Re-Surfacing the Chinese-Canadian Body in Performance: Elyne Quan’s “Surface Tension” and “What?”
Bibliographic record
Abstract
These humorous reductive warnings issued by her mother Rosa were intended to make Elyne Quan think twice before she embarked on a theatre career. Both were apt in terms of the race, gender, and body issues that Quan has found herself negotiating in Edmonton, Alberta, where she has established herself professionally over the past five years. As non-white bodies are gradually becoming visible in cultural representations, Quan has set out to examine the ways in which Chinese-Canadians are not only “surfacing” for the first time as they make their presence an indisputable fact of life, but “re-surfacing” as they remember and remind others about all those parts of themselves they lost over generations as immigrants. A second-generation Chinese-Canadian, Quan’s experiences of discrimination and hardship have been more oblique than those of her father, who came from Kaiping as a young boy with his family in the 1950s to open a café in rural Saskatchewan. By the time she was born in 1973, the year they came to Edmonton, her family had a relatively secure middle-class lifestyle. Becoming a theatre practitioner in a predominantly white culture has been Quan’s way of breaking new ground, as we see in the two performance pieces – “Surface Tension” and “What?” – which are the main focus of this article.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.036 | 0.022 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".