Culturally Safe(r) Trauma Services for Indigenous and Black Women Identifying Mainstream Barriers and Facilitators to Healing
Bibliographic record
Abstract
Indigenous and Black women continue to be overrepresented as the victims of sexual violence, yet are least likely to access legal or medical services due to the inherent systemic barriers present in contemporary systems. The objective of this paper is to encourage service providers to recognize the systemic barriers that are innate within Canada's socio-political systems, along with, how Euro-centrism maintains their status quo based on oppression. My research will identify the barriers, along with make recommendations in how to support Black and Indigenous women healing. I have utilized community action-based research methods to ensure that it is the women's voices are heard regarding their re-victimization by service providers. My interviews were with women who had accessed social services for their victimization in order to identify the barriers they encountered and not to exploit or sensationalize their stories. The data gathered from my work with service providers provided insight into their understanding of the intersectionality that shapes gender based violence. The women I worked were clear in identifying the systemic barriers in place. They also made clear recommendations on what is required for plausibility of healing to occur in mainstream settings.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".