Radiophobic Fear-Mongering, Misappropriation of Medical References and Dismissing Relevant Data Forms the False Stance for Advocating Against the Use of Routine and Repeat Radiography in Chiropractic and Manual Therapy
Bibliographic record
Abstract
There is a faction within the chiropractic profession passionately advocating against the routine use of X-rays in the diagnosis, treatment and management of patients with spinal disorders (aka subluxation). These activists reiterate common false statements such as "there is no evidence" for biomechanical spine assessment by X-ray, "there are no guidelines" supporting routine imaging, and also promulgate the reiterating narrative that "X-rays are dangerous." These arguments come in the form of recycled allopathic "red flag only" medical guidelines for spine care, opinion pieces and consensus statements. Herein, we review these common arguments and present compelling data refuting such claims. It quickly becomes evident that these statements are false. They are based on cherry-picked medical references and, most importantly, expansive evidence against this narrative continues to be ignored. Factually, there is considerable evidential support for routine use of radiological imaging in chiropractic and manual therapies for 3 main purposes: 1. To assess spinopelvic biomechanical parameters; 2. To screen for relative and absolute contraindications; 3. To reassess a patient's progress from some forms of spine altering treatments. Finally, and most importantly, we summarize why the long-held notion of carcinogenicity from X-rays is not a valid argument.
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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 | 0.084 | 0.186 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.060 |
| Scholarly communication | 0.014 | 0.023 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.014 | 0.024 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".