Smart Commute Initiative - Establishment of a Multijurisdictional Workplace-based Transportation Demand Management Program Serving the Greater Toronto Area and Hamilton
Bibliographic record
Abstract
The amount of vehicular traffic in the Greater Toronto Area and Hamilton has been increasing for decades, with demand increases outpacing additional supply. As a result, traffic congestion has been swelling, and gridlock is projected to worsen by 45% over the next 30 years. In addition to increasing travel times, the additional congestion is already costing the regional economy $1.8 billion per year. The Smart Commute Initiative was a multijurisdictional workplace-based transportation demand management program serving the commuting population of the Greater Toronto Area and Hamilton. Established in 2004, the Initiative formed and enhanced eight transportation management associations (TMAs) across the region, based on the successful experience of Ontario's first TMA, Smart Commute Black Creek. A central coordinating body, the Smart Commute Association, was also established, thereby separating demand management functions into two tiers of program delivery. Through careful monitoring at the workplace and regional levels, the impact of Smart Commute was measured before and after implementation, from May 2005 to March 2007.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".