Bibliographic record
Abstract
Ronald Carter, DC, MA* Past President, Canadian Chiropractic Association and integrity to maximize these opportunities. It appears that a small segment of our profession, with some elected leaders, appear intent on answering this crisis with only the 1910 chiropractic subluxation model. Their approach is not only wrong, but it prevents what is right from being done. Dr. Darrel Ladell stated it so well in his report on the Radiology Issue: Beware of the enemy for he is us. Subluxation, though a vital part of our history has been described as the Achilles Heel of our profession. When you review the available literature and combine it with knowledge of our history, it quickly shows where the subluxation model has failed. This model has cost us years of positive growth. This paper proposes that there is no need to beat our profession up again, punishing us with a misdirected allegiance to our dysfunctional history. There is a positive path to follow that will assure the acceptance of the patients we treat, increase the public enhancement we seek and provide a greater acceptance into the scientific health care delivery system. Working together in partnerships and further developing our expertise as the leaders in the area of manipulation will assure our future. As leaders in the complementary health care system, our profession will see greater numbers of the public and provide us greater opportunity to serve. The demands for success are not beyond what we can achieve collectively. Those who are sincere and choose a future of service and security will be anxious to read this document. Those who refuse this information may well become the true victims of the silent killer.
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.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".