Transit Oriented Development From Both Sides of the Tracks: How the City is Promoting it and How Developers are Building it
Bibliographic record
Abstract
The City of Calgary has experienced substantial population growth over the past eight years with an annual average growth rate of 2.4%, pushing the total population over one million. This increase in population has put more demand on public infrastructure, specifically roads and transit. In an effort to meet the mobility demands of Calgarians, and in turn reduce the dependency on vehicles, the City of Calgary is taking steps to improve the existing transit system. These improvements include extending current Light Rail Transit (LRT) lines, expanding the use of Bus Rapid Transit (BRT), increasing existing train capacity from three cars to four and promoting development and transit use through Transit Oriented Development (TOD) planning and policies. This paper will look at how the City is working with developers to enhance transit station areas and what some developers are proposing given these opportunities. Three specific stages of the TOD process will be covered and include the following: the land use planning stage with the City; the TOD specific transportation impact assessment requirements using the City's new Mobility Assessment & Plan (MAP); and the successful proposal of TOD areas by developers.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".