Men’s differential identification with female-perpetrated intimate partner victimization
Bibliographic record
Abstract
Men are often reluctant to self-identify as victims of female-perpetrated intimate partner violence (f-IPV), despite significant harms. This reluctance results in underreporting of experiences and a concomitant lack of support and resources for male victims. We examined predictors of men’s differential self-identification as victims of f-IPV; that is, between men who self-identify both as having experienced and as being a victim of f-IPV (abuse and victim identified = AVI), men who self-identify as having experienced f-IPV, but not as being a victim of f-IPV (abuse-only identified = AI), and men who self-identify as neither having experienced nor being a victim of f-IPV, despite behaviourally having experienced it (non-abuse and non-victim identified = N-AVI). We recruited cisgender men (N = 212) to an online study examining experiences of f-IPV and identification with abuse. About two-thirds of our sample did not self-identify as victims of f-IPV despite reporting victimisation experiences. We found that frequency of f-IPV, psychological vulnerability from f-IPV, precarious manhood beliefs, and ambivalent sexism significantly predicted men’s self-identification as victims of f-IPV. We elucidate predictors of men’s reluctance to self-identify as victims of f-IPV, allowing for the identification of men who may be less likely to seek and obtain support.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".