Bibliographic record
Abstract
Greater Vancouver has pioneered the development of bus rapid transit (BRT). The three existing routes each have distinctive differences in design and operation but model rail transit by providing frequent, reliable, easy to use, limited stop service with branded, low floor, articulated buses. The BRT service carries 50,000 passengers daily - 10% of the bus system's ridership and uses a dedicated fleet of 55 peak period buses with a distinctive livery. While the region's BRT first line has been popular, it is the second line that has captured the most interest because it includes most of the successful components of BRT. This line links the fast -growing suburban Richmond City Centre with the Vancouver International Airport and downtown Vancouver. The newest line connects the recently built Millennium SkyTrain line with the downtown area of a suburban city-Coquitlam. This paper describes the approach used in Greater Vancouver for developing BRT including a description of its key components and customer characteristics. Through the example of the #98 B-Line, the paper illustrates the challenges of implementing a complex project featuring new vehicles, infrastructure and a customer-focused service design. The #98 B-Line also illustrates the challenges of introducing this service in the middle of a financial crisis and after a four-month labour disruption. BRT support in Greater Vancouver has generally been strong. Supporters point to the low costs relative to rail and the improved image and reliable and speedy service it provides for bus riders. A few critics have called it an expensive bus service, with fancy shelters and whiz bang technology, offering limited improvements over other bus services. In its seven-year history in Greater Vancouver, BRT has emerged as a valuable transit mode that has been an excellent fit in a medium-sized metropolitan area with a low to medium density and multi-centred land use pattern. BRT offers potential for ridership growth in the transit corridors in which it is applied, until threshold demands are reached that warrant rail transit investments.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".