O rio e a metrópole: encontrando um equilíbrio entre os usos passados e futuros da margem do rio St-Lawrence em Montréal.
Bibliographic record
Abstract
This article explores the transformation of urban blue spaces in Montréal, focusing on three riverside areas along the St. Lawrence River. Since the 1990s, Montréal has undertaken revitalization efforts, transforming post-industrial landscapes into dynamic public spaces that reconnect citizens with the river. These areas face challenges such as industrial legacies and pressures for reindustrialization versus green and blue public spaces. The study integrates cultural analysis, political ecology, design and counter-mapping to document historical uses, analyze cultural layers and propose future strategies for Montréal’s waterfront areas. Although surrounded by 266 km of shoreline, Montréal faces access problems due to the industrial presence and privatization of the riverbanks. Projects such as “À nous les rives !” by the design coop Le Comité aims to reclaim these spaces, emphasizing sustainable development and community involvement. The analysis examines global variations in urban waterfronts, focusing on natural, landscaped and neglected environments shaped by historical, political and social contexts. This research highlights Montréal’s evolving relationship with water, combining environmental management with public accessibility and cultural enhancement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".