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Record W4238746938 · doi:10.32920/ryerson.14644023

Newcomer youth: how integration pitfalls may lead to participation In illegal activities

2021· preprint· en· W4238746938 on OpenAlexaff
Zainab Godwin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicGlobal Political and Social Dynamics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsJuvenile delinquencySettlement (finance)CriminologyEconomic JusticeCriminal justiceSocial integrationWork (physics)Political sciencePublic relationsSociologyBusinessLawEngineering

Abstract

fetched live from OpenAlex

Newcomer youth’s migration and integration experience is a topic with depths that are yet to be discovered. However, to enhance the integration experience, it is crucial that we look into the existing pathways and barriers to successful integration. Through a combination of primary research with 2 staff who work with newcomer youth in conflict with the law and 2 additional studies discussing integration barriers for newcomer youth, this study analyzes the systemic and individual barriers that may further marginalize newcomer youth and potentially result in their involvement in illegal/delinquent behaviours. Utilizing multiple theoretical frameworks, the research concludes that through gaps in the system (especially the education system), newcomer youth are vulnerable to illegal and delinquent behaviours as they settle and integrate in their new home country. Keywords: Newcomer youth, barriers, settlement, integration, criminal justice system, delinquency, illegal activities.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.002
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 head0.067
GPT teacher head0.368
Teacher spread0.301 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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