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Record W2066998905 · doi:10.1080/10401334.2013.770741

e-Professionalism: A New Frontier in Medical Education

2013· article· en· W2066998905 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTeaching and Learning in Medicine · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLicensureMedical educationIdentity (music)CurriculumAccreditationElement (criminal law)Social mediaProfessional associationRevocationSanctionsMedicinePsychologyPedagogyPolitical sciencePublic relationsLaw

Abstract

fetched live from OpenAlex

BACKGROUND: This article, prepared by the Association of Professors of Gynecology and Obstetrics Undergraduate Medical Education Committee, discusses the evolving challenges facing medical educators posed by social media and a new form of professionalism that has been termed e-professionalism. SUMMARY: E-professionalism is defined as the attitudes and behaviors that reflect traditional professionalism paradigms but are manifested through digital media. One of the major functions of medical education is professional identity formation; e-professionalism is an essential and increasingly important element of professional identity formation, because the consequences of violations of e-professionalism have escalated from academic sanctions to revocation of licensure. CONCLUSION: E-professionalism should be included in the definition, teaching, and evaluation of medical professionalism. Curricula should include a positive approach for the proper professional use of social media for learners.

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.

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)0.005
metaresearch head score (Gemma)0.043
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.043
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 integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.451
Teacher spread0.380 · 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