Modelling transit and automobile trip-generation propensities of post-secondary students in the Greater Toronto and Hamilton area: a cross-sectional study
Bibliographic record
Abstract
The post-secondary students in the Greater Toronto and Hamilton Area (GTHA) maintain a constant source of demand and ridership for the region’s transit infrastructure. With the province investing billions of dollars to meet the transit needs of the residents of the GTHA, a comprehensive analysis establishing the correlation between transit and automobile trips and the factors that influence the trip generation for these modes and this subpopulation is warranted. Using data from 2015 and 2019, a cross-sectional study to gain behavioural insights into travel by post-secondary students is performed. Using a bivariate ordered probit approach, the effect of land-use attributes and socio-demographics on the propensities of making transit and automobile trips is determined, followed by a marginal effects analysis. The results indicate that the propensity of making transit and automobile trips decreases if the commute distance to campus is below 5 km, and improvement in areas with low transit accessibility can considerably increase the transit trip-making propensity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".