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Record W1793302136 · doi:10.25071/1920-7336.21360

Unaccompanied/Separated Minors and Refugee Protection in Canada: Filling Information Gaps

2006· article· en· W1793302136 on OpenAlexvenueaboutno aff
Judith Wouk, Soojin Yu, Lisa Roach, Jessie Thomson, Anmarie Harris

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2006
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeCitizenshipImmigrationPlaintiffMinor (academic)CriminologyPopulationPolitical scienceLawPsychologyDemographySociology

Abstract

fetched live from OpenAlex

This paper fills information gaps with regard to unaccompanied/ separated minors in Canada. By the means of reviewing Citizenship and Immigration Canada administrative databases, it investigates how many unaccompanied/separated refugee minors exist, who they are, and how they are received in Canada.We found that there were fewer truly unaccompanied minors than previously reported. In the asylum stream, only 0.63 per cent (or 1,087) of the total claimant population were found to be unaccompanied by adults in the past five years. In the resettlement stream only two truly unaccompanied minors were resettled during 2003 and 2004. Regarding their socio-demographic characteristics, we found that unaccompanied minors compose a highly heterogeneous group from many different countries. Regarding how they were received in Canada, very little evidence existed. Our study found that unaccompanied and separated asylum-seeking minors showed a higher acceptance rate and quicker processing times than the adult population, but details about the minors’ actual reception into Canada remains to be further explored. This study recommends that Citizenship and Immigration Canada review its administrative databases with a view toward improving the data about separated/unaccompanied children. Consistent and detailed definitions are required to develop a comprehensive policy framework for unaccompanied/ separated minor refugees in Canada.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations15
Published2006
Admission routes2
Has abstractyes

Explore more

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