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Record W4384382747 · doi:10.32920/23676624

Conceptualizing the best interests of the unaccompanied child in Canadian immigration law

2023· preprint· en· W4384382747 on OpenAlexaffabout
Shannon E. Martin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsLegislationImmigrationBest interestsPolitical scienceConventionLawRefugeeConvention on the Rights of the ChildGovernment (linguistics)Immigration policyImmigration lawPublic administrationHuman rights

Abstract

fetched live from OpenAlex

This major research study explores the “best interests of the child†principle as codified by the Canadian federal government in relation to unaccompanied minors seeking asylum in Canada. Employing a qualitative content analysis design informed by an interest theory lens, this study examines two international policies and one national policy to compare how the best interests of the unaccompanied migrant child are conceptualized at each level. The research seeks to answer the following two questions: (1) how are the “best interests of the child† conceptualized for unaccompanied minors in Canadian immigration legislation? and (2) how does Canadian immigration legislation concerning the best interests of the unaccompanied migrant child compare to international legal instruments? The findings demonstrate that the best interests of the child are incompletely and poorly conceptualized within Canadian immigration legislation, highlighting the imbalance between the focus on immigration control and child protection in Canada. Key words: unaccompanied minor, best interests of the child, United Nations Convention on the Rights of the Child, Immigration and Refugee Protection Act

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.968

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0290.049
Scholarly communication0.0110.005
Open science0.0030.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.063
GPT teacher head0.355
Teacher spread0.292 · 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 designTheoretical or conceptual
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
Published2023
Admission routes2
Has abstractyes

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