BUILDING BLOCKS: INTERNATIONAL EXAMPLES OF BRT'S INFLUENCE IN SHAPING DEVELOPMENT
Bibliographic record
Abstract
Bus Rapid Transit (BRT) is like any transportation facility or service in that it is capable of influencing the type, scale, value, and timing of surrounding development. Or not, depending on the presence and influence of the myriad of other factors that also shape those same features. In this review of international examples drawn from Busways in the U.S., Canada, and Australia, a range of development impacts may be observed. Impacts can occur on the nature of development in the immediate vicinity of busway stations; along the guideways; and on a suburb-wide basis. Specific examples of Busway impact on development in cities (Ottawa, Pittsburgh, and Brisbane) are provided. The effect of BRT service on the development of an entire suburb in Ottawa, a picture of specific new and adaptive development over a fifteen year period along Pittsburgh's East Busway, and the immediate impact on property values in Brisbane's South East Busway corridor are highlighted, as examples of the influence of Busways on their surroundings. The paper concludes with a catalog of 48 Busway stations, constituting the majority of the stations currently in operation in Ottawa, Pittsburgh, Brisbane, and Adelaide. Each entry provides a high-level photograph of the station area (where available), a description of the facility, its setting, a summary of the new development that has occurred since station opening (where information is available), and an overview description of the development situation within which the station sits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".