The cardiac sonography workforce in New Zealand
Bibliographic record
Abstract
Abstract Introduction: The aim of this paper is to investigate the cardiac sonography workforce characteristics and registration requirements in New Zealand (NZ), with a comparison to similar workforces internationally. Methods: The Survey of Clinical Echocardiography in New Zealand 2 (SCANZ2) audit was performed in December 2010. All of NZ's public‐funded District Health Board (DHB) centers providing echocardiography services responded to questions relating to staff, equipment, procedure types and patient statistics. The Medical Radiation Technologists Board (MRTB), Clinical Physiologists Registration Board (CPRB) and Australian Sonographers Association Registry (ASAR) websites were reviewed in March 2012 for registered sonographers with a cardiac scope of practice. The cardiac sonography workforces in Australia, the UK, the USA and Canada were investigated for comparison. Results: There are 84 cardiac sonographers (60.3 full‐time equivalent) working in DHBs: 71% from a cardiac technical background; 40% have post‐graduate qualifications; a further 17% are undertaking post‐graduate qualifications; and 59 cardiac sonographers have registration with professional bodies in NZ and/or Australia. Cardiac sonographers in NZ do not undergo compulsory registration, but other sonographers in NZ have compulsory registration with the MRTB. Sonographers are predominantly not licensed internationally. Discussion: Disparity exists between registration of cardiac and non‐cardiac sonographers in NZ. Many cardiac sonographers have voluntary registration but few are registered with the MRTB. Reasons for this include professional alignment, educational qualifications and representation. International trends show increased pressure from governments and professional bodies to regulate sonographers. Conclusion: This study provides a snapshot of the cardiac sonography workforce in NZ for the first time.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".