The regulation of complementary and alternative medicine professions in Ontario, Canada
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: This paper explains the regulation of complementary and alternative medicine (CAM) health professions, through the comparison of four distinct examples in Ontario, Canada including: chiropractors, naturopaths, homeopaths, and traditional Chinese medicine (TCM) practitioners. METHODS: This study analyzes the agenda setting and formulation stage of the policy process. In other words, it explores what happened between stakeholders before each of these CAM professions achieved regulation. Alford's model of dominant, challenging and repressed structured interests (DSIs, CSIs, and RSIs respectively) is used to describe the competition between various players within the healthcare system and their position in the health policy process. RESULTS: All four CAM professions have existed as a RSI at some point in their history, however, over the last century has sought to align themselves with various (or even become) challenging structural interests (CSIs) in order to be recognized as a regulated health profession. Dominant structural interests (DSIs), particularly the medical profession, initially largely ignored these professions' practices, unless sufficient public support of CAM practitioners' therapies warranted them to consider the need to regulate them. CONCLUSION: Unregulated CAM professions may increase their likelihood of becoming regulated if they: (1) gain popularity/strong support from patients or the general public, (2) organize themselves sufficiently that they pose a direct threat to one or more scopes of practice desirable by the DSIs and/or (3) are willing to adopt standards in education, training, and ethics that may [initially] reduce their scope of practice or profession's membership or slow their profession's growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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