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Record W7117299580 · doi:10.1177/17506980251397837

The nation on the Catwalk: Traveling memories of belonging in the Miss Kiev Pageant in Winnipeg (1979–1984)

2025· article· en· W7117299580 on OpenAlexaboutno aff
Elisa Lucente

Bibliographic record

VenueMemory Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
FundersUniversità degli Studi di Pavia
KeywordsMulticulturalismContext (archaeology)UkrainianSituatedRhetoricCultural memoryMode (computer interface)National Identities

Abstract

fetched live from OpenAlex

This article examines how ethnic, national, and diasporic belonging were negotiated through the Miss Kiev pageant in Winnipeg. Drawing on 27 contestant entry forms from 1979 to 1984, preserved in the Sylvia Todaschuk fonds, it analyzes how young Ukrainian Canadian women enacted Ukrainianness not only as cultural continuity but as a strategic mode of civic positioning within Canadian public life. Situated in the context of Canada’s post-1971 multicultural turn, the pageant is read as both a site of diasporic memory and a platform for asserting recognition within broader national narratives. Employing thematic and critical discourse analysis, the essays are approached as microhistorical texts shaped by inherited narratives, institutional logics, and generational responsibility. The article demonstrates that Canadian multiculturalism was not merely reflected in these performances but actively reinterpreted from below, revealing both its enabling rhetoric and its structural limits in mediating difference and 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 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)0.004
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 score0.047
Threshold uncertainty score0.339

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0290.010
Scholarly communication0.0050.002
Open science0.0020.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.304
Teacher spread0.265 · 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
Published2025
Admission routes1
Has abstractyes

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