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Record W2793548578 · doi:10.1097/sih.0000000000000284

Establishing a Virtual Community of Practice in Simulation

2018· article· en· W2793548578 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 · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsAlberta Children's HospitalSaskatchewan Health AuthorityUniversity of SaskatchewanUniversity of Calgary
Fundersnot available
KeywordsStatement (logic)Instructional simulationSocial mediaCommunity of practiceComputer sciencePassionVirtual communityBest practiceEngineering ethicsMultimediaPublic relationsSociologyPsychologyWorld Wide WebEngineeringPedagogyHuman–computer interactionVirtual realityThe InternetPolitical science

Abstract

fetched live from OpenAlex

STATEMENT: Professional development opportunities are not readily accessible for most simulation educators, who may only connect with simulation experts at periodic and costly conferences. Virtual communities of practice consist of individuals with a shared passion who communicate via virtual media to advance their own learning and that of others. A nascent virtual community of practice is developing online for healthcare simulation on social media platforms. Simulation educators should consider engaging on these platforms for their own benefit and to help develop healthcare simulation educators around the world. Herein, we describe this developing virtual community of practice and offer guidance to assist educators to engage, learn, and contribute to the growth of the community.

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)0.021
metaresearch head score (Gemma)0.044
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
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 score0.198
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.141
GPT teacher head0.487
Teacher spread0.346 · 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