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Record W2414727737 · doi:10.3109/13561820.2016.1159187

Canadian student leaders’ perspective on interprofessional education: A consensus statement

2016· article· en· W2414727737 on OpenAlexaffabout
Jennifer Chicorelli, Anik Dennie, Christina Heinrich, B Hinchey, Faraz Honarparvar, M. Jennings, Chad Keefe, Trisha Lee Metro, Celeste Peel, Cordelia Snowdon, Justine Tempelman, Melody Wong, Susan L. Forbes, Lori A. Livingston

Bibliographic record

VenueJournal of Interprofessional Care · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsOntario Tech UniversityOkanagan University CollegeYork UniversityUniversity of British Columbia, Okanagan CampusLondon Health Sciences CentreLakehead UniversityWestern UniversityUniversity of British ColumbiaVancouver Island UniversityMount Royal UniversityUniversity of SaskatchewanLaurentian University
Fundersnot available
KeywordsInterprofessional educationSituatedStatement (logic)Medical educationKinesiologyPerspective (graphical)Health careSocial workPromotion (chess)Health promotionPedagogyPsychologySociologyNursingMedicinePolitical sciencePublic health

Abstract

fetched live from OpenAlex

The purpose of this article is to report on the outcomes of an interprofessional education (IPE) consensus-building exercise amongst student leaders enrolled in health science-related degree programs. The 12 participants included undergraduate and graduate students from eight different universities situated in five Canadian provinces. Their areas of study spanned a broad range of professions and disciplines including child and youth care, health promotion, nursing, kinesiology, medicine, physical education, psychology, and social work. A consensus statement regarding IPE and, more specifically, "what we know," "what we don't know," and "where do we go from here" is presented. These insights are unique, and a willingness to embrace them may be critical in building the next generation of improved IPE offerings across the country.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.032
GPT teacher head0.484
Teacher spread0.452 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations7
Published2016
Admission routes2
Has abstractyes

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