An evidence-based approach to critical incident scenario development
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
Purpose There has been an increasing emphasis on developing officers who can effectively make decisions in dynamic and stressful environments to manage volatile situations. The aim of this paper is to guide those seeking to optimize the limited resources dedicated to police training. Design/methodology/approach Drawing on research related to stress exposure training, principles of adult learning, the event-based approach to training and policing more broadly, the authors show how carefully crafted training scenarios can maximize the benefits of police training. Findings The authors’ review highlights various training principles that, if relied on, can result in scenarios that are likely to result in the development of flexible, sound decision-making skills when operating under stressful conditions. The paper concludes with an example of scenario development, which takes the reviewed principles into account. Originality/value The authors hope this discussion will be useful for police instructors and curriculum designers in making evidence-informed decisions when designing training scenarios.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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