Plural Identities in Folk-dance: Spectacle as Vehicle for Hyphenated Identities 1965-2015
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.028 | 0.023 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".