Pediatric anesthesia in Australia and New Zealand and health inequity among First Nations and Māori children
Bibliographic record
Abstract
Australia and New Zealand are two countries in the Southern Pacific region. They share many pediatric anesthesia similarities in terms of medical organizational systems, education, training, and research, however there are important differences between the two nations in relation to geography, the First Nations populations and the history of colonization. While the standards for pediatric anesthesia and the specialty training requirements are set by the Australian and New Zealand College of Anesthetists and the Society for Pediatric Anesthesia in New Zealand and Australia, colonization has created distinct challenges that each nation now faces in order to improve the anesthetic care of its pediatric population. Australia generally has a high standard of living and good access to health care; disparities exist for First Nations People and for those living in rural or remote areas. Two influences have shaped training within New Zealand over the past 40 years; establishment of a national children's hospital in 1990 and, more importantly, acknowledgement that the First Nations people of New Zealand (Māori) have suffered because of failure to recognize their rights consequent to establishing a partnership treaty between Māori and the British Crown in 1840. Health inequities among Māori in New Zealand and First Nations People in Australia have implications for the health system, culturally appropriate approaches to treatment, and the importance of having an appreciation of First Nations people's history and culture, language, family structure, and cultural safety. Trainees in both countries need to be adequately supported in these areas in order for the sub-specialty of pediatric anesthesia to develop further and improve the anesthetic and surgical outcomes of our children.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".