The migration of health care workers in the Western Hemisphere: issues and impacts
Bibliographic record
Abstract
Health care migration is a large and global business. Recruitment is decentralized, involves both public and private sector entrepreneurs, and is difficult to regulate. The countries of the Western Hemisphere are important players in the global health market but, with the partial exception of the Islands of the Caribbean, there is little cooperation among their governments to manage migration patterns or combine forces in order to achieve economies of scale and cost effective training facilities. A related area of concern within the realm of health is care for the elderly. In wealthy countries people are living longer but not necessarily healthy lives and require expanding levels of care as they age. Their care is likely to involve paid service providers who often originate from poorer countries. But the demographic and economic changes in the poorer countries make caring for the elderly more difficult there as well.In the major migrant receiving Western Hemisphere countries, the US and Canada, the concern is that domestically educated nurses will not be sufficient to meet growing demands. The recruitment of immigrant professionals in nursing fields helps fill existing gaps. The pages that follow outline a range of issues related to health care workers from the Western Hemisphere, their patterns of movement, their roles in the work force primarily in the US and Canada, and the impacts of health care migration on source and receiving countries. The study tracks the largest segment of migrating health care workers: nurses and long term/direct care providers who perform nursing functions. It covers training, migration requirements, and ethical issues raised the flight of qualified health care givers and looks at efforts, especially in the Caribbean region to manage that flight.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".