MétaCan
Menu
Back to cohort

Comparision and Contrast between Police and Medical Simulation

2006· letter· en· W2333726705 on OpenAlexaffabout
Darren Hudson, Dave Berry

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2006
Typeletter
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDebriefingSession (web analytics)PsychologyResource (disambiguation)Health careSeniorityMedical educationApplied psychologyComputer scienceMedicineSocial psychologyEngineeringPolitical science

Abstract

fetched live from OpenAlex

To the Editor: Recently I (D.H.) had an opportunity to observe and participate in simulation exercises with the Edmonton City Police Tactical Team. The exercises were part of the regular training for new recruits into the Tactical Team program. Each recruit is a member of the Edmonton City Police force with an average of 7 years seniority. These exercises and particularly the debriefing session demonstrated many similarities with medical simulation. The group leaders are interested and dedicated officers with previous tactical experience who also oversee all other aspects of the training program. Each simulation scenario started with a prebriefing followed by the exercise. The debriefing was a group activity with all participants standing in a circle to facilitate expression of opinion. The scenario and performance was reviewed in detail step by step. When issues were identified, the group discussed alternatives and repeated key steps to ensure the learning objectives were met. The main themes throughout the debriefing session mirrored crisis resource management issues addressed in healthcare. The majority of the session was spent discussing knowledge and reasoning deficits, resource allocation, fixation errors, and problems with priority formation. I did observe several differences in the debriefing session I attended versus those in healthcare Crisis Resource Management courses I have seen. The Tactical Team leaders were more critical and less supportive of learner errors. No time was spent familiarizing the learners with the concept of simulation nor was there any discussion about the deficiencies in the simulation. In other words, complete familiarity and acceptance of simulation by the trainees is assumed by their instructors. As Edmonton City Police officer are exposed to simulated training situations throughout their career and, by the time they come to the Tactical Team, they are conditioned to automatically treat the simulation as reality. This experience reinforces that issues and themes in medical simulation cut across other professions and their simulations, not just aviation. Pioneers of simulation in medicine have widely acknowledged that they borrowed the ideas and techniques from other domains, and practitioners of simulation in healthcare should continue looking to other professionals for collaboration and ideas. Darren Hudson, BSc (Hons), MD, FRCP Dave Berry From the Department of Critical Care Medicine, University of Alberta (D.H.) and the Edmonton Police Service Tactical Team Unit (D.B.), 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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.564
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.005
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 head0.058
GPT teacher head0.412
Teacher spread0.354 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2006
Admission routes2
Has abstractyes

Explore more

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