Parking BreakMulti-unit residential off-street parking requirements in Canada
Bibliographic record
Abstract
Parking requirements are an important part of urban planning. Parking influences a number of behaviours and measures relevant to planning, including mode choice, density, urban form and housing affordability. Much research on parking has taken place in American cities which have different demographic, regulatory, and transportation contexts than Canadian ones. This research is an examination of off-street parking requirements in Canadian cities. It focuses on parking standards for multi-unit residential buildings, explores different approaches used in this regulatory practice and sheds light on the ways in which Canadian cities are dealing with parking requirements today. This is done through a scan of parking requirements across the 30 largest cities in the country, the detailed analysis of parking policies and of their objectives in four cities, and interviews with professionals in Toronto and Vancouver on the political, economic and institutional forces that have shaped their city’s parking regulations. Findings suggest that large Canadian cities are facing pressure to better manage their parking systems, leading to the development of new tools to regulate parking in increasingly sophisticated ways. The paper concludes with recommendations for planners to consider when developing parking requirements, cautions them about the ways in which such requirements can be misused, and encourages them to continue to innovate and challenge accepted practices of parking regulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.200 | 0.036 |
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".