Dwelling Type Matters: Untangling the Paradox of Intensification and Bicycle Mode Choice
Bibliographic record
Abstract
Urban intensification is believed to result in a modal shift away from automobiles to more active forms of transportation. This study extended the understanding of bicycle mode choice and the influence of built form through an analysis of dwelling type, density, and mode choice. Apartment dwelling and active transportation are related to intensification, but an understanding of the impact of increased density on bicycling is muddied by the lack of isolation of cycling from walking in many studies and by the lack of controls for the confounding effects of dwelling type. This study examined the relationship between dwelling type and mode choice in Toronto, Ontario, Canada. In this study of 223,232 trips, 25 variables were controlled for, and multinomial logistic regression analysis was used to estimate relative risk ratios. Strong evidence was found that a trip that originated from an apartment-based household was less than half as likely to be taken by bicycle as a similar trip that originated from a house-based household in Toronto in 2011. Increased population density of the household location had a positive impact on the likelihood that a trip would be taken by walking and a negligible and uncertain impact on the likelihood that it would be taken by transit. However, increased population density had a negative impact on bicycling. Further analysis found that the negative impact of density did not seem to apply to those who lived in single detached housing but rather only to the likelihood that apartment and townhouse dwellers would cycle. Further research is required to identify the exact barriers to cycling that apartment dwellers experience.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".