10 Immigrant Gifts, Pluralist Spectacles, and Staging the Modern City and Nation
Bibliographic record
Abstract
Chapter Ten Immigrant Gifts, Pluralist Spectacles, and Staging the Modern City and NationIn mid-1960s Toronto, as many as 20,000 people came out for the spectacular Nationbuilders shows that took place on the grandstand stage of the Canadian National Exhibition (CNE) during the last evening of the Labour Day weekend.As a member of the community folk council that mounted what was billed as the "largest folk festival in Canada, " the International Institute of Metropolitan Toronto considered this (and other) multi-ethnic extravaganzas an integral part of their cultural mandate.A central goal of that mandate was to encourage Canadian appreciation for the talents and cultural gifts of immigrants and to promote a vision, or reimagining, 1 of a robustly pluralist city and nation.The eclectic but polished Nationbuilders shows featured a dizzying array of performers.The 1964 program included more than 50 music ensembles and a cast of 1,500 "young Canadians" who delivered performances "in the native costumes of the land of their fathers." Sir Ernest MacMillan, described as the "patriarch" of Canada's conductors, led the "mass choir" of 500 singers from Toronto's many ethnic choirs and choral groups that ended the show.In regard to the emotional impact that such performances could have on an audience, Toronto Institute personnel believed in the unifying and transformative power of music and performance.The Nationbuilders and other events under review invited Anglo-Canadians, ethno-Canadians of all origins, and newcomers to participate in a festive affair intended to lift both the hearts and minds of audiences.Insofar as the Nationbuilders shows brought an impressive number of newcomers into one of the defining public spaces of the city of Toronto, the CNE, they mark, too, the emergence of Toronto's immigrants as part of a wider culturally consuming public.The success of the shows, the costumes for which cost an estimated $100,000, served, paradoxically, to both reify immigrant folk cultures and legitimize public displays of cultural difference.It also encouraged still bolder experiments in promoting ethnic diversity through popular spectacle.Aided by the wider folk and white-ethnic revivals of the post-1945 and
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.020 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".