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Record W4391637644 · doi:10.32920/25193519.v1

Unaccompanied Refugee Youth: Their Migration, Maturity, and Best Interests

2024· preprint· en· W4391637644 on OpenAlexaffabout
Raymond G. McCarthy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcMaster UniversityToronto Metropolitan University
Fundersnot available
KeywordsRefugeeImmigrationCompetence (human resources)ConventionPolitical scienceMaturity (psychological)Refugee lawLawPsychologySocial psychology

Abstract

fetched live from OpenAlex

In this Major Research Paper (MRP), I address the issue of unaccompanied refugee minors (URMs) who are adolescents between the ages of 14 and 18. Canada’s immigration and refugee board (IRB) and immigration officials rely on the convention on the rights of the child (CRC) as well as Canadian guidelines pertaining to age and, to a lesser degree, competence are used as the two main indicators of the child's capacity to be mature, reasonable, and independent before, during, and after their migration process. This can result in URMs being assessed as incompetent and incapable. It is not the purpose to argue that URMs should not be given all the rights of children, as they are minors. Rather, I argue that specific Articles of the UNHCR’s Convention on the Rights of the Child limit the recognition of the decision-making ability of unaccompanied refugees in their process of development into adulthood by ignoring the way their migration experiences speed and enhance their maturation. Therefore, I conclude that the maturity and capability of URMs should be properly assessed in a more sophisticated process, one to be developed through further research, a process that will afford them an opportunity to make clear what they deem best for themselves and why, rather than one that assigns them to the protocols appropriate for “children”.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0010.003
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 head0.056
GPT teacher head0.353
Teacher spread0.297 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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