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Record W4302524800 · doi:10.25071/1913-5874/37349

Queer is in the Eye of the Newcomer: Mapping Performances of Place

2010· article· en· W4302524800 on OpenAlexaboutno aff
Liz Miller

Bibliographic record

VenueInTensions · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeQueerIdentity (music)Gender studiesSexual identityConventionInterpretation (philosophy)SociologyPreferenceState (computer science)PsychologySocial psychologyCriminologyMedia studiesPolitical scienceHuman sexualityAestheticsArtLawComputer scienceSocial science

Abstract

fetched live from OpenAlex

This article describes two collaborative media projects that work with groups of LGBTQ or queer youth with refugee experience in Toronto to explore alternative representations to the victimization they must perform in order to obtain refugee status. Canada has traditionally maintained a progressive interpretation of the UN Refugee Convention permitting individuals who are exposed to violence based on their sexual preference/identity to apply for asylum. At the same time the state works with essentialized Western notions of gay identity and the act of proving oneself often becomes a humiliating process. The objectives of the collaborative media projects are to challenge past performances of victimization, to help the youth involved articulate their identity in a new place, and to explore the advocacy potential in taking their personal stories public.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.117
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0050.006
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.029
GPT teacher head0.318
Teacher spread0.288 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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