How do midwives learn about, understand, and integrate Cultural Safety into their care of First Nations women and families? A qualitative exploration
Bibliographic record
Abstract
PROBLEM: Midwives are required to provide care based on Cultural Safety for First Nations women and families. Recent literature has suggested that midwives' understanding of Cultural Safety and how it translates into their practice differs widely. This disparity requires further exploration. BACKGROUND: The Australian professional midwifery codes and standards state that there is a requirement to provide care based on Cultural Safety. It is critical to understand how First Nations people's history and culture impacts their health and wellbeing, requiring midwives to recognise how this may impact care. AIM: To determine Australian midwives' knowledge and understanding of Cultural Safety and how this translates into their practice when caring for First Nations women and families. METHODS: A qualitative study was undertaken. Data were collected via semi-structured interviews with 12 midwives practicing in Australia. Data were transcribed and thematically analysed. FINDINGS: Three themes were identified: 'Society and Systems', 'Knowingness versus Understanding', and 'Personal Qualities, Engagement and Partnerships' which highlight the strengths and deficits of Cultural Safety education and its integration into midwifery practice in Australia. DISCUSSION: Health systems providing maternity care remain rooted in Western biomedical philosophies, which influences the practice of Cultural Safety at all levels. Midwives are beginning to understand the ongoing impact of colonisation on the health and wellbeing of First Nations families, but still face challenges when striving to provide culturally safe care. CONCLUSION: Cultural Safety must be valued at an organisational level, in which midwives can engage in authentic, maternity-based educational programs led by suitably prepared educators.
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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 | 0.026 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".