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Record W4244783284 · doi:10.32920/ryerson.14648787

"What's Up With All these Walls?" : Racialized Lesbian/Queer Women Immigrants and Belonging in Toronto

2021· preprint· en· W4244783284 on OpenAlexaffabout
Sheila C.S Pardoe

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsQueerGender studiesLesbianScholarshipImmigrationMainstreamSociologyContext (archaeology)Subject (documents)Queer theoryPolitical scienceHistoryLaw

Abstract

fetched live from OpenAlex

Despite government and scholarly interest in how Canada's immigrants settle after arrival, there is limited scholarship on how queer female immigrants find spaces for belonging in a Toronto context in both immigration scholarship, and in theories of queer migration. Drawing on critical queer, critical post-colonial feminist, and critical whiteness approaches, the paper aims to demonstrate why a universal subject, and increasingly, a universal queer subject renders a racialized lesbian/queer woman immigrant living in Toronto marginalized, impossible and unintelligible in mainstream and queer spaces. For the study, three racialized lesbian/queer women immigrants living in Toronto were interviewed. A reflexive analysis of the experiences of the three participants suggests that spaces of belonging for a racialized lesbian/queer woman immigrant in Toronto and beyond are limited, contradictory, and conditional.

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)0.002
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 score0.078
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0370.018
Scholarly communication0.0060.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.314
Teacher spread0.297 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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