Military-related sexual assault in Canada: a cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Most research on military-related sexual assault is based on the United States military and has important limitations, such as low response rates. We sought to estimate the lifetime prevalence of sexual assault, assess its relation to military service and identify the circumstances, correlates and associations with mental disorders of military-related sexual assault among Canadian military personnel. METHODS: = 67 776), as per Statistics Canada requirements. We assessed lifetime trauma exposure and past-year mental disorders using the Composite International Diagnostic Interview. We defined lifetime military-related sexual assault as forced sexual activity or unwanted sexual touching that occurred on deployment or in another military workplace, or was perpetrated by Department of National Defence or Canadian Armed Forces personnel. We defined all other sexual assault as non-military-related sexual assault. RESULTS: Self-reported sexual assault was more prevalent among women (non-military-related sexual assault 24.2%, military-related sexual assault 15.5%) than men (5.9% and 0.8%, respectively). About a quarter of women with military-related sexual assault reported experiencing at least 1 event on deployment. After covariates were controlled for, military-related sexual assault was independently associated with any lifetime and any past-year mental disorder (adjusted odds ratio 2.9 and 3.0, respectively) and lifetime and past-year posttraumatic stress disorder (adjusted odds ratio 4.3 and 4.1, respectively). INTERPRETATION: Canadian military women are at increased risk for sexual assault and military-related sexual assault relative to their male counterparts. Deployment may be a period of elevated risk for military-related sexual assault, and women who reported military-related sexual assault are more likely to have experienced mental disorders, especially posttraumatic stress disorder.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".