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Record W4390952113 · doi:10.1108/pijpsm-09-2023-0111

Procedurally just policing and persons in behavioral crises: investigating public perceptions, stigma and emotion

2024· article· en· W4390952113 on OpenAlexaff
Sean Patrick Roche, Angela M. Jones, Ashley N. Hewitt, Adam D. Vaughan

Bibliographic record

VenuePolicing An International Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsVignettePsychologyAngerSocial psychologyMental illnessStigma (botany)PopulationOriginalityPerceptionCriminal justiceProcedural justiceValue (mathematics)CriminologyMental healthPsychiatryMedicine

Abstract

fetched live from OpenAlex

Purpose The police often respond to persons who are not in direct violation of the law, but are rather undergoing behavioral crises due to mental illness or substance abuse disorders. The purpose of this study is to examine how police behavior influences civilian bystanders' emotional responses and perceptions of procedural justice (PPJ) when officers interact with these populations, which traditionally have been stigmatized in American culture. Design/methodology/approach Using a factorial vignette approach, the authors investigate whether perceived public stigma moderates the relationship between police behaviors (i.e. CIT tactics, use of force) and PPJ. The authors also investigate whether emotional reactions mediate the relationship between police behaviors and PPJ. Findings Regardless of suspect population (mental illness, substance use), use of force decreased participants' PPJ, and use of CIT tactics increased PPJ. These effects were consistently mediated by anger, but not by fear. Interactive effects of police behavior and perceived public stigma on PPJ were mixed. Originality/value Fear and anger may operate differently as antecedents to PPJ. Officers should note using force on persons in behavioral crisis, even if legally justifiable, seems to decrease PPJ. They should weigh this cost pragmatically, alongside other circumstances, when making discretionary decisions about physically engaging with a person in crisis.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.000
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 head0.148
GPT teacher head0.458
Teacher spread0.310 · 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 designObservational
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

Citations2
Published2024
Admission routes1
Has abstractyes

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