Identifying and dismantling racism in Australian perinatal settings: Reframing the narrative from a risk lens to intentionally prioritise connectedness and strengths in providing care to First Nations families
Bibliographic record
Abstract
INTRODUCTION: The perinatal period is a time when provision of responsive care offers a life course opportunity for positive change to improve health outcomes for mothers, infants and families. Australian perinatal systems carry the legacy of settler-colonialism, manifesting in racist events and interactions that First Nations parents encounter daily. OBJECTIVE: The dominance of a western risk lens, and conscious and unconscious bias in the child protection workforce, sustains disproportionately high numbers of First Nations infants being removed from their parents' care. Cascading medical interventions compound existing stressors and magnify health inequities for First Nations women. DESIGN: Critical discourse was informed by Indigenous ways of knowing, being and doing via targeted dialogue with a group of First Nations and non-Indigenous experts in Australian perinatal care who are co-authors on this paper. Dynamic discussion evolved from a series of yarning circles, supplemented by written exchanges and individual yarns as themes were consolidated. RESULTS: First Nations maternity services prioritise self-determination, partnership, strengths and communication and have demonstrated positive outcomes with, and high satisfaction from First Nations women. Mainstream perinatal settings could be significantly enhanced by embracing similar principles and models of care. CONCLUSIONS AND RELEVANCE: The Australian Anti-racism in Perinatal Practice (AAPP) Alliance calls for urgent transformations to Australian perinatal models of care whereby non-Indigenous health policy makers, managers and clinicians take a proactive role in identifying and redressing ethnocentrism, judgemental and culturally blind practices, reframing the risk narrative, embedding strength-based approaches and intentionally prioritising engagement and connectedness within service delivery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".