Towards sustainable neighbourhoods? Tensions and heterogeneous transport priorities among suburban residents
Bibliographic record
Abstract
A major challenge in North America’s car-centric suburbs is developing sustainable transportation strategies that align with residents’ diverse needs and preferences. Using a survey of 1,850 residents in Scarborough, an eastern suburb of Toronto, we used descriptive statistics and an exploded logit model to identify which environmental factors, sociodemographic characteristics , travel behaviors, political values, mobility options and transport barriers, and aspirations influence residents’ transport priorities in terms of space and investment. Overall, transit investments are considered the top priority, followed by walking, driving, and cycling, with clear neighbourhood-specific variations. Newcomers, older adults, and racialized groups prefer sustainable transport options, while women, white and right-wing individuals prioritize car investment. Moreover, transport priorities are closely linked to people’s lifestyles and neighborhood aspirations, as reflected in the destinations they want near their homes. These findings enhance our understanding of transportation preferences and offer valuable insights for developing effective, context-specific sustainable transportation strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".