Violence Against Separated, Divorced, and Married Women in Canada, 2004
Bibliographic record
Abstract
The purpose of this study was to examine violence against separated, divorced, and married women using Statistics Canada's 2004 Statistics Canada. 2004. Divorces. The Daily, May 4: 1–5. [Google Scholar] General Social Survey. Based on a subsample of 6,716 heterosexual women (429 separated; 614 divorced; 5,673 married), available risk markers were examined in the context of a nested ecological framework. Consistent with past research, the results indicated that there may be differences in the dynamics of violence across the 3 groups. Separated women reported 7 times the prevalence of violence and divorced women reported twice the prevalence of violence than married women in the year prior to the study. Young age was an important predictor of violence for separated and divorced women. Unemployment and the presence of children of the ex-partner were important predictors for divorced women. Patriarchal domineering and sexually proprietary behaviors were strong predictors of violence for married women. The results suggested the possibility that motives for postseparation violence tend to differ depending on whether one is separated or divorced. Future research is warranted to uncover these potentially differing dynamics of risk.
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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 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".