Remembering the Small-Town Chinese Restaurant: Diasporic Culture at the Junction of Old and New
Bibliographic record
Abstract
Eating Chinese: Culture on the Menu in Small Town Canada opens with a short narrative about Hoy Fat Leong and Charlie Chew Leong. In 1917, the father and son moved to New Dayton, Alberta, and opened the town’s first restaurant, the N. D. Cafe. The narrative swiftly moves from the restaurant’s fragmented history to its recent immortalization in the black-and-white pages of a text commemorating the passing prairie landscape. However, Lily Cho persuasively argues that restaurants such as the N. D. Cafe are still ubiquitous across the country. As a common feature and the social hub of small towns, Chinese restaurants constitute an important and under-interrogated site for cultural studies scholarship. Seeking to contribute to a discourse that privileges multinational citizenship, global cities and ethnic enclaves in urban centres, Cho contends that this locus of small town everyday experience “is almost everywhere[...], and yet almost nowhere in contemporary discussions of Chinese immigration, diasporas, Canadian multiculturalism, transnational migration patterns, and global movements of people and capital” (7). Eating Chinese takes this “paradox of visibility” (7) as its starting point. What is the significance of the “premature requiem for the restaurant that has not yet passed” (15)? As sites of cultural production, what can small-town Chinese restaurants tell us about how diasporic culture is constituted? How do the interactions around food, memory and nostalgia at these sites consolidate racialized identities and ideas about Chineseness, Canadianness and Westernness? How should we read small-town Chinese restaurants for signs of diasporic agency?
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.019 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".