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Record W2903285464 · doi:10.1097/acm.0000000000002457

Shedding More Light on the State of Interprofessional Education

2018· letter· en· W2903285464 on OpenAlexaffabout
Louise Nasmith, Victoria Wood, Carrie Krekoski

Bibliographic record

VenueAcademic Medicine · 2018
Typeletter
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsGeneral partnershipInterprofessional educationHealth careGovernment (linguistics)SociologyHigher educationInstitutionWork (physics)Political sciencePublic relationsSocial science

Abstract

fetched live from OpenAlex

To the Editor: On behalf of the University of British Columbia (UBC), one of the academic institutions cited in the most recent article by Drs. Paradis and Whitehead, “Beyond the Lamppost: A Proposal for a Fourth Wave of Education for Collaboration,”1 we would like to clarify misconceptions about the implementation of interprofessional education (IPE) at our institution and present our current work, which we argue places us firmly in the fourth wave of education for collaboration. The authors cite the work of Dr. John McCreary at UBC as an example of a failed attempt during the first wave of IPE. Although UBC’s Division of Interprofessional Education was not sustainable, it laid the foundation for decades of subsequent collaboration across the health professional programs at UBC through the College of Health Disciplines (2001–2015) and now the Office of UBC Health situated within the provost’s portfolio (2015–present). This evolution has firmly rooted collaboration within the health programs at UBC and has allowed us to move into what we would consider the fourth wave of IPE, which we argue is “integration” and includes a number of the elements proposed by Drs. Paradis and Whitehead. Our work at UBC is anchored in the provincial priority of team-based care and is developed in partnership with patients, health authorities, government, and students. The evolution of health care towards an integrated system focused on individual and community well-being is a challenge of global importance and urgency; supporting this transformation is a strategic priority for UBC. Under the umbrella of UBC Health, our programs use an integrated approach to health professional education, which focuses on learning opportunities that address complex areas of health care that benefit from a collaborative approach (ethics, Indigenous cultural safety, e-health, professionalism, and resilience). Technology supports learning that is unique to each profession and provides economies of scale for foundational knowledge common to all programs, while learning is enhanced by interprofessional components that bring together students for collaborative sessions interspersed throughout their programs. This integrated approach has moved IPE from an add-on that was often extracurricular and focused on discreet competencies, to being a part of students’ program requirements, replacing or supplementing current learning that is contextualized within the broader curriculum. Finally, the integrated approach to health professions education at UBC is supported by a unique organizational model with a governance structure that ensures that collaboration is at the heart of our daily operations. Louise Nasmith, MDCM, MEd, FCFP, FRCPSC(Hon)Professor, Office of UBC Health, University of British Columbia, Vancouver, British Columbia, Canada; [email protected] Victoria Wood, MACurriculum manager, Office of UBC Health, University of British Columbia, Vancouver, British Columbia, Canada. Carrie Krekoski, RDH, BDSc (Dental Hygiene), MEdPractice education manager, Office of UBC Health, University of British Columbia, Vancouver, British Columbia, Canada.

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)0.016
metaresearch head score (Gemma)0.083
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.027
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.083
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0070.011
Scholarly communication0.0130.013
Open science0.0060.005
Research integrity0.0270.054
Insufficient payload (model declined to judge)0.0080.002

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 head0.039
GPT teacher head0.465
Teacher spread0.426 · 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
GenreCommentary

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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