Bibliographic record
Abstract
Toronto, among the most diverse cities in the world, is home to a massive Chinese diaspora and hosts no fewer than five Chinese orchestras. Varying in size from 20 to 60 members, and in status from professional to amateur, these orchestras have been providing a home for Chinese instrumentalists and exposing Torontonians to Chinese music since 1993. In this article, I analyze the repertoire choices of three of these orchestras since 1993 to consider how their repertoire relates to their members’ identities and the organizations’ goals. In particular, I argue that the repertoire represents complex negotiations of diasporic communities, both with their audiences and among the orchestra members themselves; for instance, these orchestras’ directors seek the balance between new repertoire and old repertoire without losing audiences. Moreover, these negotiations demonstrate the impact of transnationalism (Zheng Su, 2010) and hybridity (Ang Ien, 2003) on diasporic Chinese communities in Toronto. The city’s multicultural environment enables these Chinese orchestras to collaborate with musicians and music groups from different cultural backgrounds. This article provides insights into how the history of Chinese orchestras in Toronto contributes to our understanding of how Chinese diaspora music history is actually Canadian music history.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".