Preferences of physicians for public and private sector work
Bibliographic record
Abstract
BACKGROUND: The public-private mix of healthcare remains controversial. This paper examines physicians' preferences for public sector work in the context of dual practice, whilst accounting for other differences in the characteristics of jobs. METHODS: A discrete choice experiment is conducted with data from 3422 non-GP specialists from the Medicine in Australia: Balancing Employment and Life (MABEL) panel survey of physicians. RESULTS: Physicians prefer to work in the public sector, though the value of working in the public sector is very small at 0.14% of their annual earnings to work an additional hour per week. These preferences are heterogeneous. Contrary to other studies that show risk averse individuals prefer public sector work, for physicians, we find that those averse to taking career or clinical risks prefer to work in the private sector. Those with relatively low earnings prefer public sector work and those with high earnings prefer private sector work, though these effects are small. CONCLUSIONS: Other job characteristics are more important than the sector of work, suggesting that these should be the focus of policy to influence specialist's allocation of time between sectors.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".