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Record W2596550903 · doi:10.1108/pijpsm-06-2016-0080

Gender differences in understanding police perspectives on crowd disorder

2017· article· en· W2596550903 on OpenAlexaffabout
Stephanie E. Dawson, Garth Davies

Bibliographic record

VenuePolicing An International Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCrowdsPerspective (graphical)Context (archaeology)OfficerOriginalityPsychologyPerceptionSocial psychologyValue (mathematics)CriminologyApplied psychologyPolitical scienceComputer securityComputer scienceGeography

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to examine the nature and dynamics of crowd disorder from the perspective of the police in a Canadian context, as well as to extend this perspective to include the opinions of female police officers. Design/methodology/approach A total of 460 Vancouver police officers participated in this study. Following the 2011 Stanley Cup riot, police officers received mail-based questionnaires focussed on gathering information concerning police perceptions of the crowd and the police response in riot situations. A total of 15 response items were analysed using descriptive approaches and confirmatory factor analyses. Findings The study findings revealed that, in addition to being multidimensional, the police perspective of crowd disorder may be contingent upon certain officer characteristics. Although, the police perspective can generally be categorized by four overarching constructs: dichotomous crowd, homogeneous threat, strict policing and tactical response; it becomes more complex once the officers’ gender is taken into consideration. The results suggest that the male and female police officers may have some differing views about the nature of crowds and the type of police response required to manage disorderly crowd situations. Originality/value In addition to being the first study to analyse police perceptions of crowd disorder in a Canadian context, this research is the first to include the points of view of female officers.

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 categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.230
GPT teacher head0.464
Teacher spread0.234 · 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

Citations4
Published2017
Admission routes2
Has abstractyes

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