Exposure to Intimate Partner Violence: Perceived Links with Other Victimizations and the Severity of Violence by Young Adults in Québec
Bibliographic record
Abstract
The objective of this qualitative study was to understand how young adults (18 - 25 years old) who were exposed to intimate partner violence (IPV) during childhood and adolescence explained the links between this violence and the other victimizations that they had experienced, as well as the perceived severity that they assigned to these victimizations. The participants (N = 45) were recruited in the Province of Quebec (Canada). Before the interview, they filled out an online questionnaire with the Adult Retrospective Version of the Juvenile Victimization Questionnaire as well as answering sociodemographic questions. They likewise noted the victimization to which they were subjected before they reached adulthood. These data helped us to better prepare the qualitative interviews, allowing us to explore the links the youth see or do not see between their exposure to IPV and other declared victimizations. Interviews lasted an average of two hours and were supported by a semi-structured interview guide and a life history calendar. The results show that many of the participants identified stronger links between exposure to IPV and child maltreatment, intimidation at school, and dating violence. Findings highlight the importance of considering youth’s viewpoints about the victimizations they suffer so as to develop intervention and prevention programs that are better adapted to these youth’s experiences and point of views.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".