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Record W1490497777 · doi:10.21225/d57309

The Characteristics of Continuing Professional Education Systems in the Health Professions in Canada

2006· article· en· W1490497777 on OpenAlexaffvenueabout
Vernon Curran, Fran Kirby, Lisa Fleet

Bibliographic record

VenueCanadian Journal of University Continuing Education · 2006
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCredentialingLicensureCertificationContinuing educationHealth professionsCompetence (human resources)Medical educationProfessional certification (computer technology)Continuing professional developmentProfessional associationHealth careProfessional developmentAllied health professionsMedicineNursingPublic relationsPsychologyPolitical science

Abstract

fetched live from OpenAlex

Mandatory continuing education (MCE) has become widely accepted across many professions and jurisdictions in Canada as a re-credentialing mechanism. MCE is defined as continuing professional education (CPE) courses and/or programs, beyond the entry-level educational requirements, required by a licensure board, professional organization, or the workplace in order to maintain competence or retain licensure, certification, and/or employment. The purpose of this paper is to summarize the nature and characteristics of the CPE systems of the major health care professions in Canada. Overall, mandatory systems of CPE are increasing among allied health professional groups in Canada. This introduces significant opportunities for providers of CPE for the health professions. Important trends appear to include an increase in distance education formats, an increase in collaborative arrangements between providers, and an increase in the use of CPE to regulate practice.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.249
Teacher spread0.243 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations11
Published2006
Admission routes3
Has abstractyes

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