Anti-oppression as praxis in the research field: Implementing emancipatory approaches for researchers and community partners
Bibliographic record
Abstract
Equity, diversity, and inclusion (EDI) and anti-oppression (AO) policies are implemented in research to address intersecting systemic barriers for marginalized populations. Grant applications now include questions about EDI to ensure researchers have considered how research designs perpetuate discriminatory practices. However, complying with these measures may not mean that researchers have engaged with AO as praxis. Three central points emerged from our work as a women's research collective committed to embedding AO practices within the research methodology of our community-based study. First, research ideas must be connected to larger pursuits of AO in and across marginalized communities. Secondly, AO as praxis in the research design is an exercise in centering cultural knowledge and pragmatic research preparation and response that honours the collective. Lastly, AO approaches are not prescriptive. They must shift, adapt, and change based on the research project and team, creating space for transformative resistance and emancipation of racialized researchers and community workers.
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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 | 0.520 | 0.321 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.039 | 0.104 |
| Scholarly communication | 0.038 | 0.037 |
| Open science | 0.008 | 0.073 |
| Research integrity | 0.009 | 0.018 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".