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Record W2744583484 · doi:10.14288/cl.v0i227.187792

"Paul Wong and Refugee Citizenship"

2016· article· en· W2744583484 on OpenAlexaffabout
Donald C. Goellnicht

Bibliographic record

VenueOpen Collections · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRefugeeCitizenshipRacismGender studiesNationalismAgency (philosophy)ComplicityFace (sociological concept)State (computer science)MulticulturalismIdentity (music)SociologyNationalityPoliticsNational identityPolitical scienceImmigrationLawSocial scienceAesthetics

Abstract

fetched live from OpenAlex

At the start of the millennium, Vancouver-based video artist Paul Wong was commissioned by the Canadian Race Relations Foundation, a state-funded agency, to make a series of brief public service announcements for television, which he titled Refugee Class of 2000 and which form part of the CRRF’s “See People for Who They Really Are: Unite Against Racism” campaign.In the three brief videos, Wong brings the viewer face to face with students from the graduating class at Charles Tupper High School in Vancouver, while also exhuming the history of racism and racist exclusion in Canada. This paper examines the subtle ways in which Wong, working for a state-funded agency, negotiates the complex balancing act between complicity and critique in dealing with issues of national belonging, official multiculturalism, racism, identity politics, citizenship, and transnational or diasporic identity in Refugee Class of 2000. It argues that in Wong’s form of Asian Canadian critique, the transnational identities of the refugee subjects—not all of whom are Asian, and not all of whom are refugees by conventional definitions—bring pressure to bear on nationalist concepts of citizenship and belonging, insisting on the paradoxical notion of refugee citizenship as an alternative to conventional concepts of national belonging.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.228
Threshold uncertainty score0.999

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 studies0.0040.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.314
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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes2
Has abstractyes

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