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Microcosms of violence among street gang members: Social contagion, propensity to violence, and gang embeddedness

2025· article· en· W4409383554 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Criminal Justice · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsSt. Joseph’s Healthcare HamiltonUniversité Laval
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEmbeddednessCriminologySuicide preventionPoison controlHuman factors and ergonomicsInjury preventionOccupational safety and healthMedical emergencyPsychologySociologyMedicineSocial science

Abstract

fetched live from OpenAlex

Gang members face a paradox: while they may join a gang for protection from violence, they are actually more likely to be victimized than non-gang members. Although it is known that gang affiliation increases the risk of violence perpetration and victimization, little is understood about the factors within gangs that influence these risks. This study examines the relationship between violent perpetration and victimization within the context of gang networks. Using 20 years of police data, we mapped the incidents of violent victimization and perpetration among 1587 Haitian street gang members and their affiliates in Montreal, Canada. Our results show that violence occurs in clusters within these groups and that victimization and perpetration are more likely to happen in the same locations within the network. Regression models revealed that victimization was strongly related to: (1) having committed violence, (2) having more violent perpetrators in one's entourage, and (3) having more victims in one's entourage. These three effects were interdependent, creating a mutual aggravation effect: members who had perpetrated high levels of violence, high levels of victimization in their network, and who had violent peers were 15 times more victimized than members who were not directly or indirectly involved in violence. The structure of peer relationships was also important. Denser networks provided some protection against victimization, but this was dependent on members' own level of violence. Violent perpetrators did not benefit from the protection offered by a close-knit network. Our findings show that violence within gangs is not equally distributed and is concentrated in certain areas of the network. Perpetration and victimization are linked, and the local density of the network can reduce the impact of violence in the network. Thus, the idea that gangs can provide protection may not be as paradoxical as it seems. In tightly knit groups, and for members not directly involved in violence, gang affiliation did not increase violence risk. This understanding may improve targeted interventions to prevent both the experience and commission of violence. • Violence within gangs tends to occurs in clusters. • Victimization and perpetration of violence occur in the same areas of the network. • Violence, perpetrated and sustained, among peers creates a mutual aggravation effect. • In some circumstances, denser gang networks offer protection against victimization.

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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)0.001
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 score0.296
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.027
GPT teacher head0.325
Teacher spread0.298 · 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