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Record W4414119640 · doi:10.22215/apb.v2i1.4984

Comparing Police Decision-Making Errors and Stress Arousal During Video and Live Requalification Scenarios

2025· article· en· W4414119640 on OpenAlexaffabout
Judith P. Andersen, Paula M. Di Nota

Bibliographic record

VenueApplied police briefings : · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPopularityPresentation (obstetrics)Virtual realityArousalStress (linguistics)

Abstract

fetched live from OpenAlex

Despite the popularity in virtual reality (VR) simulation systems, there is a lack of research investigating how the presentation simulations (live vs. video) impact police performance. The research examined lethal force decision-making and heart rate (HR) among 187 Canadian police officers completing their annual re-qualification evaluation, which involved both live reality-based scenarios and video-based simulations that were projected onto a wall. Officers made more lethal force errors and had lower maximum heart rate during the video simulations compared to the live ones, which has implications for how officers are trained and evaluated. Before investing limited funding on virtual simulation training to enhance performance in highpressure situations, police agencies should consider the findings reported in this research.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.348
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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