Rhythms of gentrification: eventfulness and slow violence in a happening neighbourhood
Bibliographic record
Abstract
Gentrification involves the transformation of neighbourhood social spaces in ways that remake place in line with the needs and desires of new residents and capital investors. While spatial transformations have been well documented in the gentrification literature, temporality has rarely been foregrounded, although social space is also altered by privileging new rhythms and tempos of everyday life. Using a case study of Toronto’s gentrifying Junction neighbourhood, this article explores the restructuring of everyday neighbourhood rhythms around consumption-oriented and place-making events that draw on a collage of ideas about the timespace of ‘authentic’ urban street life. I argue that the reorganization of neighbourhood social life through the creation and privileging of specific temporal landscapes functions as a means of excluding, marginalizing or rendering invisible certain community members and their needs. The inability of some to participate in the new temporalities of the neighbourhood becomes a barrier to recognition and representation, one that both hides and enables the ongoing ‘slow violence’ of gentrification.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.030 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.011 |
| 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".