LET IT RIDE : TRANSIT AND TOURIST ROADS ARE PLACING THEIR PASSENGER- GROWTH CHIPS ON NEW MARKETING STRATEGIES, CAPACITY ADDITIONS AND CREATURE COMFORTS
Bibliographic record
Abstract
This article presents a survey of passenger railroads, both commuter and long-distance, on tactics they plan to use to try to counteract the anticipated drop in ridership and sales tax revenues that support many of them. They are stepping up marketing and advertising campaigns, including restructuring fares to make them more attractive to new riders, adding amenities such as parking spaces, and beefing up other passenger amenities. Tourist and scenic roads are stepping up their advertising and promotions. The Bay Area Rapid Transit (BART) system hopes its new leg to SFO Airport will help offset ridership drops that will bring it down to 88 million from the 2001 total of 97.2 million. Among the operators profiled are Calgary Transit, Denver's Regional Transportation District, GO Transit in Ontario, Niagara Frontier Transportation Authority, the Altamont Commuter Express, the White Pass & Yukon Route Railroad, which is linked to steamship cruise lines, and the Montana Rockies Rail Tours, which only operates during peak vacation months and holidays.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".