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Record W4308813968 · doi:10.1002/symb.621

Police Accounts of Body‐Worn Camera Footage In News Media

2022· article· en· W4308813968 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

VenueSymbolic Interaction · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsBrandon University
Fundersnot available
KeywordsAccountabilityLegitimacyContext (archaeology)Public relationsExploratory researchPolitical sciencePsychologySociologySocial psychologyLawHistoryPolitics

Abstract

fetched live from OpenAlex

People offer accounts in response to actions that are subjected to valuative inquiry. Recordings of police actions captured on body‐worn camera (BWC) video can become subject to valuative inquiry when footage is publicly released. This footage may possibly undermine police legitimacy. Managing legitimacy is a basic rationale for why police provide accounts in response to their conduct. Proponents of BWCs assert that the devices enhance legitimacy and, while police have long used accounts to justify their conduct, less is known about how body cameras affect police accountability in practice. Drawing from Scott and Lyman's accounts theory framework, this qualitative, exploratory study examines official police accounts as both outcomes of police accountability in practice and as provided in the context of news media coverage of publicly released body‐worn camera footage. This allows us to ask the following questions: What types of accounts have police officials provided in news media reports in the context of publicly released BWC footage? And, more generally, what insight might an analysis of police accounts provide about accountability in relation to the implementation of BWCs? A key finding reveals that the timing of police accounts varied quite considerably, and that accounts were usually not static. The findings provide some general insight into what kinds of actions captured on body camera recordings constitute acceptable use of force by officers, even in situations when police actions resulted in death. This study also provides a small empirical window into when and how police officials provide accounts in response to publicly released body camera footage.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.379
Teacher spread0.338 · 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