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Record W2623010390

Plural Identities in Folk-dance: Spectacle as Vehicle for Hyphenated Identities 1965-2015

2017· article· en· W2623010390 on OpenAlexaffabout
Desanka Djonin

Bibliographic record

VenueOral History Forum d'histoire orale · 2017
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsYork University
Fundersnot available
KeywordsSerbianDanceSpectaclePluralIdentity (music)SociologyCollective identityImmigrationVisual artsAestheticsHistoryGender studiesArtPolitical scienceLawLinguistics
DOInot available

Abstract

fetched live from OpenAlex

In this paper, I examine the preparation and execution of spectacle, often facilitated by cultural religious traditions, as a vehicle for nurturing and evolving a collective hyphenated identity among Canadian-Serbs, by compiling an oral history archive of interviews with sponsors, administrators, and artists involved in theatrical Serbian-Canadian folk-dance organizations in Ontario. Together with the continued practice of the Christian Orthodox religion, the theatrical folk-dance continues to be a shared extracurricular activity, as well as a key component in the upbringing of second and third generations of Serbian immigrants dating back to the post-war out-migrations of Serbs from Yugoslavia. While the folk-dance form was realized in its theatrical form in 1948 and brought to Canada with the post-war migrations, I argue that the collective effort put into the creation and performance of spectacle was a key factor in the expression and nurturing of a Serbian-Canadian collective identity. Through the incorporation of personal memories via oral histories and archival materials, this paper surveys the ways in which Canadian social, economic and cultural frameworks, together with Serbian-Canadian dance organizations, have served as a vehicle for the integration of Serbian immigrants, not only into Canadian society but also into Canadian dance cultures.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.034
GPT teacher head0.305
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2017
Admission routes2
Has abstractyes

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