Impacts of public transit improvements on ridership, and implications for physical activity, in a low-density Canadian city
Bibliographic record
Abstract
Public transit ridership offers valuable opportunities for modest amounts of daily physical activity (PA). Transit is a more feasible option for most Canadian commuters who live too far from work to walk or cycle, yet public transit usage in midsized Canadian cities has historically remained low due to inefficient transit service. The objectives of this longitudinal study were threefold: to assess whether the introduction of express transit service in the low-density city of Kingston, Ontario, has translated to greater transit use among a targeted employee group; to document the characteristics of those employees that have shifted to transit; and to examine the PA levels of employees using transit compared to other commute modes. An online survey was administered in October 2013 and October 2014 to all non-student employees at Queen's University. 1356 employees completed the survey in 2013, and 1123 in 2014; 656 of these employees completed the survey both years, constituting our longitudinal sample. Year-round transit ridership increased from 5.5% in 2013 to 8.5% in 2014 (p < 0.001). Employees who shifted to transit had fewer household-level opportunities to drive to work and more positive attitudes toward transit. Transit commuters accrued an average of 80 minutes/week of commute-related PA, and 50 minutes/week more total PA than those that commuted entirely passively. Kingston Transit's express service has stimulated an increase in transit ridership among one of their target employers, Queen's University. The findings from this study suggest that shifting to transit from entirely passive commuting can generate higher overall PA levels.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".