Disputed post-industrial landscapes : an enquiry into the "loft-living" cultural model in Montreal's Saint-Henri
Bibliographic record
Abstract
The working-class neighbourhood of Saint-Henri in Montreal experiences social, economic and material transformations that see former sites of production changed into residential environments. The urban "revitalization" efforts have often translated into social discomfort, as projects intended to inject vitality into a fractured landscape have truncated and disrupted long-established spatial and social patterns. This thesis posits that the built environment is a material and cultural substance that mediates relationships between social and economic agents. The study employs a three-pronged analytical approach that Includes: firstly, a reading into the built environment itself; secondly, an analysis of the real-estate marketing discourse; and thirdly, through in-depth interviews, a documentation of the perceptions of newcomers and long-term residents, in order to delve into the cultural impacts of new development practices. Relying on Pierre Bourdieu's concepts of habitus and capital, and Henri Lefebvre's notions of space, this study explores the status of a "loft-living" cultural model in the wider field of gentrification. More specifically, it examines how the social and economic determinants of redevelopment strategies influence the spatial and social 'disputes' taking place in the former industrial landscapes of Montréal' Saint-Henri.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.029 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 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".