Exploring The Continuum: Sexualized Violence by Men And Male Youth Against Women And Girls
Bibliographic record
Abstract
In this paper, the continuum of violence against women is explored through numerous news media reports. After a review of social learning, cultural violence and feminist theories on violence against women, the paper concentrates on the climate of misogyny and increased risk of violence, as manifested in the rise in sexual harassment, terrorism in relation to abortion seekers and providers, and intimate femicide, in both the United States and Canada. R E S U M E Dans cet article le continuum de la violence envers les femmes est explore par l'entremise de nombreux rapports de nouvelles. Apres un bilan de l'apprentissage social, de la violence culturelle et les theories feministes sur la violence envers les femmes, cet article se concentre sur le climat de misogynie et le risque croissant de violence, tel que manifeste par la hausse de harcelement sexuel, le terrorismc envers les personnes qui veulent avoir un avortement et ceux qui les dispensent, et le femicide intime, aux Etats-Unis et au Canada. In the last few decades, interest in violence against women has been on the rise. Whether one reads or watches the news media, or scrolls down popular or academic journals or books, coverage of violence against women abound. Two recent
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".