Reflections on the ethics of recruiting foreign-trained human resources for health
Bibliographic record
Abstract
BACKGROUND: Developed countries' gains in health human resources (HHR) from developing countries with significantly lower ratios of health workers have raised questions about the ethics or fairness of recruitment from such countries. By attracting and/or facilitating migration for foreign-trained HHR, notably those from poorer, less well-resourced nations, recruitment practices and policies may be compromising the ability of developing countries to meet the health care needs of their own populations. Little is known, however, about actual recruitment practices. In this study we focus on Canada (a country with a long reliance on internationally trained HHR) and recruiters working for Canadian health authorities. METHODS: We conducted interviews with health human resources recruiters employed by Canadian health authorities to describe their recruitment practices and perspectives and to determine whether and how they reflect ethical considerations. RESULTS AND DISCUSSION: We describe the methods that recruiters used to recruit foreign-trained health professionals and the systemic challenges and policies that form the working context for recruiters and recruits. HHR recruiters' reflections on the global flow of health workers from poorer to richer countries mirror much of the content of global-level discourse with regard to HHR recruitment. A predominant market discourse related to shortages of HHR outweighed discussions of human rights and ethical approaches to recruitment policy and action that consider global health impacts. CONCLUSIONS: We suggest that the concept of corporate social responsibility may provide a useful approach at the local organizational level for developing policies on ethical recruitment. Such local policies and subsequent practices may inform public debate on the health equity implications of the HHR flows from poorer to richer countries inherent in the global health worker labour market, which in turn could influence political choices at all government and health system levels.
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 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 | 0.105 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.038 | 0.070 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.003 | 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".