Transit Benefit Index: A Comprehensive Index for Capturing Externalities in Transit Planning
Bibliographic record
Abstract
This research provides a methodology for estimating the total societal benefit generated from substituting private vehicle trips with public transportation trips. The external costs of private and public transportation were estimated using a base case travel demand model and then a mode shift was simulated to calculate the effects of shifting one full transit unit (e.g., bus) of demand from a private to public mode. This shift was performed for all origin–destination (O-D) pairs in a region to find the O-D pairs that resulted in the greatest net benefit. These benefits were then normalized using the total automobile vehicle kilometers traveled removed from the network to generate a “transit benefit index.” This methodology was applied to a case study of the city of Bogotá, Colombia. A total of 102 scenarios were simulated: a 2 in base case, and 10 total sensitivity analyses, each including two transit provision alternatives. The results were contrasted with the cost of a new transit unit—a new bus in this case—revealing that the total economic benefit derived from 1 year of increased transit ridership was larger than the financial cost of a new bus to the transit operator. These results suggest that the City of Bogotá should consider further subsidies to transit fares to increase ridership and mitigate externalities.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".