Subway user behaviour when affected by incidents in Toronto (SUBWAIT) survey — A joint revealed preference and stated preference survey with a trip planner tool
Bibliographic record
Abstract
Transit user behavioural response under disrupted service conditions, specifically how transit riders choose among available mode options to complete their trips, is not well understood. This study aimed to investigate transit user mode choice in response to rapid transit service disruption in the City of Toronto, incorporating such factors as the type of disruption, stage of the passenger’s trip (pre-trip or en-route), weather conditions, and uncertainty of delay duration. A joint revealed preference (RP) and stated preference (SP) survey was designed where the RP part gathered information on the respondent’s actual response to the most recent service disruption while the SP part solicited the respondent’s travel choices under a set of hypothetical service disruption scenarios. A transit trip planner tool was developed to generate alternative transit mode and path options to avoid the disrupted segment. An empirical model using RP data is presented to verify the survey design technique.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".