Bibliographic record
Abstract
This paper analyzes the etiology of wife abuse using the Violence Against Women Survey conducted by Statistics Canada. Two major theoretical models are compared. The power theory developed by Murray Straus and his colleagues focuses on power imbalance in the family. The major argument is that the family is a system which responds to broad social-structural conditions that produce stress and conflict Low-income families, families in which the husband has a low-status occupation, and 228 families in which one or more adults are unemployed are characterized by high levels of stress. When stress is mediated by a personal history of aggressive socialization, and if social support mechanisms are lacking, violence is legitimized as a means of coping. Feminist theory focusses on the ideology of familial patriarchy, which supposedly teaches men how and when to use violent techniques, and structured gender inequality on a societal level which disadvantages women relative to men in terms of their economic, legal, educational, and other options. The data indicate that a culture of male dominance is central to the etiology of wife abuse but that it is an insufficient explanation. Men who have a father who is abusive to his wife, who have been unemployed, who are married common-law, and who have a low family income are significantly more likely to adhere to a familial ideology of patriarchy. Previous experience with violence also has a direct effect on the likelihood of being abused. A theory which incorporates gender inequality along with other sources of power provides a better explanation for who is most likely to be abusive.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.020 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".