“Hot+Noisy” Public Space: Conviviality, “Unapologetic Asianness,” and the Future of Vancouver’s Chinatown
Bibliographic record
Abstract
Questions of change and the future have become increasingly salient in Vancouver’s Chinatown in the last decade, as gentrification proceeds apace. Various actors have used the neighbourhood’s public spaces to express their visions of Chinatown’s future. These claims are articulated through attempts to demonstrate and strengthen the vitality of Chinatown in the face of growing narratives of its putative decline and death. By engaging with the contemporary sociological literature on conviviality, where relatively “thin” versus more radical conceptualizations of conviviality are being debated, and putting it into conversation with both the geographical literature on the politics of public space and political theory discussions of agonism, we argue that the uses of public space must be analyzed without romanticizing conviviality or consensus in order to understand the productive possibilities of “political conviviality” and agonistic encounters. Our focus is the “Hot+Noisy Mahjong Socials” held in recent summers in an iconic plaza in Chinatown. These are organized by a community group that builds connections between mostly Chinese Canadian youth and largely Cantonese-speaking seniors. These groups espouse a goal of “place-keeping” in the context of planning trends toward “placemaking.” Through this case, we consider how activists from marginalized communities build solidarities through agonistic “place-keeping” in the face of gentrification and threats of cultural erasure.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.024 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".