Statutory Regulation of Traditional Medicine Practitioners and Practices: The Need for Distinct Policy Making Guidelines
Bibliographic record
Abstract
The World Health Organization (WHO) has called for the increased statutory regulation of traditional and complementary medicine practitioners and practices, currently implemented in about half of nations surveyed. According to recent WHO data, however, the absence of policy guidelines in this area represents a significant barrier to implementation of such professional regulations. This commentary reviews several key challenges that distinguish the statutory regulation of traditional medicine practitioners and practices from biomedical professional regulation, providing a foundation for the development of policy making parameters in this area. Foremost in this regard are the ongoing impacts of the European colonial encounter, which reinforce biomedicine's disproportionate political dominance across the globe despite traditional medicine's ongoing widespread use (particularly in the global South). In this light, the authors discuss the conceptual and historical underpinnings of contemporary professional regulatory structures, the tensions between institutional and informal traditional medicine training pathways, and the policy challenges presented by the prospect of standardizing internally diverse indigenous healing approaches. Epistemic and evidentiary tensions, as well as the policy complexities surrounding the intersection of cultural and clinical considerations, present additional challenges to regulators. Conceptualizing professional regulation as an intellectual property claim under the law, the authors further consider what it means to protect traditional knowledge and prevent misappropriation in this context. Overall, the authors propose that innovative professional regulatory approaches are needed in this area to address safety, quality of care, and accessibility as key public interest concerns, while prioritizing the redress of historical inequities, protection of diverse indigenous knowledges, and delivery of care to underserved populations.
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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 | 0.224 | 0.263 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.064 |
| Scholarly communication | 0.029 | 0.036 |
| Open science | 0.011 | 0.015 |
| Research integrity | 0.046 | 0.068 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".