Missing the Connection? A case study approach to understanding effective public transit transfers in dispersed lower density cities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The 'network effect' is a public transit operating approach aimed at serving the complex travel patterns of dispersed lower density cities. The approach relies on effective transfers between transit modes. In compensation for the inconvenience of transfer, passengers are rewarded with a service providing access to a wide, rather than limited, geographic area. Whilst the theory is now well established, analysis of its success in practice is less well researched. This paper adds to knowledge on the network effect by comparing feeder transit service levels and rates of transfer observed in two case study locations. Feeder transit quality of service is measured by (i), the number of services provided on each route, and (ii), the timetabled wait time between feeder and trunk services (and vice versa). The paper compares rates of transfer between bus and train at stations on the Dandenong Line in Melbourne with the eastern branch of the Montreal metro Green line to Honore Beaugrand. The paper reports on on-going analysis that seeks to identify relationships between these variables and rates of transfer observed at stations along both lines. In particular, the analysis is interested in factors influencing the higher rates of transfer seen in the Montreal case study. The findings will be important for any transit agency looking to benefit from the theoretical advantages of the network effect in suburban land forms common to Australian and North American cities. They are of particular interest in Melbourne given recent investment commitments to grade separations and the Melbourne Metro rail tunnel.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it