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Record W3131428175 · doi:10.1080/09687637.2021.1872500

Factors contributing to frequent police contact among young people: a multivariate analysis including homelessness, community visibility, and drug use in British Columbia, Canada

2021· article· en· W3131428175 on OpenAlexaffabout
Alissa Greer, Marion Selfridge, Kiffer G. Card, Cecilia Benoit, Mikael Jansson, Zina Lee, Scott Macdonald

Bibliographic record

VenueDrugs Education Prevention and Policy · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of the Fraser ValleyUniversity of VictoriaSimon Fraser University
Fundersnot available
KeywordsDemographicsBivariate analysisMultivariate analysisDemographyMetropolitan areaRace (biology)ConfoundingGeographyPsychologyMedicineGerontologySociologyGender studies

Abstract

fetched live from OpenAlex

There is increasing recognition and attention towards the patterns of police encounters with citizens. In this study, we examine the determinants of being stopped and questioned by the police among a heterogenous sample of adolescents and young adults, who were either people who use drugs and a comparison group, in three non-metropolitan areas of British Columbia, Canada. We conducted bivariate and multivariate analyses to identify the unique variation of frequent police encounters based on demographic characteristics and potential confounders. Of 448 young people, 92.0% reported at least one event where police stopped and questioned them in the past five years, and half (49.8%) reported frequent (four or more) police encounters in this time frame. The demographics of race, age, and gender were not significant in the analyses, whereas weekly illicit drug use, homelessness, and high visibility in the community were significantly related to frequent police encounters. Findings suggest that, controlling for demographic variables, young people who have precarious housing, use drugs, and have higher community visibility are at higher risk of police contact. Our findings also show when street involvement and drug use are controlled for, race does not determine police encounters.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.038
GPT teacher head0.395
Teacher spread0.358 · 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

Citations11
Published2021
Admission routes2
Has abstractyes

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