A cross-sectional workforce survey of three traditional and complementary medicine professions in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Workforce studies about traditional and complementary medicine (T&CM) occupations in industrialized countries are scant; and, these occupations' position within the broader occupational workforce remains unclear. This study aims to address these gaps using a comparative approach. METHODS: Naturopaths, traditional Chinese medicine (TCM) / acupuncture practitioners, and homeopaths in Ontario, Canada were surveyed regarding their demographics, practice characteristics and self-reported income. Results were compared with parallel data from within and outside of Ontario. RESULTS: Study response rate: 23.3% (n = 1205). While predominantly female (57.9%), Ontario's TCM/acupuncture profession was less feminized than the naturopathic (77.1%) and homeopathic (78.3%) groups. Naturopaths were significantly younger than, and reported fewer years of clinical experience than, the other two groups. About half of TCM/acupuncture practitioners, and almost one-third of homeopaths had trained outside of Canada, predominantly in East and South Asia, respectively. More TCM/acupuncture practitioners (58.9%) and homeopaths (57.6%) had multilingual clinical practices than naturopaths (19.1%). Homeopaths worked fewer hours and saw fewer patients per week than the other occupations. Self-reported mean incomes varied across groups, with naturopaths earning more on average ($63,834, SD $57,101) than did TCM/acupuncture practitioners ($45,624, SD $44,081) or homeopaths ($29,230, SD $41,645). Holding other variables constant, internationally-trained practitioners reported earning one-third less than their Canadian-trained counterparts. DISCUSSION & CONCLUSIONS: Study findings echo occupationally-specific data from other industrialized jurisdictions; and, affirm that different T&CM occupations have distinctive demographic and practice characteristics. The demographic makeup of Ontario's TCM/acupuncture and homeopathy occupations suggests a role for these groups in delivering culturally-responsive care within Asian ethnic communities. T&CM practitioner incomes, in particular for internationally-trained practitioners, fell below the provincial population income median, and in many cases below the poverty line. T&CM occupations' relative socio-political marginality may be impacting clinicians' ability to earn a viable living.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".