships and mental health
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.031 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".