MétaCan
Menu
← Back to cohort
Record W2419105950

Medical professionalism in the new millennium: are there intercultural differences? Brief report and commentary.

2009· article· en· W2419105950 on OpenAlexaboutno aff
Mohammad Nashit Shah, Eleanor M. Summerhill, Constantine A. Manthous

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsIMGIndoctrinationMedical schoolMedical educationPsychologyMedicinePolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

We hypothesized that differences in premedical and medical indoctrination might lead to demonstrable differences in notions of medical professionalism among U.S. medical schoolgraduates (USMG) and international medical graduates (IMG). We used the previously validated Barry Challenges to Professionalism questionnaire to query applicants to our Medicine residency. Two hundred sixty-six of 1,476 applicants responded; 57 were USMG and 188 IMG were non-U.S. citizens. There were no significant differences in responses based on gender or medical school background (comparing USMG vs IMG). Graduates of U.S. and Canadian schools were more likely than those of Indian schools to answer correctly three of 10 questions. We use the results of this ostensibly "negative" study to comment on the foundations for the hypothesis and logistic difficulty of studying the question.

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)0.010
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation 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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.025
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.073
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0040.005
Scholarly communication0.0030.005
Open science0.0040.002
Research integrity0.0250.014
Insufficient payload (model declined to judge)0.0060.002

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 head0.038
GPT teacher head0.325
Teacher spread0.287 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venuePubMed→Same topicInnovations in Medical Education→French-language works237,207→