Canadian Men’s Experiences with Female-perpetrated Intimate Partner Violence: An Investigation of Masculinity and Help-seeking Behaviours
Bibliographic record
Abstract
There is substantial research attention on victimized women’s experiences with intimate partner violence (IPV), which has made great strides as a method of offering support and awareness to a vulnerable population. However, there remains a dearth in the literature with regard to research on men’s experiences as victims of female-perpetrated IPV. This study aimed to address this gap by examining men’s experiences as recipients of female perpetrated IPV. In the present study, 36 men from Canada, aged 22-50, took part in a survey that utilized open-ended questions to investigate the male IPV experience. Thematic analysis was used to analyze the men’s responses which revealed four key areas of discussion: (1) the extent and forms of IPV experienced, (2) men’s decisions on whether to stay in a relationship or leave, (3) men’s views of themselves, and (4) men’s help-seeking behaviours. The findings are in line with other IPV research indicating that men experience a variety of physical, verbal, and sexual abuse. Men reported that these experiences affected their views of themselves in a number of ways, including impacting their feelings of masculinity. When seeking help, men described using both formal and informal support systems to assist them with their IPV experiences. This research discusses past research on male survivors in Canada as well as internationally, followed by suggestions for future directions in the research on men’s experiences with IPV.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".