A mixed-methods study of health worker migration from Jamaica
Bibliographic record
Abstract
BACKGROUND: This study sought to better understand the drivers of migration, its consequences, and the various strategies countries have employed to mitigate its negative impacts. The study was conducted in four countries-Jamaica, India, the Philippines, and South Africa-that have historically been 'sources' of health workers migrating to other countries. The aim of this paper is to present the findings from the Jamaica portion of the study. METHODS: Data were collected using surveys of Jamaica's generalist and specialist physicians, nurses, midwives, and dental auxiliaries, as well as structured interviews with key informants representing government ministries, professional associations, regional health authorities, healthcare facilities, and educational institutions. Quantitative data were analyzed using descriptive statistics and regression models. Qualitative data were analyzed thematically. Multiple stakeholder engagement workshops were held across Jamaica to share and validate the study findings and discuss implications for the country. RESULTS: Migration of health workers from Jamaica continues to be prevalent. Its causes are numerous, long-standing, and systemic, and are largely based around differences in living and working conditions between Jamaica and 'destination' countries. There is minimal formal tracking of health worker migration from Jamaica, making scientific analysis of its consequences difficult. Although there is evidence of numerous national and international efforts to manage and mitigate the negative impacts of migration, there is little evidence of the implementation or effectiveness of such efforts. Potential additional strategies for better managing the migration of Jamaica's health workers include the use of information systems to formally monitor migration, updating the national cadre system for employment of health personnel, ensuring existing personnel management policies, such as bonding, are both clearly understood and equitably enforced, and providing greater formal and informal recognition of health personnel. CONCLUSION: Although historically common, migration of Jamaica's health workers is poorly monitored and understood. Improved management of the migration of Jamaica's health workers requires collaboration from stakeholders across multiple sectors. Indeed, participating stakeholders identified a wide range of potential strategies to better manage migration of Jamaica's health workers, the implementation and testing of which will have potential benefits to Jamaica as well as other 'source' countries.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".