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Record W2619918085 · doi:10.7202/1039805ar

L’adhésion à la culture de gang

2017· article· fr· W2619918085 on OpenAlexaffvenueabout
Manuelle Bériault, Catherine Laurier, Jean‐Pierre Guay

Bibliographic record

VenueCriminologie · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsInternational Centre for Comparative CriminologyUniversité de MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La présence accrue de jeunes faisant partie de groupes ethnoculturels minoritaires dans les institutions pour jeunes contrevenants au Québec est une problématique complexe et préoccupante. Cette étude explore le rôle de l’identité ethnique et du fait de faire partie d’un groupe de minorités racisées dans l’association autorévélée à un gang de rue et dans l’adhésion à la culture de gang. Les participants (n = 69 ; âge 14-20 ans) ont été recrutés dans des centres de réadaptation de la région montréalaise. Il ressort des résultats que le fait de se reconnaître membre d’un gang de rue ne diffère pas entre les jeunes issus des minorités racisées et ceux qui n’en sont pas issus. Les analyses de régressions multiples effectuées révèlent que plus un jeune contrevenant rapporte un niveau d’exploration de l’identité ethnique élevé, plus il adhère aux dimensions signes et symboles et règles et rituels de l’adhésion à la culture de gang, et ce, peu importe son âge ou qu’il fasse partie d’un groupe de minorités racisées. Cette étude fait ressortir l’importance de s’intéresser aux questions identitaires lors d’interventions auprès de jeunes contrevenants, et ce, peu importe leurs origines.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.465
Threshold uncertainty score0.935

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.007
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.336
GPT teacher head0.392
Teacher spread0.057 · 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 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

Citations3
Published2017
Admission routes3
Has abstractyes

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