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Record W4413017220 · doi:10.22215/etd/2025-16681

Feeling Blue: the Impact of Body-Worn Cameras on Police Officers' Well-Being During Investigations of Misconduct

2025· dissertation· en· W4413017220 on OpenAlexaff
Andrew Brown

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsCarleton University
Fundersnot available
KeywordsMisconductFeelingPsychologyApplied psychologySocial psychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Police misconduct investigations are critical to maintaining public trust and keeping law enforcement agencies accountable. Still, they can be prolonged, stressful processes for the subject officers (and complainants) involved. Through three interrelated studies, the current dissertation makes two important contributions to the research literature-it highlights police misconduct as a salient stressor in policing and it draws attention to the potential use of body-worn cameras (BWCS) as a mental wellness tool. Study 1 employs a vignette-based experimental design to examine how misconduct allegation severity, allegation truthfulness, and BWC presence influence expected officer stress in the ensuing misconduct investigation, confidence in the available evidence, expected investigation duration, and the likelihood of a guilty verdict being reached. Findings suggest that officers expect lower stress levels, particularly in cases where the misconduct allegations are false, higher confidence in the evidence, and shorter investigations when BWC footage is available. Study 2 utilizes semi-structured interviews with officers who have been involved in misconduct investigations. This study provides qualitative insights into the lived experiences of officers, highlighting the chronic stress, uncertainty, and moral injury they endure as a result of an allegation or investigation of misconduct. Officers described investigative delays and a lack of procedural transparency as stressors within the complaints process and viewed BWCs as a potential tool for reducing ambiguity, expediting case resolution, and enhancing officer wellness. Study 3 shifts focus to public perceptions of police misconduct investigations, oversight mechanisms, and the role of BWCs in investigations. Using a nationwide survey, this study finds a public preference for civilian oversight models. However, this preference lessened when participants scored higher on perceptions of police legitimacy. The public also recognizes the stress experienced by both officers and complainants involved in misconduct investigations and largely supports BWCs as a mechanism for transparency and efficiency.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.391
Teacher spread0.356 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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 routes1
Has abstractyes

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