Getting into the zone: What can municipal bylaws tell us about transit-oriented development in Montreal, Quebec?
Bibliographic record
Abstract
Transit-oriented development (TOD) has been widely encouraged as a strategy to limit urban sprawl, increase urban density, reduce car dependency, and enhance neighborhood diversity.Federal and regional governments have been increasingly promoting such TOD in parallel to their light-rail-transit (LRT) projects to ensure high return on investments and foster sustainable urban transitions.We know little, however, about the extent to which municipalities are making adequate changes to existing land-use regulations to sufficiently accommodate these TOD goals.This article provides an assessment of changes in municipal plans and bylaws surrounding a new $7B LRT in Montreal, Canada that is set to open in late 2022, 6 years after its announcement.Specifically, we analyze whether changes in municipal bylaws conform with TOD plans recommended by the regional government.Through policy and spatial analysis, this research finds that only a limited number of boroughs have made sufficient bylaw changes between 2016-2022 to adequately support TOD plans aimed at implementing mixed-use zoning, increasing urban density, reducing parking minimums, and supporting affordable housing around stations.These findings suggest that some municipalities are not doing enough to maximize benefits from one of the largest public-transport investments currently being implemented in North America.These findings can aid planners and policymakers in understanding the importance of municipal zoning bylaws in an integrated transport and land-use approach.If LRT projects are to be successful in meeting sustainability goals, greater engagement with land-use regulations across multiple scales is needed to facilitate TOD.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".