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Record W2108889622 · doi:10.3109/13561820.2010.515044

Evaluating the effectiveness of an interprofessional education faculty development course: The transfer of interprofessional learning to the academic and clinical practice setting

2010· article· en· W2108889622 on OpenAlexafffund
Brian Simmons, Ivy Oandasan, Sophie Soklaradis, Martina Esdaile, Keegan K. Barker, Debbie Kwan, Molyn Leszcz, Mandy Lowe, Azi Moaveni, Denyse Richardson, Ivan Silver, Lynne Sinclair, Maria Tassone, Susan Wagner

Bibliographic record

VenueJournal of Interprofessional Care · 2010
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsSunnybrook Health Science CentreUniversity Health NetworkUniversity of Toronto
FundersAssociated Medical ServicesRoyal College of Physicians and Surgeons of Canada
KeywordsInterprofessional educationMedical educationFaculty developmentCourse (navigation)PsychologyTransfer of learningMedicineNursingProfessional developmentHealth careEngineeringPolitical science

Abstract

fetched live from OpenAlex

Currently, the literature offers little in the way of empirical accounts for the effectiveness of faculty/staff development in interprofessional education/collaboration (IPE/IPC) (e.g. Steinert, 20...

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)0.017
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.007
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 head0.059
GPT teacher head0.579
Teacher spread0.521 · 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

Citations17
Published2010
Admission routes2
Has abstractyes

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