Physical, Sexual, and Intimate Partner Violence Among Transgender and Gender-Diverse Individuals
Bibliographic record
Abstract
Importance: Transgender and gender-diverse (TGD) communities experience disproportionate levels of violence, yet due to limitations in measuring TGD identity, few state-representative estimates are available. Objective: To assess gender identity differences in experiences of violence among adults. Design, Setting, and Participants: Cross-sectional data from the 2023 California Violence Experiences (CalVEX) survey, weighted to provide state-representative estimates, was used to assess associations between gender identity and past-year experiences of violence among adults 18 years and older. Data were analyzed from June to December 2023. Exposure: Gender identity (cisgender women, cisgender men, transgender women, transgender men, and nonbinary individuals). Main Outcomes and Measures: Experience of physical violence (including physical abuse and threat or use of a weapon), sexual violence (verbal sexual harassment, homophobic or transphobic slurs, cyber and physically aggressive sexual harassment, and forced sex), and intimate partner violence (IPV; emotional, physical, or sexual violence) using age-adjusted logistic regression. Results: In total 3560 individuals (weighted cumulative response rate, 5%) completed the 2023 CalVEX survey, with 1978 cisgender women, 1431 cisgender men, 35 transgender women, 52 transgender men, and 64 nonbinary respondents (mean [SD] age, 47.1 [17.5] years; 635 [17%] were Asian, 839 [37%] were Hispanic, and 1159 [37%] were White). Past-year physical violence was reported by 22 transgender men (43%), 9 transgender women (24%), and 9 nonbinary respondents (14%). Past-year sexual violence was reported by 23 transgender men (42%), 11 transgender women (14%), and 31 nonbinary respondents (56%). Compared with cisgender women, transgender women and transgender men had greater risk of past-year physical violence (any form) (transgender women adjusted incidence rate ratio [AIRR], 6.7; 95% CI, 2.5-18.2; transgender men AIRR, 9.7; 95% CI, 5.3-17.7), as well as past-year IPV (any form) (transgender women AIRR, 3.2; 95% CI, 1.3-8.0; transgender men AIRR, 6.7; 95% CI, 4.0-11.3). Relative to cisgender women, transgender men (AIRR, 3.0; 95% CI, 1.7-5.1) and nonbinary respondents (AIRR, 3.3; 95% CI, 2.1-5.2) had greater risk of past-year sexual violence (any form). Conclusions and Relevance: In this survey study of adults in California, results showed that TGD individuals, especially transgender men, are at higher risk of experiencing all forms of violence relative to cisgender women. Results highlight the need for gender-affirming violence prevention and intervention services as well as policies that protect TGD individuals from discriminatory violence.
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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 | 0.001 | 0.001 |
| 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".