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Record W2994418493 · doi:10.25071/1920-7336.40371

“Imposter-Children” in the UK Refugee Status Determination Process

2016· article· en· W2994418493 on OpenAlexaffvenue
Stephanie J. Silverman

Bibliographic record

VenueRefuge Canada s Journal on Refuge · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsRefugeeSafeguardingImmigrationThrivingMinor (academic)PoliticsPolitical scienceWelfareGender studiesCriminologySociologyPsychologyLawSocial scienceMedicine

Abstract

fetched live from OpenAlex

This article describes and analyzes an emerging problematic in the asylum and immigration debate, which I cynically dub the “imposter-child” phenomenon. My preliminary exploration maps how the imposter-child relates to and potentially influences the politics and practices of refuge status determination in the United Kingdom. I argue that the “imposter-child” is being discursively constructed in order to justify popular and official suspicion of spontaneously arriving child asylum-seekers in favour of resettling refugees from camps abroad. I also draw connections between the discursive creation of “imposter-children” and the diminishment of welfare safeguarding for young people. Further complicating this situation is a variety of sociocultural factors in both Afghanistan and the United Kingdom, including the adversarial UK refugee status determination process, uncertainty around how the United Kingdom can“prove” an age, and a form of “triple discrimination” experienced by Afghan male youth. Through unearthing why the “imposter-child” is problematic, I also query why it is normatively accepted that non-citizens no longer deserve protection from the harshest enforcement once they “age out” of minor status.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.290
Teacher spread0.280 · 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

Citations24
Published2016
Admission routes2
Has abstractyes

Explore more

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