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Record W3163540978 · doi:10.30770/2572-1852-94.2.8

Continuing Medical Education, Professional Development, and Requirements for Medical Licensure: A White Paper of the Conjoint Committee on Continuing Medical Education

2008· article· en· W3163540978 on OpenAlexaff
Stephen H. Miller, James N. Thompson, Paul E. Mazmanian, Alejandro Aparicio, David A. Davis, Bruce E. Spivey, Norman B. Kahn

Bibliographic record

VenueJournal of Medical Regulation · 2008
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLicensureContinuing medical educationLicenseContinuing educationCompetence (human resources)MandateCommitMedical educationAttendanceMedicineProfessional developmentProfessional associationPsychologyPublic relationsPolitical science

Abstract

fetched live from OpenAlex

To provide the best care to patients, a physician must commit to lifelong learning, but continuing education and evaluation systems in the United States typically require little more than records of attendance for professional association memberships, hospital staff privileges, or reregistration of a medical license. While 61 of 68 medical and osteopathic licensing boards mandate that physicians participate in certain numbers of hours of continuing medical education (CME), 17 of them require physicians to participate in legislatively mandated topics that may have little to do with the types of patients seen by the applicant physician. Required CME should evolve from counting hours of CME participation to recognizing physician achievement in knowledge, competence and performance. State medical boards should require valid and reliable assessment of physicians' learning needs and collaborate with physician and CME communities to assure that legislatively mandated CME achieves maximal benefit for physicians and patients. To ensure the discovery and use of best practices for continuing professional development and for maintenance of competence, research in CME and physician assessment should be raised as a national priority.

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)0.067
metaresearch head score (Gemma)0.092
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.933
Threshold uncertainty score0.353

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.092
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0070.008
Scholarly communication0.0110.006
Open science0.0060.004
Research integrity0.0430.028
Insufficient payload (model declined to judge)0.0050.005

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 head0.021
GPT teacher head0.354
Teacher spread0.333 · 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.

Study designNot applicable
DomainIncentives
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

Citations3
Published2008
Admission routes1
Has abstractyes

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