How times change:Evaluation of the need to revise chiropractic education standards in the United Kingdom.
Bibliographic record
Abstract
Introduction & Aim: Health regulators in the UK fulfil their statutory duty to maintain high standards of education and training of health professionals by setting standards for education. Ensuring standards are contemporary and fit for purpose is fundamental to this function. This research aimed to evaluate whether the Education Standards of the General Chiropractic Council (2017) (ES) remained fit for purpose in 2021, or whether revisions were needed to meet current and future competency requirements for chiropractic graduates. Methods: An exploratory, qualitative methodology was followed. The ES were comparatively mapped to relevant standards, authoritative practice and quality assurance frameworks from other healthcare and higher education regulators, professional and chartered bodies. Areas of difference from other standards and frameworks were identified and substantive differences described. Results: 21 global and national frameworks and standards were mapped. Healthcare disciplines included physiotherapy, medicine and osteopathy. Subjects included musculoskeletal capabilities, rehabilitation, person- centred approaches, dementia training, research competencies and education. 20 substantive areas not captured in the ES, or requiring strengthening, were identified. These included: person-centred approaches, safety and quality, rehabilitation, prevention and health promotion, psychologically informed approaches, interprofessional practice, collaborative care, integration of evidence into practice, digital readiness and reflective practice. Substantive areas linked to programme delivery included: protecting the interests of patients in an education setting, integrating clinical and educational governance, clinical experience and interdisciplinary learning. Conclusion: Although broadly fit for purpose, mapping indicated the ES were falling out of step with the
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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 | 0.074 | 0.216 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".