Bibliographic record
Abstract
This paper describes how the City of Vancouver (British Columbia, Canada) is currently developing the last remaining industrial waterfront site in its downtown area as a Southeast False Creek (SEFC) is envisioned to be a complete community in which people live, work, play and learn in an urban neighborhood that will be designed as a model of sustainable development. The SEFC lands comprise approximately 80 acres and will house over 13,000 new residents at build-out. Developing transportation and circulation systems, which focus on pedestrian and bicycle paths and transit linkages, is of primary importance in ensuring a livable and environmentally sustainable waterfront neighborhood. This paper not only addresses the traditional transportation issues of trip generation and mode splits but also how Vancouver has gone further by developing 'Sustainable Transportation Strategies' that support the development of SEFC as a model sustainable community. This included increasing the range of transportation choices and services available within the community, such as providing enhanced pedestrian and cycling paths, improving transit (bus, light rail, rapid transit, and ferries), promoting carsharing, and creating specific guidelines on how to incorporate sustainability into street design. To determine how effective the Sustainable Transportation Strategies would be at influencing mode choice, the possible reductions in car use were estimated and compared to the original mode splits. In addition, residents in adjacent neighborhoods were surveyed on how they would respond to the recommended package of sustainable transportation strategies. Initiatives that prove to reduce auto dependency and ownership in the SEFC community could potentially be applied elsewhere at a much broader scale.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".