The Influence of Housing Suitability on Commuting Patterns in Montreal, Toronto and Vancouver
Bibliographic record
Abstract
This thesis explores the impact of housing suitability on the commute to work link for the metropolitan areas of Montreal, Toronto and Vancouver. Housing suitability, operationalized in this thesis using variables for number of bedrooms and dwelling type, has not been studied extensively in the literature. The research goal is to build upon the current knowledge of the factors shaping the distance between home and work by investigating the role of housing suitability using a large data set permitting statistical analysis. This requires access to household level data including geographic identifiers for the workers’ home and work location rarely available in public data to protect confidentiality of respondents. Accessibility to the confidential micro-level census data from 2006 provided by Statistics Canada was secured to enable such a unique quantitative examination. Two different approaches are used to measure the influence of housing suitability on the home-work link. First, a series of regression models estimate the importance of housing suitability on proximity to the workplace holding several other factors constant. Second using a descriptive, comparative analysis the housing in the employment centres of each CMA is compared to (a) the current housing occupied by workers and (b) the housing that would be required, based on suitability criteria, to accommodate the workforce currently working in specific employment centres. The results speak to the role housing suitability plays in countering Smart Growth planning principles as workers are forced to live further away from work due to the inability to find suitable housing near their place of work. For planners the results indicate that an examination of housing suitability at the metropolitan scale, in relation to the home-work link, is required before attempts are made to implement Smart Growth policy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".