Interprofessional collaboration among first responder students in a simulated disaster exercise
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.
Bibliographic record
Abstract
INTRODUCTION: Interprofessional disaster simulation exercises provide an opportunity for first responder students to learn about disaster response and recovery, to practice their roles and to learn to collaborate with other first responders. With the move to virtual education during the COVID-19 pandemic, a table-top disaster exercise is an alternative format to inperson exercises. To date, most disaster simulation exercises for students have focused on the roles of healthcare providers. As first responders play a critical role in disaster management, there is a need for interprofessional exercises that include students in first responder programs. METHODS: A table-top disaster simulation exercise was held with students from the police (n = 94) and firefighter (n = 30) programs at a large community college in Toronto, Canada, in February 2021. It was held virtually using the Zoom® platform, with college faculty as well as professionals from community partner sites. An evaluation survey that had open- and closed-ended items was administered to students following the event. RESULTS: Thirty-eight percent of the students participated in the survey, and the majority rated the event highly useful and reported that the exercise demonstrated the importance of interprofessional collaboration. Students' responses to the open-ended survey items yielded two themes: understanding roles and performing under duress. DISCUSSION: This evaluation demonstrates the value of using a simulated disaster exercise to teach first responder students about their role in disaster response and recovery, and the importance of interprofessional collaboration.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it