Revisiting the Diversity of Gentrification: Neighbourhood Renewal Processes in Brussels and Montreal
Bibliographic record
Abstract
This article provides a comparative analysis of neighbourhood renewal processes in Brussels and Montreal based on a typology of such processes wherein gentrification is precisely delimited. In this way, it seeks to break with the extensive use of a chaotic conception of gentrification referring to the classic stage model when dealing with the geographical diversity of neighbourhood renewal, within or between cities. In both Brussels and Montreal, the gentrification concept only adequatly describes the upward movement of very restricted parts of the inner city, while neighbourhood renewal in general more typically comprises marginal gentrification, upgrading and incumbent upgrading. Evidence drawn from the case studies suggests that each of these processes is relevant on its own-i.e. linked to a particular set of causal factors-rather than composing basically transitional states within a step-by-step progression towards a common gentrified fate. Empirical results achieved in Brussels and Montreal suggest that a typology such as the one implemented in this article could be used further in wider research aimed at building a geography of neighbourhood renewal throughout Western cities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".