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Record W2120688845 · doi:10.3109/0142159x.2014.890281

Understanding, teaching and assessing the elements of the CanMEDS Professional Role: Canadian Program Directors’ views

2014· article· en· W2120688845 on OpenAlexaffabout
Andrew E. Warren, Victoria M. Allen, Fiona Bergin, Lara Hazelton, Peggy Alexiadis Brown, Katie Lightfoot, Jill McSweeney, Jerome F. Singleton, Joan Sargeant, Karen Mann

Bibliographic record

VenueMedical Teacher · 2014
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedical educationProfessional developmentPsychologyMedicinePedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: Physicians are required to maintain and sustain professional roles during their careers, making the Professional Role an important component of postgraduate education. Despite this, this role remains difficult to define, teach and assess. OBJECTIVE: To (a) understand what program directors felt were key elements of the CanMEDS Professional Role and (b) identify the teaching and assessment methods they used. METHODS: A two-step sequential mixed method design using a survey and semi-structured interviews with Canadian program directors. RESULTS: Forty-six program directors (48% response rate) completed the questionnaire and 10 participated in interviews. Participants rated integrity and honesty as the most important elements of the Role (96%) but most difficult to teach. There was a lack of congruence between elements perceived to be most important and most frequently taught. Role modeling was the most common way of informally teaching professionalism (98%). Assessments were most often through direct feedback from faculty (98%) and feedback from other health professionals and residents (61%). Portfolios (24%) were the least used form of assessment, but they allowed residents to reflect and stimulated self-assessment. CONCLUSION: Program directors believe elements of the Role are difficult to teach and assess. Providing faculty with skills for teaching/assessing the Role and evaluating effectiveness in changing attitudes/behaviors should be a priority in postgraduate programs.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
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 integrity0.0000.001
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 head0.070
GPT teacher head0.405
Teacher spread0.335 · 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

Citations35
Published2014
Admission routes2
Has abstractyes

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