Does use-of-force simulation training in Canadian police agencies incorporate principles of effective training?
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
Numerous police agencies in Canada incorporate use-of-force simulation training into their overall instructional regime. A prominent theory of learning, known as cognitive load theory, suggests that in order for this training to be effective, instructional methods must facilitate the acquisition and automation of task-relevant schemas without overwhelming the limited processing capacity of the learner. In this article, several instructional effects, proposed and supported by the cognitive load literature, are discussed. These training effects operate by minimizing unnecessary cognitive demands, by drawing on instructional methods that enhance schema acquisition, and/or by carefully managing the inherent complexity of the to-be-learned material. The argument is advanced that although use-of-force simulation training may be able to capitalize on many of these effects, at present there is little evidence to suggest that it currently does. The authors conclude by discussing the urgent need to assess how the knowledge gained from cognitive load theory might serve to enhance the effectiveness of use-of-force simulation training.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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