Domestic Violence in Immigrant Communities: Case Studies (Spanish)
Bibliographic record
Abstract
This document contains excerpts from the book Domestic Violence in Immigrant Communities: Case Studies by Dr. Ferzana Chaze, Dr. Bethany Osborne, Ms. Archana Medhekar and Dr. Purnima George that have been translated into Spanish so that a wider audience can access them. The book is a freely accessible educational resource to be used in training with social work and legal practitioners. The translated case studies in this document are real life stories of immigrant women who have experienced domestic violence in Canada. The cases emerged from closed legal case files handled by Archana Medhekar Law Office and reflect the stories of racialized immigrant women who experienced domestic violence in Canada and who sought legal help. Permission to carry out this research was received from the Research Ethics Board of both Ryerson University and Sheridan College in June 2019. All cases included in this research took place within the past ten years and were closed for at least one year prior to the start of the research. In addition to the case studies, included are questions for discussion with community groups on the topic of domestic violence. We hope you will find this tool useful as you engage your communities on issues around domestic violence.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".