Community-Based Doula Training: A Promising Practice for Improving Black Maternal Health
Bibliographic record
Abstract
Introduction: This paper presents findings from an evaluation of the novel community-based Black Postpartum Doula Training pilot project in Regent Park, Toronto. Rooted in the urgent need to address health care disparities and improve maternal outcomes, this initiative seeks to empower Black women to become doulas, health care leaders, and advocates within their own communities. Methods: Analysis of training participant interviews revealed several key themes. This pilot contributes to the growing body of evidence supporting the value of doula care in addressing health disparities, especially among marginalized communities. Results: It emphasizes the potential of targeted doula training programs as promising practices for promoting health equity in maternal care. These findings hold implications for future practice, highlighting the role of doulas in combating anti-Black racism and driving structural change in maternal health care. Conclusion: The paper underscores the significance of culturally competent care, advocacy, and self-care in enhancing maternal health outcomes and advancing health equity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".