MétaCan
Menu
Back to cohort
Record W2587557373 · doi:10.18192/uojm.v7i1.1798

Medical Education Research and the Hierarchy in Medical Training: An Interview with Dr. Dylan Bould

2017· article· en· W2587557373 on OpenAlexaffvenueabout
Menachem Benzaquen

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMentorshipMedicineMedical schoolLibrary scienceMedical education

Abstract

fetched live from OpenAlex

AbstractDr. Dylan Bould is an anesthesiologist at CHEO (Children’s Hospital of Eastern Ontario) and Director of Education Research at the University of Ottawa’s Department of Anesthesiology. Dr. Bould began training in anesthesia in the U.K. and completed fellowships in pediatric anesthesia and medical education at SickKids and St. Michael’s Hospital in Toronto, as well as a pediatric cardiac anesthesia fellowship in London, England. Over the course of his fellowships in Toronto, Dr. Bould completed a Master of Education at the University of Toronto focusing on medical education. Dr. Bould is also involved in global health, having worked in Nepal and Kenya, and was part of the organization process of the University of Zambia Anesthesia Residency Program. Dr. Bould’s current research focuses on hierarchy in medical training, mentorship in medical education, and simulation in healthcare education. RésuméDr Dylan Bould est un anesthésiologiste au Centre hospitalier pour enfants de l’est de l’Ontario (CHEO) et le directeur de la recherche en enseignement au département d’anesthésie de l’Université d’Ottawa. Dr Bould a commencé sa formation en anesthésie au Royaume-Uni et a complété des formations complémentaires (fellowships) en anesthésie pédiatrique et en enseignement médical à SickKids et à l’Hôpital St Michael à Toronto, ainsi qu’une formation en anesthésie cardiaque pédiatrique à Londres, en Angleterre. Au cours de ses formations complémentaires à Toronto, Dr Bould a complété une maîtrise en éducation à l’Université de Toronto axée sur l’enseignement médical. Dr Bould est également impliqué dans le domaine de la santé mondiale, ayant travaillé au Népal et au Kenya, et ayant aidé à mettre sur pied le programme de résidence en anesthésie à l’Université de la Zambie. La recherche actuelle de Dr Bould se concentre sur la hiérarchie présente lors de la formation médicale, le mentorat en enseignement médical, et la simulation dans l’enseignement des soins de santé.

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)0.031
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.046
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0300.019
Scholarly communication0.0100.012
Open science0.0030.009
Research integrity0.0060.022
Insufficient payload (model declined to judge)0.0040.001

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 head0.083
GPT teacher head0.410
Teacher spread0.327 · 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.

Study designQualitative
DomainMethods
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

Citations0
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueUniversity of Ottawa Journal of MedicineSame topicInnovations in Medical EducationFrench-language works237,207