The financial losses from the migration of nurses from Malawi
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The migration of health professionals trained in Africa to developed nations has compromised health systems in the African region. The financial losses from the investment in training due to the migration from the developing nations are hardly known. METHODS: The cost of training a health professional was estimated by including fees for primary, secondary and tertiary education. Accepted derivation of formula as used in economic analysis was used to estimate the lost investment. RESULTS: The total cost of training an enrolled nurse-midwife from primary school through nurse-midwifery training in Malawi was estimated as US$ 9,329.53. For a degree nurse-midwife, the total cost was US$ 31,726.26. For each enrolled nurse-midwife that migrates out of Malawi, the country loses between US$ 71,081.76 and US$ 7.5 million at bank interest rates of 7% and 25% per annum for 30 years respectively. For a degree nurse-midwife, the lost investment ranges from US$ 241,508 to US$ 25.6 million at 7% and 25% interest rate per annum for 30 years respectively. CONCLUSION: Developing countries are losing significant amounts of money through lost investment of health care professionals who emigrate. There is need to quantify the amount of remittances that developing nations get in return from those who migrate.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it