Empirical Analysis of Transit Network Evolution: Case Study of Mississauga, Ontario, Canada, Bus Network
Bibliographic record
Abstract
This paper presents the results of the first phase of an ambitious research project aiming at modeling the changes over a 15-year period in the bus network of the city of Mississauga, Ontario, Canada, a fast-growing suburb in the greater Toronto area. Data for the Mississauga transit network, along with a host of demographic and socioeconomic variables, were analyzed. For each main route, a buffer zone representing its vicinity was constructed, and the relevant variables captured inside these zones were computed for inclusion in the proposed empirical models. Other global variables for the city were included as well to account for other effects. Results from multiple regression and simultaneous equation models attempting to relate transit supply to this group of demographic, socioeconomic, and route-specific variables are presented. Time and demand-supply interactions were taken into consideration in the simultaneous equation models. The models show that supply increases with demand and population density...
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".