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Record W4404787505 · doi:10.22215/apb.v1i2.5012

Policing Strategies Adopted by Officers Working in Isolated Communities

2024· article· en· W4404787505 on OpenAlexaff
Noah Bennell

Bibliographic record

VenueApplied police briefings : · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsCarleton University
Fundersnot available
KeywordsCriminologyPublic relationsPolitical sciencePsychologySociology

Abstract

fetched live from OpenAlex

The research in the source article identified several distinct policing challenges in isolated communities, including problematic social issues and crime rates, strained community-police relations, harassment from the community, and excessive workload. Officers in isolated communities were found to rely on several unconventional policing methods compared to their counterparts in non-isolated communities and to emphasize problem-solving and adaptability to address the distinct challenges they encounter. The results of this research suggest an increased need for: (1) collaboration between community members, police professionals, and academic researchers to address policing challenges in isolated communities, (2) the recruitment of officers for isolated communities with greater flexibility in their policing style and an interest in non-enforcement related work, and (3) training that emphasizes the importance of community involvement for policing in isolated communities and imparts knowledge about the nature of policing in those communities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.036
GPT teacher head0.334
Teacher spread0.299 · 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
Published2024
Admission routes1
Has abstractyes

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