Experiences of Physical and Psychological Violence Against Male Victims in Canada: A Qualitative Study
Bibliographic record
Abstract
The concept of intimate partner violence (IPV) implies gender-neutrality in the experiences of violence. Gender symmetry in IPV implies similar numbers of men and women victims. Data from the 2014 Canadian General Social Survey (Victimization) indicate that 262,267 men and 159,829 women were victims of self-reported spousal violence over the past 5 years. Despite the prevailing notion that IPV predominantly affects female victims, these data suggest that men too are victims of IPV, especially in heterosexual relationships. However, very few qualitative studies have shed light on heterosexual male victims' experiences of IPV. This article describes some of these experiences and also seeks to understand the effects of IPV on male victims. Qualitative data collected through semi-structured interviews with 16 male victims of IPV were used to explore their experience of physical IPV and psychological IPV, as well as the consequences of such abuse. Results revealed common themes pertaining to the type of abuses (i.e., physical, controlling and threatening behaviours, and verbal abuse) male victims experienced and the subsequent physical and psychological impacts. This study identifies the need to distinguish between physically and psychologically abused male victims of IPV.
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 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.029 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".