Source country perceptions, experiences, and recommendations regarding health workforce migration: a case study from the Philippines
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 Philippines continues to overproduce nurses for export. Little first-hand evidence exists from leading organisations in the Philippines concerning their experiences and perceptions in relation to Filipino nurse migration. What are their views about health workforce migration? This paper addresses this research gap by providing a source country perspective on Filipino nurse migration to Australia. METHODS: Focus-group interviews were conducted with key informants from nine Filipino organisations in the Philippines by an Australian-Filipino research team. The organisations were purposively selected and contacted in person, by phone, and/or email. Qualitative thematic analysis was performed using a coding framework. RESULTS: Health workforce migration is perceived to have both positive and negative consequences. On the one hand, emigration offers a welcome opportunity for individual Filipino nurses to migrate abroad in order to achieve economic, professional, lifestyle, and social benefits. On the other, as senior and experienced nurses are attracted overseas, this results in the maldistribution of health workers particularly affecting rural health outcomes for people in developing countries. Problems such as 'volunteerism' also emerged in our study. CONCLUSIONS: In the context of the WHO (2010) Code of Practice on the International Recruitment of Health Personnel it is to be hoped that, in the future, government recruiters, managers, and nursing leaders can utilise these insights in designing recruitment, orientation, and support programmes for migrant nurses that are more sensitive to the experience of the Philippines' education and health sectors and their needs.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.015 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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