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Record W2333596082 · doi:10.1097/sih.0b013e31825e8daa

British Columbia Interprofessional Model for Simulation-Based Education in Health Care

2012· article· en· W2333596082 on OpenAlexaffabout
Karim Qayumi, Stuart Donn, Bin Zheng, Lynne Young, James Dutton, Monica Adamack, Ron Bowles, Adam Cheng

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2012
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsAlberta Children's HospitalUniversity of VictoriaUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsInterprofessional educationHealth careHealth professionalsMedical educationNursingMedicinePolitical science

Abstract

fetched live from OpenAlex

The rapid uptake of simulation-based education has led to the development of simulation programs and centers all around the world. Unfortunately, many of these centers are functioning as localized silos and not taking advantage of the potential for collaboration with other regional centers to promote interprofessional education. In the province of British Columbia (BC), Canada, 38 institutions, including health care authorities, universities, colleges, and other health-related organizations, have participated in assessing the use of simulation in BC and in developing a provincial model that enables collaboration and interprofessional learning at the provincial level.This article describes methods and results of a needs assessment and discusses an interprofessional simulation in health care educational model that provides access for all health care professionals in BC regardless of their geographic location and/or institutional affiliation. We anticipate that this information will be useful to and supportive of others in developing simulation collaborations in their respective regions.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.047
GPT teacher head0.423
Teacher spread0.377 · 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 designSimulation or modeling
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

Citations13
Published2012
Admission routes2
Has abstractyes

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Same venueSimulation in Healthcare The Journal of the Society for Simulation in HealthcareSame topicSimulation-Based Education in HealthcareFrench-language works237,207