The health of New Zealand cardiology: senior medical officer workforce survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: To quantify the current state of the cardiology specialist workforce in Health New Zealand - Te Whatu Ora. METHODS: The Cardiac Society of Australia and New Zealand sent a survey to all Health New Zealand - Te Whatu Ora cardiology departments in 2024, requesting information on specialist cardiac staff. Population information was obtained from Health New Zealand - Te Whatu Ora. International comparisons were obtained by website search. RESULTS: Of 154 Health New Zealand - Te Whatu Ora-employed cardiologists, 119 (77%) were male, and 113 (73%) received cardiology training in New Zealand. Over half were aged >50, 35% >55, including 18% >60 years. Time in current position was 12±9 years and the vacancy rate was 14%. The current ratio of persons per cardiologist is 35,000. In the five districts with the highest proportion of Māori and Pacific peoples, this ratio exceeds the national average: Tairāwhiti 54,000; Counties Manukau 38,000; Lakes 61,000; Northland 52,000; Hawke's Bay 47,000. For cities with cardiac surgery the ratio is 32,000 and without is 46,000. International ratios include: United States of America (USA) 15,000; Canada 25,000; United Kingdom (UK) 40,000 and Australia 25,000 persons per cardiologist. CONCLUSIONS: Health New Zealand - Te Whatu Ora has an experienced but ageing cardiologist workforce, with many vacancies. Districts with higher Māori/Pacific populations have fewer cardiologists per capita than the national average of 1:35,000, which is similar to the UK, but less than the USA, Australia and Canada.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it