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Record W4402109594 · doi:10.55016/ojs/jet.v42i3.52435

Experiences of Undergraduate Education Students in an Interprofessional Course

2018· article· en· W4402109594 on OpenAlexaffabout
Gayle Rutherford, Robin Whiting, Hans Smits

Bibliographic record

VenueJournal of educational thought. · 2018
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCourse (navigation)Medical educationMathematics educationInterprofessional educationPsychologyPedagogyMedicineEngineeringPolitical scienceHealth care

Abstract

fetched live from OpenAlex

This paper explores the question "How might teacher education live well in a changing world?" through the lens of a particular course, "Interprofessional Practice in a Community Setting," offered at the University of Calgary during the 2005-2006 academic year. This action research project was inquiry-based and grounded in reflective practice driven by the essential question "what is the meaning and nature of inter-professional practice?" Details of the community-based projects were negotiated between the student project-based teams and the community liaisons. The students learned about interprofessional practice through their own experiences within their project team, their observations in the community. as well as through in-class discussions. This article takes up the reflections and observations through the experiences of the education students who chose to participate in this unique course offering.

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)0.006
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0190.009
Scholarly communication0.0120.004
Open science0.0020.017
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0050.001

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 head0.035
GPT teacher head0.518
Teacher spread0.484 · 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
GenreOther

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
Published2018
Admission routes2
Has abstractyes

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