The determinants of the migration decisions of immigrant and non-immigrant physicians in Canada
Bibliographic record
Abstract
In this paper, we use data from the confidential master files of the Canadian Census over the years 1991-2006 to study the geographic mobility of immigrant and non-immigrant physicians who are already resident in Canada. We consider both inter- and intra- provincial migration, with a particular focus on migration to and from rural areas of Canada. We exploit the fact that it is possible to link individuals within families in the Census files in order to investigate the impact on the migration decision of the characteristics of a married physician’s spouse. Our results indicate that the magnitude of outflows is substantial and that the retention of immigrant physicians in rural areas and in some provinces will continue to be difficult. We find strong evidence that migration is a family decision, and spousal characteristics (education, age, years in Canada for immigrants) are important. As well, we find that large Canadian cities (mainly in Ontario) are the likely destination for the types of immigrant physicians typically able to be recruited to other areas, implying recruitment efforts of smaller provinces may have significant implications for the size of health care costs in larger provinces.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".