Vancouver's Downtown Eastside: An ethnography of restaurateurs and neighbourhood change
Bibliographic record
Abstract
This thesis examines the relationship between high-end food and beverage establishments and neighbourhood change, which come together to produce 'foodie gentrification'. Drawing on ethnographic fieldwork in Vancouver's Downtown Eastside, including participant observation, archival analysis, and interviews, I provide accounts of the micro-level practices enacted through material and symbolic boundary-making to elucidate how spatial manifestations of exclusion are enacted and narrated from the perspective of restaurateur gentrifiers. This research project begins with an understanding that cultural production on the ground is a key component of contemporary urban restructuring. First, I ask: how might the study of 'food space' production and consumption in urban neighbourhoods inform an understanding of the complementarity between the political economy and cultural politics of gentrification? Producing uneven and contradictory experiences which vary from amicable and neighbourly to dehumanizing and violent, these micro-practices are an everyday aspect of high-end food space production, and are instrumental to how gentrification unfolds. Second, I examine the cultural production of 'foodie gentrification', and its increasing orientation toward 'social enterprise' as an important contextual and discursive feature of gentrification in the Downtown Eastside. I argue that by paying attention to the different ways restaurateur gentrifiers are significant agents of these processes, we can gain important insight into how the interrelation of culture and economy produce neighbourhood change. This research therefore offers inroads to developing an empirical reconciliation of cultural and economic explanations of gentrification. The micro-practices of exclusion and displacement are not 'surface-level' results of, but rather are requirements of the cultural and economic production of urban restructuring.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".