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Record W2173832866 · doi:10.3402/jecme.v4.30030

A new day for CME/CPD in Canada: proceedings from the 1st Canada Regional Conference of the Global Alliance for Medical Education in Montreal, Canada

2015· article· en· W2173832866 on OpenAlexaboutno aff
Suzanne Murray, Lisa Sullivan

Bibliographic record

VenueJournal of European CME · 2015
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsAllianceContinuing medical educationContinuing educationContinuing professional developmentPolitical scienceMedical educationPublic relationsProfessional developmentPsychologyMedicine

Abstract

fetched live from OpenAlex

The Global Alliance for Medical Education (GAME) is a not-for-profit organization founded in 1995, with the aim of advancing innovation in medical education. The 1st GAME Canada regional conference was held in Montreal on May 22, 2015, under the leadership of Suzanne Murray, who acted as programme chair, and GAME president Lisa Sullivan. The conference brought together a broad array of speakers and panellists, including experts from academic centres, health systems, accreditors, private organizations, and industry. Thirty-one key stakeholders participated in the event, demonstrating a strong commitment towards the improvement of best practice in continuing medical education (CME)/continuing professional development (CPD). The conference included diverse presentations providing opportunities for reflection and discussion throughout the day. The participants actively took part in stimulating discussions that covered a large range of topics, including the need for enhanced networking and opportunities to learn from others, the challenges of assessment and the potential solutions, interprofessional education and competencies, and, finally, the future of a Canadian CME/CPD organization.

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)0.006
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.290
Teacher spread0.256 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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