ISKWEW: EMPOWERING VICTIMS OF WIFE ABUSE
Bibliographic record
Abstract
recently described family violence as a senous problem, with high costs to individuals, families, and society as a whole (Canada 1988). Family violence has come to be broadly defined and includes the abuse of wives, children, youths and the elderly. Women's groups have been very successful in creating public awareness of wife and child abuse and, as a result, public concern about family violence has increased significaotly in receDt years. There is growing recognition that family violence is an unacceptable behaviour which has serious social and criminal consequences for Canadians, and for our society (Canada 1988). The prevalence of abuse of Canadian women is a national tragedy. In May 1982, the Canadian House of Commons officially accepted that one out of every ten Canadian women tS battered by her hu band (Macleod 1987: 3). The proportion of Canadian Native women who are abused is estimated to be as bigh as seven out of ten in some communities (W. Jamieson 1987: 6). The term, wife abuse, is the commonly used descriptive phrase, but IOciudes abuse of girlfriend, partner, former wife, and so on. The problems of abused women and theIr children do not end after the crisis phase of the abuse cycle. Family violence cycles are usually repeated many times in the lives of these women. Despite a growing realization among professionals who are concerned with family violence, and who feel it is tlme to move attention beyond the crisis phase of physical family violence, this awareness has not been reflected in budget allocations for follow-
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".