Gay men and intimate partner violence: a gender analysis
Bibliographic record
Abstract
Though intimate partner violence (IPV) is predominately understood as a women's health issue most often emerging within heterosexual relationships, there is increasing recognition of the existence of male victims of IPV. In this qualitative study we explored connections between masculinities and IPV among gay men. The findings show how recognising IPV was based on an array of participant experiences, including the emotional, physical and sexual abuse inflicted by their partner, which in turn led to three processes. Normalising and concealing violence referred to the participants' complicity in accepting violence as part of their relationship and their reluctance to disclose that they were victims of IPV. Realising a way out included the participants' understandings that the triggers for, and patterns of, IPV would best be quelled by leaving the relationship. Nurturing recovery detailed the strategies employed by participants to mend and sustain their wellbeing in the aftermath of leaving an abusive relationship. In terms of masculinities and men's health research, the findings reveal the limits of idealising hegemonic masculinities and gender relations as heterosexual, while highlighting a plurality of gay masculinities and the need for IPV support services that bridge the divide between male and female as well as between homosexual and heterosexual.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".