Women and Gendered Violence in Canada: An Intersectional Approach
Bibliographic record
Abstract
"Violence against women is usually framed as an issue of interpersonal violence perpetuated by men. While domestic violence and sexual assault are significant social problems, such a narrow framing obscures the diversity of women's experience, fails to illuminate the role social structures play, and excludes discussions of labour site and state violence. By drawing on a range of theoretical traditions emerging from feminism, criminology, and sociology, Women and Gendered Violence in Canada expands the conversation of violence against women to critically examine violence as conditioned by the political, cultural, economic, and social reality of women collectively and individually. The book contains 12 chapters organized into 4 sections. The first section develops the conceptual and contextual framework that informs the remainder of the text, and the following three sections are organized around types of victimization: interpersonal, labour site, and state. Although the book's main focus is Canadian society, the conclusion broadens this focus by exploring how Canadian women are complicit in the victimization and exploitation of women in less privileged parts of the world. Each chapter ends with lists of suggested activities and further readings, and textboxes with first person narratives are used throughout the text to personalize the material and issues being examined."--
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.025 | 0.013 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".