A challenging little balance: How white doulas with mainstream training understand and engage with anti-oppressive practice
Bibliographic record
Abstract
Though the benefits of doula care in reducing birth inequities and mitigating obstetric violence are well established, little is known about how White doulas from mainstream training programs (most doulas in Canada) understand and implement anti-oppressive practice (AOP) in different sociocultural contexts. Guided by interpretative phenomenological analysis, we conducted life history and semi-structured interviews with five White doulas working in Western Canada. The doulas described varying levels of engagement, confidence, and effectiveness across three distinct levels of sociopolitical interaction: relationships with birthing families (micro level), supporting clients within biomedical institutions (meso level), and advocating for enhanced maternal care within the broader structural landscape (macro level). Differences in AOP across these three sociopolitical contexts and between doulas were connected to various factors, including mainstream doula training, healthcare politics, professional structures, local histories, and individual preferences and circumstances. Implications for mainstream doula education, interprofessional collaboration, and hospital birthing practices are discussed.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".