We Can’t Get There from Here: Why Pricing Congestion is Critical to Beating It
Bibliographic record
Abstract
"Traffic Costs Us. Pricing Congestion is the Missing Piece of our Urban Mobility Puzzle.Traffic congestion costs Canadians. It slows economic productivity, raises the price of consumer goods, damages health, creates pollution, and lowers quality of life. Rapidly growing urban populations hasten the need for urgent solutions. Reducing traffic congestion requires two actions (1) creating more transportation choices and (2) shifting transportation incentives. Many Canadians cities focus efforts on the first approach, but incentives remain the missing piece of the puzzle. This is the gap filled by congestion pricing. Attaching a fee to driving, for example in traffic hot spots at peak times, increases urban mobility by encouraging more informed transportation choices, while making all other transportation investments work better. Canada should begin exploring congestion pricing policies now with temporary and transparent urban pilot projects supported by all levels of government."
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".