International Emergency Medical Teams Training Workshop Special Report
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
The World Health Organization's (WHO; Geneva, Switzerland) Emergency Medical Team (EMT) Initiative created guidelines which define the basic procedures to be followed by personnel and teams, as well as the critical points to discuss before deploying a field hospital. However, to date, there is no formal standardized training program established for EMTs before deployment. Recognizing that the World Association of Disaster and Emergency Medicine (WADEM; Madison, Wisconsin USA) Congress brings together a diverse group of key stakeholders, a pre-Congress workshop was organized to seek out collective expertise and to identify key EMT training competencies for the future development of training programs and protocols. The future of EMT training should include standardization of curriculum and the recognition or accreditation of selected training programs. The outputs of this pre-WADEM Congress workshop provide an initial contribution to the EMT Training Working Group, as this group works on mapping training, competencies, and curriculum. Common EMT training themes that were identified as fundamental during the pre-Congress workshop include: the ability to adapt one's professional skills to low-resource settings; context-specific training, including the ability to serve the needs of the affected population in natural disasters; training together as a multi-disciplinary EMT prior to deployment; and the value of simulation in training. AlbinaA, ArcherL, BoivinM, CranmerH, JohnsonK, KrishnarajG, ManeshiA, OddyL, Redwood-CampbellL, RussellR. International Emergency Medical Teams training workshop special report. Prehosp Disaster Med. 2018;33(3):335-338.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.033 | 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