The “subluxation” issue: an analysis of chiropractic clinic websites
Bibliographic record
Abstract
BACKGROUND: Vertebral subluxation theories are controversial in chiropractic. Divisions are evident in the chiropractic community among those who align their practices to subluxation theories and those who do not. This study investigated how many clinics offering chiropractic in the Canadian province of Alberta promote a theory of subluxation, which health ailments or improvements were linked to subluxation, and whether the subluxation discourse was used to promote chiropractic for particular demographics. METHODS: Using the search engine on the Canadian Chiropractic Associations' website, we made a list of all clinics in Alberta. We then used Google searches to obtain a URL for each clinic with a website, totalling 324 URLs for 369 clinics. We then searched on each website for "subluxation" and performed content analysis on the related content. RESULTS: One hundred twenty-one clinics' websites (33%) presented a theory of vertebral subluxation. The health ailments and improvements discussed in relation to subluxation were wide-ranging. An observed trend was the marketing of chiropractic for children, which was observed on 29 clinic websites (8%). CONCLUSIONS: Based on the controversy surrounding vertebral subluxation, the substantial number of clinic websites aligning their practice with vertebral subluxation should cause concern for regulatory bodies.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".