Canadian Adolescents’ Experiences of Dating Violence: Associations with Social Power Imbalances
Bibliographic record
Abstract
A substantial minority of adolescents experience and use dating violence in their sexual and/or romantic relationships. Limited attention has been paid to exploring theory-driven questions about use and experience of adolescent dating violence (ADV), restricting knowledge about promising prevention targets for diverse groups of youth. To address this gap, this paper investigates whether factors tied to power imbalances (bullying, risk of social marginalization) are associated with patterns of ADV victimization and perpetration in a large sample of Canadian mid-adolescents. We used data from the 2017/2018 Health-Behavior in School-Aged Children (HBSC) study, a nationally representative sample of Canadian youth. Our study was comprised of adolescents who were in grades 9 or 10, and who had dated in the past 12 months (N = 3779). We assessed multiple forms of ADV and bullying victimization and perpetration. We also included six variables assessing adolescents' risk of social marginalization: gender, race/ethnicity, immigration status, family structure, food insecurity, and family affluence. We used latent class analysis to explore the ways adolescents experience and use different forms of ADV, and then examined whether factors tied to power imbalances (bullying, social marginalization) were associated with classes of ADV. Three ADV classes emerged in our sample: uninvolved (65.7%), psychological and cyber victimization only (28.9%), and mutual violence (5.4%). Bullying was most strongly associated with the mutual violence class, suggesting a transformation of power from peer to romantic contexts. Social marginalization variables were associated with ADV patterns in different ways, highlighting the need to use a critical and anti-oppressive lens in ADV research and prevention initiatives.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".