A culinary hub in the global city: diasporic Asian foodscapes across Scarborough, Canada
Bibliographic record
Abstract
This article examines the role of late twentieth-century transnational migrants to Canada in transforming Scarborough into a culinary hub with global and Asian resonances—a place where dense affective, sensory, social, cultural, and economic networks of foodways overlap and combine to create place-specific diasporic sensescapes. The primary research questions are: How does such an Asian culinary hub emerge and function in the transnational and diasporic setting of a contemporary global city and how do citizens’ negotiations of its mobile foodways constitute the hub, and act as its archive? To locate answers for these questions, the authors engaged with long-term collaborative research among academics, students, and community stakeholders connected to the Culinaria Research Centre of the University of Toronto.
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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 | 0.004 |
| Science and technology studies | 0.019 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| 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".