Modelling the future of the Canadian cardiac surgery workforce using system dynamics
Why this work is in the frame
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Bibliographic record
Abstract
Due to the high costs and lengthy lead times involved with training health human resources such as physicians and surgeons, combined with the serious burden borne by the general population when health care provider shortages occur, advance planning of resource requirements is critical. This is particularly true in light of current demographic trends and Canada’s ageing population, which will potentially increase demand for health care providers in the future while also leading to the retirement of many of the providers currently practicing. The purpose of this research was to develop a model simulating the workforce within a single specialty at a national level, which includes students training to enter the profession, providing a tool that would help to inform future resource planning. We present the details of this model, developed using system dynamics modelling, and demonstrate it using the example of cardiac surgeons in 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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it