The impact of colonial-era policies on health workforce regulation in India: lessons for contemporary reform
Bibliographic record
Abstract
BACKGROUND: Regulation is a critical function in the governance of health workforces. In many countries, regulatory councils for health professionals guide the development and implementation of health workforce policy, but struggle to perform their responsibilities, particularly in low- and middle-income countries (LMICs). Few studies have analyzed the influence of colonialism on modern-day regulatory policy for health workforces in LMICs. Drawing on the example of regulatory policy from India, the goals of this paper is to uncover and highlight the colonial legacies of persistent challenges in medical education and practice within the country, and provide lessons for regulatory policy in India and other LMICs. MAIN BODY: Drawing on peer-reviewed and gray literature, this paper explores the colonial origins of the regulation of medical education and practice in India. We describe three major aspects: (1) Evolution of the structure of the apex regulatory council for doctors-the Medical Council of India (MCI); (2) Reciprocity of medical qualifications between the MCI and the General Medical Council (GMC) in the UK following independence from Britain; (3) Regulatory imbalances between doctors and other cadres, and between biomedicine and Indian systems of medicine. CONCLUSIONS: Challenges in medical education and professional regulation remain a major obstacle to improve the availability, retention and quality of health workers in India and many other LMICs. We conclude that the colonial origins of regulatory policy in India provide critical insight into contemporary debates regarding reform. From a policy perspective, we need to carefully interrogate why our existing policies are framed in particular ways, and consider whether that framing continues to suit our needs in the twenty-first century.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".