The global prevalence of sexual assault: A systematic review of international research since 2010.
Bibliographic record
Abstract
OBJECTIVE: We present a review of peer-reviewed English-language studies conducted outside the United States and Canada on the prevalence of sexual assault victimization in adolescence and adulthood published since 2010. METHOD: A systematic literature search yielded 32 articles reporting on 45 studies from 29 countries. Studies that only provided prevalence estimates for sexual assault in intimate relationships or did not present separate rates for men and women were excluded. All studies were coded by two coders, and a risk of bias score was calculated for each study. Both past-year and prevalence rates covering longer periods were extracted. RESULTS: =6 each). One study came from the Middle East and no studies were found from Oceania. Across the 22 studies that reported past-year prevalence rates, figures ranged from 0% to 59.2% for women, 0.3% to 55.5% for men, and 1.5% to 18.2% for LGBT samples. The average risk of bias score was 5.7 out of 10. Studies varied widely in methodology. CONCLUSION: Despite regional variation, most studies indicate that sexual assault is widespread. More sustained, systematic, and coordinated research efforts are needed to gauge the scale of sexual assault in different parts of the world and to develop prevention measures.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".