Factors associated with suspected drug-facilitated sexual assault
Bibliographic record
Abstract
BACKGROUND: There has been little systematic investigation of widespread reports of drugging and sexual assault. We sought to determine the prevalence of and factors associated with suspected drug-facilitated sexual assault. METHODS: Between June 2005 and March 2007, a total of 977 consecutive sexual assault victims underwent screening for suspected drugging at 7 hospital-based sexual assault treatment centres. We defined victims of drug-facilitated sexual assault as those who presented to a centre within about 72 hours of being assaulted and who provided at least 1 valid reason for suspecting that she or he had been drugged and sexually assaulted. We used logistic regression modelling to compare victims of suspected drug-facilitated sexual assault with other sexual assault victims, controlling for covariates. RESULTS: In total, 882 victims were eligible for inclusion in the study. Of these, 855 (96.9%) were women, and 184 (20.9%) met the criteria for suspected drug-facilitated sexual assault. Compared with other victims, victims of drug-facilitated sexual assault were more likely to have presented to a large urban centre for care (odds ratio [OR] 2.31, 95% confidence interval [CI] 1.47-3.65), to be employed (OR 1.92, 95% CI 1.34-2.76), to have consumed over-the-counter medications (OR 3.97, 95% CI 2.47-6.38) and street drugs (OR 1.71, 95% CI 1.12-2.62) in the 72 hours before being examined and to have used alcohol before the assault (OR 4.00, 95% CI 2.53-6.32). INTERPRETATION: Suspected drug-facilitated sexual assault is a common problem. Sexual assault services should be tailored to meet the needs of those experiencing this type of victimization.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".