Global Forum on Quality Assurance in CE/CPD: Assuring Quality across Boundaries
Bibliographic record
Abstract
As a result of the globalization of access and provision of continuing education and continuing professional development (CE/CPD), the national CE/CPD accreditation organizations of Australia, Canada, Ireland, New Zealand, South Africa, United Kingdom and United States formed the Global Forum on Quality Assurance of Continuing Education and Continuing Professional Development (GFQACE) to investigate and develop means of recognizing CE/CPD across boundaries. Two priorities were identified at their first meeting in 2016: (1) the development of an accreditation framework and (2) the identification of models and approaches to mutual recognition. The GFQACE approved an accreditation framework and facilitated review approach to mutual recognition in 2018 and is currently working on implementation guides. As background to the work of the GFQACE, this article provides a brief history of continuing education (CE) and continuing professional development (CPD) and discusses the value and benefits of CE/CPD to professional development of pharmacy professionals, innovation of pharmacy practice and the provision of quality patient care. Due to the essential role of CE/CPD accreditation in enabling recognition across boundaries, the nature and role of accreditation in defining, assuring and driving quality CE/CPD is described. Four conclusions regarding the broad sharing of perceptions of quality CE/CPD, the potential for expansion of the GFQACE and the benefits to pharmacy professionals, providers and pharmacy practice are discussed.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".