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Record W4399125852 · doi:10.3390/laws13030034

Child Welfare, Immigration, and Justice Systems: An Intersectional Life-Course Perspective on Youth Trajectories

2024· article· en· W4399125852 on OpenAlexafffundabout
Marsha Rampersaud, Kristin Swardh, Henry Parada

Bibliographic record

VenueLaws · 2024
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsToronto Metropolitan UniversityYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLife course approachPsychological resilienceSociologyImmigrationCriminologyWelfareDeportationPerspective (graphical)Economic JusticeCriminal justicePolitical scienceSocial psychologyPsychologyLaw

Abstract

fetched live from OpenAlex

This study explores how racialized migrant youth navigate Ontario’s child welfare, criminal justice, and immigration systems. Insights from youth, academics, practitioners, lawyers, policymakers, and social workers were gathered from a conference and contextualized using the Intersectional Life Course Theory and a critical phenomenological framework. Our analysis focuses on timing, locally and globally linked lives, social identities, and resilience, and emphasizes the interconnectedness of individual experiences within societal structures. We review systemic challenges and ethical dilemmas for young migrants, particularly concerns about fairness in potential inadmissibility or deportation consequences. We propose systemic support measures to foster resilience and disrupt adverse trajectories in order to mitigate discriminatory practices and provide targeted support for youth within these systems.

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)0.002
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 score0.372
Threshold uncertainty score0.740

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.007
Scholarly communication0.0060.004
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.297
Teacher spread0.278 · 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

Citations2
Published2024
Admission routes3
Has abstractyes

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