Peer doula support training for Black and Indigenous groups in Nova Scotia, Canada: A community‐based qualitative study
Bibliographic record
Abstract
OBJECTIVES: The objectives of this qualitative study were to explore participant experiences of doula training programs offered by a prisoner health advocacy organization and Indigenous and Black community groups. DESIGN: This investigation employed a qualitative design. Recruitment was conducted through email. Interviews were conducted in Winter 2020. Data were analyzed using thematic analysis. SAMPLE: A total of 12 participants were recruited to participate in this study. Six participants identify as Black and six identify as Indigenous. All participants identify as women. MEASUREMENTS: Qualitative interviews were conducted using a semi-structured interview guide to elicit a breadth of information. RESULTS: Key themes included training experiences, training improvements and ''bridging the gap''. The training validated participants' experiences of birth and began to address the exclusion of Black and Indigenous people from birth work. However, participants expressed concerns about not being adequately positioned for sustained participation in birth work. CONCLUSIONS: Participants expressed receiving great value from the training programs. These trainings, which were fully subsidized, removed a financial barrier. However, these trainings do not address the exclusion of Black and Indigenous people from perinatal work or the lack or sustainable support systems for Black and Indigenous communities. This study makes several recommendations for future interventions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".