“These Conversations Shouldn’t be Easy … You’re Going to Have to Shift. It Means Reflection … It Means Change”: Moving Anti-Oppression Beyond Incremental Changes in the GBV Sector
Bibliographic record
Abstract
Little is known about racialized women's work experiences in EDI/AO policy-led Canadian women's organizations in the gender-based violence (GBV) sector. Twenty-three racialized and white GBV workers participated in a critical qualitative study. Five themes emerged illustrating that racialized women workers are experiencing systemic violence through acts of racism and discrimination. The two themes examined in this paper: a culture of silence and shifting the needle forward reveal that the GBV sector is primarily an affirmative space. Creating greater safety for racialized women workers means moving toward transformative approaches that challenge the system's responsibility in creating and supporting anti-oppressive efforts in the elimination of violence.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.054 | 0.042 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".