A Brief Review of Chiropractic Educational Programs and Recommendations for Celebrating Education on Chiropractic Day
Bibliographic record
Abstract
Objective: The purpose of this article is to provide an overview of the growth of chiropractic education globally and a chronological list of current training programs. Another purpose is to provide exemplars of enduring programs and offer suggestions for how chiropractic practitioners may celebrate education on Chiropractic Day, which is September 18. Discussion: Chiropractic education has transformed considerably over the past 125 years, and there are now 52 programs globally. We consider the 5 longest-existing chiropractic programs and propose hypotheses for what may have contributed to their durability. In addition, we offer ideas and opportunities for how chiropractic practitioners may focus on chiropractic education when celebrating the founding of the profession. Conclusion: Since its inception, chiropractic education has expanded around the world and continues to develop. Recognized accreditation agencies and testing organizations are ensuring that standards of education are established and maintained internationally. With innovation, international collaboration, and a commitment to continuous professional development, the future of chiropractic education is bright. We urge chiropractic practitioners from all over the world to celebrate these accomplishments on Chiropractic Day.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".