Care and Global Migration in the Nursing Profession: a north Indian perspective
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
Globalisation, supply–demand dynamics, uneven development, enhanced connectivity including the better flow of information, communication and the reduced cost of travel have encouraged the global integration of nursing labour markets. Developed regions of the world have attracted internationally educated nurses (IENs) because of growing healthcare needs. India, along with the Philippines, has become a key supplier of nurses in the global economy. Traditionally the supply of nurses was heavily regionalised in south India, especially Kerala, but of late Punjab, in north India, has played an increasing role in nurse training and migration as the profession has become more respected and more international. This paper uses survey and interview data to detail the recent interest in nursing as a channel for independent female international migration from Punjab, and to examine how migratory ambitions have developed over the last decade in parallel with the changing status of nursing as an internationally respected profession. We identify growing interest in international migration for nursing students and their increased intention to pursue employment opportunities in Australia and New Zealand. This research highlights how nursing and care migration are increasingly structured by international circuits of training and employment, and how such circuits alter migrant and occupational geographies on the ground in sending regions.
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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 | 0.002 | 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