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Record W2044298617 · doi:10.1075/jls.3.1.03ric

Testimonies of LGBTIQ refugees as cartographies of political, sexual and emotional borders

2014· article· en· W2044298617 on OpenAlexaffabout
Nathalie Ricard

Bibliographic record

VenueJournal of Language and Sexuality · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRefugeeDeportationPersecutionQueerLiminalityGrassrootsSexual orientationHuman sexualityGender studiesCriminologyPoliticsEthnographyImmigrationEconomic JusticePolitical scienceIdentity (music)SociologyLawAnthropology

Abstract

fetched live from OpenAlex

To be granted status, refugee claimants have to testify at the Immigration and Refugee Board of Canada (IRB). This liminal space is charged with both the promise of liberation and the threat of deportation. Adding to the challenge are the governmental measures that constrain the right to asylum. This paper suggests answers to the question: What language and other discursive features do LGBTIQ claimants have to use to be recognized as refugees? This ethnography is based on fieldwork conducted in Toronto and Vancouver. I will present two vignettes of claimants I accompanied to their hearings. Contrary to heterosexuals, queer asylum seekers have to prove their sexual orientation and/or their gender identity. Truth about their sexuality and persecution is evaluated through the lens of legal technologies, and stereotypes are still common. However, extralegal forms of communication also come into play. New avenues for justice are being fostered by grassroots organizations.

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)0.010
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0170.008
Scholarly communication0.0040.003
Open science0.0010.008
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.342
Teacher spread0.330 · 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

Citations7
Published2014
Admission routes2
Has abstractyes

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