Mediating Factors Explaining the Association Between Sexual Minority Status and Dating Violence
Bibliographic record
Abstract
Dating violence presents a serious threat for individual health and well-being. A growing body of literature suggests that starting in adolescence, individuals with sexual minority identities (e.g., individuals who identify as gay, lesbian, or bisexual) may be at an increased risk for dating violence compared with heterosexuals. Research has not, however, identified the mechanisms that explain this vulnerability. Using a diverse sample of young adults ( n = 2,474), the current study explored how minority stress theory, revictimization theory, sex of sexual partners, and risky sexual behavior explained differences in dating violence between sexual minority and heterosexual young adults. Initial analyses suggested higher rates of dating violence among individuals who identified as bisexual, and individuals who identified as gay or lesbian when compared with heterosexuals, and further found that these associations failed to differ across gender. When mediating and control variables were included in the analyses, however, the association between both sexual minority identities and higher levels of dating violence became nonsignificant. Of particular interest was the role of discrimination, which mediated the association between bisexual identity and dating violence. Other factors, including sex and number of sexual partners, alcohol use, and childhood maltreatment, were associated with higher rates of dating violence but did not significantly explain vulnerability among sexual minority individuals compared with their heterosexual peers. These findings suggest the importance of minority stress theory in explaining vulnerability to dating violence victimization among bisexuals in particular, and generally support the importance of sexual-minority specific variables in understanding risk for dating violence within this vulnerable population.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".