Bibliographic record
Abstract
The Canadian Institute for Health Information says that more than 600 physicians left Canada in 2001, a 45% increase over the previous year (see related article, page 679). This figure, combined with the fact that only 334 physicians returned here, means that Canada suffered a net loss of 275 physicians in 2001. This represents a 68% increase over 2000 and the largest net loss since 1997, when it stood at 431 doctors. Most of the physicians moving abroad (72%) were specialists; of those, 64% had graduated from medical school 15 years ago or less. The number of active physicians in Canada increased again in 2001, to 58 546, and the number of physicians per 100 000 population improved slightly, from 187 per 100 000 in 2000 to 188 per 100 000 in 2001. This is the highest ratio since 1995 but is still below the 1993 peak of 191 per 100 000. The physician total is split evenly between specialists (49%) and family physicians (51%). Women continue to represent an increasingly larger share of the pool of practising doctors (30%); among family physicians, women account for 35% of the workforce. The average age of physicians continues to rise, with specialists averaging 48.8 years, family physicians 46.4. Fifteen percent (9200) of the country's practising physicians are aged 60 or older. — Lynda Buske, Associate Director of Research, CMA
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.145 | 0.074 |
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".