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Record W2801397449 · doi:10.1097/acm.0000000000002233

Beyond the Lamppost: A Proposal for a Fourth Wave of Education for Collaboration

2018· article· en· W2801397449 on OpenAlexafffund
Elise Paradis, Cynthia Whitehead

Bibliographic record

VenueAcademic Medicine · 2018
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsWomen's College HospitalSocial Sciences and Humanities Research CouncilThe Wilson CentreCanadian Institutes of Health Research
FundersCanadian Institutes of Health Research
KeywordsInterprofessional educationPopularityWorkforceScholarshipHealth carePublic relationsCurriculumPopulation healthMedical educationMedicineSociologyPolitical sciencePublic healthNursingPedagogy

Abstract

fetched live from OpenAlex

Interprofessional education (IPE) is an increasingly popular educational model that aims to educate health care students to be better collaborators by enabling them to learn with, from, and about each other. IPE's rising popularity is evident in the increase in scholarship on this topic over the last few decades. In this Perspective, the authors briefly describe three historical "waves" of IPE: managing the health workforce through shared curriculum, maximizing population health through health workforce planning, and fixing individuals to fix health care. Using insights from the social sciences and past practice, they then discuss six reasons why the current third wave of IPE is likely to fall short of meeting its goals, including that (1) IPE is logistically complex and costly, (2) IPE is developmentally inappropriate, (3) the link between IPE and key outcomes is still missing, (4) IPE insufficiently engages with theory, (5) IPE rarely addresses power and conflict, and (6) health care is an inertial system that IPE is unlikely to change. The authors conclude by sharing their vision for a fourth wave of education for collaboration, addressing workplace systems and structures, which would combine undergraduate, uniprofessional education for collaboration with practice-based interventions.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.570
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.484
Teacher spread0.433 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations154
Published2018
Admission routes2
Has abstractyes

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