No Access to Services: The Struggle of Injection Drug Using Women in Abusive Relationships
Bibliographic record
Abstract
Women who experience violence and are at risk for HIV/AIDS are a multiply marginalized population which the majority of service providers ignore or feel they do not have the resources to deal with. Furthermore, while the Canadian government issues reports on violence against women, it does not provide an analysis of the intersection between violence HIV/AIDS. Women who are at risk for HIV due to injection drug use are particularly vulnerable when in a violent relationship; most women’s shelters have zero tolerance policies for substance use leaving these women isolated. By examining how substance use increases HIV risk for women who experience violence, the high risk behaviors associated with violence, and the high risk behaviors associated with substance use, multiply marginalized women’s needs become clearer. Service providers for multiply marginalized women must always consider the ramifications of their policies, as well as the ideologies that their policies are based on so that they can effectively help their target population. To address the needs of multiply marginalized women, drastic changes need to be made to the current shelter system: shelters need to examine their ideological foundation and analyze what stigmas their current policies support. Coordinated efforts are needed between multiple service providers to address the challenges that these often forgotten women face.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.022 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".