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Record W4414265855 · doi:10.1177/0032258x251379229

Reasonability-of-force assessments mediate the link between police experience and use-of-force decision making

2025· article· en· W4414265855 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Police Journal Theory Practice and Principles · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsCalgary Laboratory Services
FundersBureau of Justice Assistance
KeywordsInterrogationProcedural justiceFirst responderHuman factors and ergonomicsTraining (meteorology)Interview

Abstract

fetched live from OpenAlex

We examined if experienced officers use less and lower levels of force than less-experienced officers due to differences in reasonability-of-force assessments. Officers observed body-camera videos involving use-of-force, indicated their course of action, and the extent to which several factors were relevant in determining appropriate use-of-force. Experienced officers were more likely to use verbal commands and less-experienced officers were more likely to use less-lethal and lethal force. This was mediated by available force mitigation opportunities, nearby weapons, and the subject’s likelihood of escape. Results inform the skills involved in and training that reinforces expert use-of-force decision making performance.

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 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)0.009
metaresearch head score (Gemma)0.005
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 score0.315
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.122
GPT teacher head0.465
Teacher spread0.344 · 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