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Record W6977119040 · doi:10.6084/m9.figshare.4983158

Current state of interprofessional education in Canadian medical schools: Findings from a national survey

2017· article· en· W6977119040 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2017
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
Fundersnot available
KeywordsInterprofessional educationCurriculumState (computer science)Health careHealth professionalsUndergraduate educationSurvey data collection

Abstract

fetched live from OpenAlex

Interprofessional education (IPE) is being increasingly recognised and prioritised in undergraduate medical education. While efforts are underway to integrate IPE into health professional curricula across Canada, the state of IPE in Canadian medical schools remains unclear. This study aims to assess the current practice of IPE in Canadian undergraduate medical curricula. An online survey was distributed to IPE directors (or designees) of all Canadian medical schools. The survey gathered details of the IPE experiences offered, curriculum structure, and perceived barriers to the programmes. The survey was completed by 12 of 17 Canadian medical schools and revealed that IPE is generally well represented in Canadian undergraduate medical education curricula. Reported barriers to IPE efforts included scheduling and funding limitations. By comparison, student interest was one of the least commonly cited issues. It would appear that students and faculty are interested in advancing the state of IPE in undergraduate medical education. The results of this study are crucial as IPE continues to evolve as a component of undergraduate medical curricula across the globe.

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)0.026
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: none
Teacher disagreement score0.795
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.008
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.180
GPT teacher head0.458
Teacher spread0.278 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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