Physician migration to and from Canada: The challenge of finding the ethical and political balance between the individual's right to mobility and recruitment to underserved communities
Bibliographic record
Abstract
Physician migration to and from countries results from many local causes and international influences. These factors operate in the context of an increasingly globalized economy. From an ethical point of view, selective and targeted "raiding" of developing countries' medical workforce by wealthier countries is not acceptable. However, within specific countries, additional factors need to be identified to moderate the situation. I discuss the context in which Canada, a developed country, has struggled with workforce planning, with troubling results. I identify challenges for Canada but emphasize that decisions based on sloppy assumptions or inadequate data can lead to invalid policies, and poorly coordinated implementation can lead to a waste of human capital. Myths and attitudes further complicate physician workforce planning. Implementing recommendations of the recently concluded Task Force on the Licensure of International Medical Graduates will hopefully ameliorate the situation.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.016 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.012 |
| 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".