The feminisation of Canadian medicine and its impact upon doctor productivity
Bibliographic record
Abstract
OBJECTIVE: We examined the differences in work patterns between female and male doctors in Canada to gain insight into the effect of an increased number of female doctors on overall doctor productivity. METHODS: Data on the practice profiles of female and male doctors across Canada were extracted from the 2007 National Physician Survey. A doctor productivity measure, 'work hours per week per population' (WHPWPP), was created, based on the number of weekly doctor hours spent providing direct patient care per 100,000 citizens. The predicted WHPWPP was calculated for a hypothetical time-point when the female and male doctor populations reach equilibrium. The differences in current and predicted WHPWPP were then analysed. RESULTS: Female medical students currently (2007) outnumber male medical students (at 57.8% of the medical student population). The percentage of practising doctors who are women is highest in the fields of paediatrics, obstetrics and gynaecology, psychiatry and family practice. Female doctors work an average of 47.5 hours per week (giving 30.0 hours of direct patient care), compared with 53.8 hours worked by male doctors (35.0 hours of direct patient care) (P < 0.01, chi(2) test). Female doctors tend to work less on call hours per week and see fewer patients while on-call. Female doctors are also more likely to take parental leave or a leave of absence (P < 0.01, chi(2) test). The difference in current and predicted WHPWPP was found to be 2.6%, equivalent to 1853 fewer full-time female doctors or 1588 fewer full-time male doctors. CONCLUSIONS: Gender appears to have a significant influence on the practice patterns of doctors in Canada. If the gender-specific work patterns described in the present study persist, an overall decrease in doctor productivity is to be anticipated.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".