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Record W4414180578 · doi:10.1192/j.eurpsy.2025.804

“Hidden” Voices Marginalised community perspectives on policing and community safety; an international scoping systematic review

2025· article· en· W4414180578 on OpenAlexaboutno aff
Lucinda Jordan, G. Mitu Gulati, Colum Dunne, Brendan D. Kelly, Mary Donnelly

Bibliographic record

VenueEuropean Psychiatry · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsLaw enforcementPsychological interventionRefugeeLatin AmericansEnforcementWork (physics)Scopus

Abstract

fetched live from OpenAlex

Introduction Community safety is about everyone having the right to be and feel safe in their community. People from marginalised communities (including people with mental illness, intellectual disability, migrants, and homeless) are over-represented in policing contacts. Yet, little is known about the real world perspectives of these marginalised groups in respect of perceived safety and interventions that work to improve this. Objectives To systematically review the published literature concerning the experiences of people from marginalised communities on policing and community safety. Methods Research database SCOPUS (inception to 1 January 2024) was searched for English-language publications using key words. The electronic search was augmented by manual searching through reference lists and websites of governmental and non-governmental organisations. Published studies with information about the experiences of persons from marginalised communities on policing and community safety were included. Opinion articles or reviews that did not contain qualitative data were excluded, as were studies that focused on law enforcement professionals views. Results Of the 857 papers identified, 17 studies met eligibility criteria with a total of 1254 participants from 5 countries. A recurring theme from different marginalised communities was “greater fear” and “less trust” of police and a reluctance to report crime. Those with physical disabilities were less likely to use public transport. Latin migrants feared speaking Spanish in America. African refugees in Australia felt targeted by the police because of their ethnicity. Muslims in England reported they were under increased police surveillance. Homeless youths in Canada with early negative experiences with law enforcement personnel were less likely to seek police involvement if needed in future. Conversely both Mexican-origin residents and Chinese immigrants living in America identified police as having a critical role in making them feel safe. Conclusions This study scoped the experiences of people from marginalised communities in respect of policing and community safety. To the author’s knowledge, this is the largest scoping study of this type, to date. It is evident from this review that there are voices, sometimes “hidden voices”, from marginalised communities that perceive policing approaches differently. This guides not only their future interactions with police but also their social outlook. Working closely and proactively with individuals within these marginalised communities will help find the balance between “over policing” and “under policing” to help contribute to the overall community safety. A key recommendation from this review would be for authorities to meaningfully incorporate these voices when developing or reviewing policies relating to community safety. Disclosure of Interest None Declared

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.106
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.028
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.106
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0220.018
Science and technology studies0.0020.004
Scholarly communication0.0080.008
Open science0.0020.006
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.046
GPT teacher head0.399
Teacher spread0.354 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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