An exploration of safe and acceptable housing for racialized women who have experienced intimate partner violence within the housing crisis in Vancouver
Bibliographic record
Abstract
In the era of The Highway of Tears, the Missing and Murdered Girls and Women in the\nDowntown Eastside, stories like Tina Fontaine, and the #MeToo Movement, this research\nexplores the personal political stories of racialized women who have experienced intimate\npartner violence within the housing crisis in Vancouver. To capture racialized women’s voices of\nresilience, pain, growth, trauma, and over coming, this research uses Feminist Participatory\nAction and Photovoice methods. The purpose of this method was to illuminate authentic, and on\nthe ground knowledge. The findings from their narratives and courage that arose were conditions\nof unsafe and unacceptable housing after changing living situations, how the impact of violence\naffected their health, and how resilience and self-actualization grew from adversity. These\nfindings and discussion with the participants concluded that policies that address these issues\nneed to include action towards the perpetrators. Policies need to call out and make men\naccountable. Policies need to empower racialized women with just wages and employment,\nincreased stock of safe and acceptable housing, and appropriate treatment and resources for\nracialized women who have been abused.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.012 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".