Prevalence of Abuse and Violence Before, During, and After Pregnancy in a National Sample of Canadian Women
Bibliographic record
Abstract
OBJECTIVES: We describe the prevalence of abuse before, during, and after pregnancy among a national population-based sample of Canadian new mothers. METHODS: We estimated prevalence, frequency, and timing of physical and sexual abuse, identified category of perpetrator, and examined the distribution of abuse by social and demographic characteristics in a weighted sample of 76,500 (unweighted sample = 6421) Canadian mothers interviewed postpartum for the Maternity Experiences Survey (2006-2007). RESULTS: Prevalence of any abuse in the 2 years before the interviews was 10.9% (6% before pregnancy only, 1.4% during pregnancy only, 1% postpartum only, and 2.5% in any combination of these times). The prevalence of any abuse was higher among low-income mothers (21.2%), lone mothers (35.3%), and Aboriginal mothers (30.6%). In 52% of the cases, abuse was perpetrated by an intimate partner. Receiving information on what to do was reported by 61% of the abused mothers. CONCLUSIONS: Large population-based studies on abuse around pregnancy can facilitate the identification of patterns of abuse and women at high risk for abuse. Before and after pregnancy may be particularly important times to monitor risk of abuse.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".