Towards an Analytical Tool to Connect Women in Low-income Neighbourhoods to Utilitarian Cycling Infrastructure in Guelph
Bibliographic record
Abstract
Cycling is a convenient, and affordable mode of active transportation linked to increased physical and mental health, as well as environmental and socioeconomic benefits. However, cycling represents a marginal mode of commuter transportation in Canada, undertaken primarily by men with high levels of income and education. The factors that deter women in low-income neighbourhoods from engaging in utilitarian cycling are poorly understood. This study employs parametric modeling software Grasshopper to develop an analytical tool capable of generation optimized cycling route recommendations, based on input parameters hypothesized to encourage greater female ridership. To evaluate the parameters, the analytical tool is used to connect a residential low-income neighbourhood in Guelph to utilitarian destinations such as grocery stores, schools, childcare services, and existing cycling networks. The results indicate that more direct routes, greater separation from vehicular traffic, and lower speed limits are required to encourage equitable access to utilitarian cycling.
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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 | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".