Sexual violence in the lives of first-year university women in Canada: no improvements in the 21st century
Bibliographic record
Abstract
BACKGROUND: Summarizes the frequency, type, and context of sexual assault in a large sample of first-year university women at three Canadian universities. METHODS: As part of a randomized controlled trial assessing the efficacy of a sexual assault resistance education program, baseline data were collected from women between ages of 17 and 24 using computerized surveys. Participants' experience with sexual victimization since the age of 14 years was assessed using the Sexual Experiences Survey--Short Form Victimization (SES-SFV). RESULTS: Among 899 first-year university women (mean age = 18.5 years), 58.7% (95% CI: 55.4%, 62.0%) had experienced one or more forms of victimization since the age of 14 years, 35.0% (95% CI: 31.9%, 38.3%) had experienced at least one completed or attempted rape, and 23.5% (95% CI: 20.7%, 26.4%) had been raped. Among the 211 rape victims, 46.4% (95% CI: 39.7%, 53.2%) had experienced more than one type of assault (oral, vaginal, anal) in a single incident or across multiple incidents. More than three-quarters (79.6%; 95% CI: 74.2%, 85.1%) of the rapes occurred while women were incapacitated by alcohol or drugs. One-third (33.3%) of women had previous self-defence training, but few (4.0%) had previous sexual assault education. CONCLUSIONS: Findings from the first large Canadian study of university women since the 1990s indicate that a large proportion of women arrive on campuses with histories of sexual victimization, and they are generally unprepared for the perpetrators they may face during their academic years. There is an urgent need for effective rape prevention programs on university campuses. TRIAL REGISTRATION: ClinicalTrials.gov NCT01338428. Registered 13 April 2011.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".