Midwifery knowledge of equitable and culturally safe maternity care for Aboriginal women
Bibliographic record
Abstract
BACKGROUND: The Birthing on Noongar Boodjar project (NHMRC Partnership Project #GNT1076873) investigated Australian Aboriginal women and midwives' views of culturally safe care during childbearing. This paper reports on midwifery knowledge of Aboriginal women's cultural needs, their perceptions of health systems issues, and their ability to provide equitable and culturally safe care. METHOD: A qualitative study framed by an Indigenous methodology and methods which supported inductive, multilayered analyses and consensus-driven interpretations for two clinical midwife data groups (n = 61) drawn from a larger project data set (n = 145) comprising Aboriginal women and midwives. FINDINGS: Midwives demonstrated limited knowledge of Aboriginal women's cultural childbearing requirements, reported inadequate access to cultural education, substituted references to women-centered care in the absence of culturally relevant knowledge and consistently expressed racialized assumptions. Factors identified by midwives as likely to influence the midwifery workforce enabling them to provide culturally safe care for Aboriginal women included more professional development focused on improving understandings of cultural birth practices and health system changes which create safer maternal health care environments for Aboriginal women. CONCLUSIONS: Individual, workforce, and health systems issues impact midwives' capability to meet Aboriginal women's cultural needs. An imperative exists for effective cultural education and improved professional accountability regarding Aboriginal women's perinatal requirements and significant changes in health systems to embed culturally safe woman-centered care models as a means of addressing racism in health care.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".