(A156) Performance Indicators: Technical, Physical and Mental Readiness
Bibliographic record
Abstract
The purpose of this presentation is to report the results from a series of standardized exercises administered to experienced, disaster-emergency-responders on their “operational readiness.” Based on original research with Olympic athletes, these results include: a frontline-perspective of challenges in a disaster; a quantitative definition of “readiness;” and the creation of related performance indicators. A growing body of literature has drawn attention to the significance of mental-readiness skills in attaining peak performance in challenging situations. For example, we know that top-level athletes have particularly well-honed mental-readiness skills and that this fact has often separated those who win a gold medal from those who do not. In recent years, this research has been extended to other occupations, including the field of surgery, policing, and now disaster-emergency-response, and similar results were found. For example, in the study entitled “Gold Medal Policing: Mental Readiness and Performance Excellence” (McDonald, 2006), peak-performing police officers demonstrated excellent technical and physical skills but excelled in mental readiness skills. Traditionally, the focus of most core-competencies has been on the technical and physical skills necessary to perform the duties. Given what we now know about the significance of mental-readiness skills, we can specifically develop and formally recognize these skills. That is, in addition to seeking the technical and physical skills required of a job, particular emphasis is places on refining the mental skills that ultimately makes the difference between satisfactory performance and peak performance. The goal of any field-training, is to produce a competent, independent, functioning frontline-responder. Such a responder will demonstrate concrete, observable “performance indicators.” Current research on peak performers has been integrated into developing comprehensive performance indicators. This outcome can benefit the recruitment, selection, training and evaluation of professions seeking to enter into the unique world of disaster emergency medicine.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".