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Record W2407114206 · doi:10.1097/acm.0000000000000996

Resident Role Modeling

2015· article· en· W2407114206 on OpenAlexaffabout
Robert Sternszus, Mary Ellen Macdonald, Yvonne Steinert

Bibliographic record

VenueAcademic Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

PURPOSE: Role modeling by staff physicians is a significant component of the clinical teaching of students and residents. However, the importance of resident role modeling has only recently emerged, and residents' understanding of themselves as role models has yet to be explored. This study sought to understand residents' perceptions of themselves as role models, describe how residents learn about role modeling, and identify ways to improve resident role modeling. METHOD: Fourteen semistructured interviews were conducted with residents in internal medicine, general surgery, and pediatrics at the McGill University Faculty of Medicine between April and September 2013. Interviews were audio-recorded and subsequently transcribed for analysis; iterative analysis followed principles of qualitative description. RESULTS: Four primary themes were identified through data analysis: residents perceived role modeling as the demonstration of "good" behaviors in the clinical context; residents believed that learning from their role modeling "just happens" as long as learners are "watching"; residents did not equate role modeling with being a role model; and residents learned about role modeling from watching their positive and negative role models. CONCLUSIONS: While residents were aware that students and junior colleagues learned from their modeling, they were often not aware of role modeling as it was occurring; they also believed that learning from role modeling "just happens" and did not always see themselves as role models. Helping residents view effective role modeling as a deliberate process rather than something that "just happens" may improve clinical teaching across the continuum of medical education.

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)0.005
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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 integrity0.0000.001
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 head0.096
GPT teacher head0.410
Teacher spread0.314 · 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

Citations29
Published2015
Admission routes2
Has abstractyes

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