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Record W2512436401 · doi:10.1097/ceh.0000000000000075

Evolving Alignment in International Continuing Professional Development Accreditation

2016· article· en· W2512436401 on OpenAlexaffabout
Graham T. McMahon, Samar Aboulsoud, Jennifer Gordon, Mindi K. McKenna, James Meuser, Mark L. Staz, Craig M. Campbell

Bibliographic record

VenueJournal of Continuing Education in the Health Professions · 2016
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMedical Council of Canada
Fundersnot available
KeywordsAccreditationCompetence (human resources)Medical educationCore competencyContext (archaeology)Health careMedicineSet (abstract data type)NursingEngineering ethicsComputer sciencePsychologyPolitical scienceEngineeringBusiness

Abstract

fetched live from OpenAlex

Several of the world's accreditation systems for continuing professional development (CPD) are evolving to encourage continuous improvement in the competence and performance of health care providers and in the organizations in which they provide patient care. Clinicians learn best when they can to choose from a diverse array of activities and formats that are relevant and meet their needs. Since choice and diversity are key to meeting clinicians' needs, several CPD accreditors have been engaging in deliberate, concerted efforts to identify a core set of principles that can serve as the basis for determining substantive equivalency between CPD accreditation systems. Substantive equivalency is intended to support the mobility of learners, allowing them to access accredited learning activities that are recognized by various CPD accreditation systems in a manner that maximizes the value of those accreditation systems, while minimizing the burden of adhering to their requirements. In this article, we propose a set of core principles that all CPD accreditation systems must express as the basis for determining substantive equivalency between CPD accreditation systems. The article will illustrate how five CPD accreditation systems (two in the USA, two in Canada, and one in Qatar), differing in focus (activity-based versus provider-based), context, and culture, express these values and metrics, and concludes by identifying the value of substantive equivalency for learners, medical regulators, and CPD accreditation systems.

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 imitation

Not 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.

metaresearch head score (Codex)0.142
metaresearch head score (Gemma)0.142
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.142
Threshold uncertainty score0.753

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1420.142
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.008
Science and technology studies0.0070.010
Scholarly communication0.0190.008
Open science0.0030.011
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.024
GPT teacher head0.414
Teacher spread0.390 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2016
Admission routes2
Has abstractyes

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