Where do family physicians practise after residency training? Flow of physicians from region to region across Canada.
Bibliographic record
Abstract
OBJECTIVE: To understand the flow of family physicians from region to region across Canada. To discover how many leave a region after residency, how many stay, and how many flow into a region from other regions. DESIGN: Cross-sectional study using descriptive statistics. SETTING: Various regions across Canada. PARTICIPANTS: A weighted sample (N = 14,332) of all family physicians who completed the College of Family Physicians of Canada's 2001 National Family Physician Workforce Survey. This survey asked where physicians had done their family medicine residency. MAIN OUTCOME MEASURES: The proportion of family physicians whose current region of practice was the same as their place of residency ("staying"), the proportion of family physicians who trained in one region and who now practise in a different region ("outflow"), the proportion of family physicians who practise in a region but were trained in another region ("inflow"), and the number of family physicians flowing in and out of regions. RESULTS: Half of Canadian family physicians were practising in regions different from the regions where they did their residency programs. This percentage varied by region, however, with only Ontario's percentage resembling the Canadian figure. In the Atlantic and Prairie regions, few stayed (13.8% and 24.7%, respectively), but many flowed in. In Quebec, a high proportion stayed after residency training (81.6%). In British Columbia, only 23.7% stayed, but many flowed in. CONCLUSION: This study provides information about the relationship between where family physicians did their residency programs and where they subsequently practised. Our results add important information to the health human resource literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".