The Ngarrama Story: insights across the first 10 years of a midwifery service for First Nations women and families
Bibliographic record
Abstract
The Ngarrama midwifery group practice at the Royal Brisbane Women’s Hospital in 2012, after extensive community consultation, support, and intentional co-design process. Metro North Elders named the service ‘Ngarrama’ which means “Calling the protective forces, the Birth Spirit, which will protect the hopes, dreams and guardianship of our mothers and babies.” Ngarrama Maternity Services has grown, and collectively provided care for more than 3000 Aboriginal and / or Torres Strait Islander women and their babies over the past decade. A Ngarrama Elder has described the services as “Ngarrama Angels- as you are supporting our women and future generations by supporting traditional ways and importance of country”. This presentation will share the principles and model which the Ngarrama service is founded within and also clinical outcome data from the Ngarrama service, such as preterm birth, mode of birth and consumer perspective insight.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.033 | 0.017 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 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".