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.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.117 | 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 teacher head, 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".