The Councils on Chiropractic Education International Mapping Project: Comparison of Member Organizations’ Educational Standards to the Councils on Chiropractic Education International Framework Document
Bibliographic record
Abstract
Objective: The purpose of this project was to investigate how well each member agency's standards complied with the Councils on Chiropractic Education International (CCEI) framework standards. Methods: Each of the CCEI member agencies were provided with a mapping template that was approved by all representatives. A representative from each agency independently mapped their agency's standards to the CCEI framework standards using the template document. Discrepancies were explored and discussed among members. Member agencies discussed with their constituents the omissions and areas that did not comply or adequately match the CCEI document. Changes or additions to member agency standards were made, and updated versions of the mapping were agreed by all CCEI representatives. Results: There were 12 sections containing 30 standards within the CCEI framework standards. The Council of Chiropractic Education Australasia and Council on Chiropractic Education Canada reported relevant standards for all 30 CCEI standards. The European Council on Chiropractic Education had 29 of 30 relevant standards, with no direct standard for service. The products that were created were an executive summary of our findings and a detailed map showing similarities for each of the member agencies. Conclusion: This mapping project demonstrated the similarities of the CCEI member agency standards and that these standards focused on outcomes-based chiropractic education. This quality improvement project resulted in useful dialogue among the member agencies during this project, which clarified areas of difference.
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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 | 0.167 | 0.273 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.023 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".