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Record W2322007582 · doi:10.1097/sih.0000000000000077

Co-debriefing for Simulation-based Education

2015· article· en· W2322007582 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2015
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsDebriefingContext (archaeology)ToolboxMedical educationPsychologyHealth careMedicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

STATEMENT: As part of simulation-based education, postevent debriefing provides an opportunity for learners to critically reflect on the simulated experience, with the goal of identifying areas in need of reinforcement and correcting areas in need of improvement. The art of debriefing is made more challenging when 2 or more educators must facilitate a debriefing together (ie, co-debriefing) in an organized and coordinated fashion that ultimately enhances learning. As the momentum for incorporating simulation-based health care education continues to grow, the need for faculty development in the area of co-debriefing has become essential. In this article, we provide a practical toolbox for co-facilitators by discussing the advantages of co-debriefing, describing some of the challenges associated with co-debriefing, and offering practical approaches and strategies to overcome the most common challenges associated with co-debriefing in the context of simulation-based health care education.

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.

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)0.006
metaresearch head score (Gemma)0.004
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 score0.316
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.101
GPT teacher head0.450
Teacher spread0.349 · 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