Funding Transportation in the Dark? The Case Study of Ontario, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The challenges of funding transportation infrastructure and services are significant and they shape both what is built and how individuals travel. Transportation funding sources are evolving considering changing technologies. The case study of Ontario, Canada, which is in the process of a generational investment in transit infrastructure, illustrates opportunities for addressing these challenges. This case study uses a policy assessment lens considering efficiency, equity, efficacy/feasibility, and environmental sustainability. Ontario's policy shift was spurred by the increased provincial role in transit capital funding and supportive policies, but its success depends on future provincial governments continuing to prioritize transportation investments. With a slowly increasing federal role, there are also new funding opportunities. Looking forwards, municipalities need more options to fund transportation themselves and more consistency as an alternative to relying on the provincial political process to deliver funds. Four key questions are highlighted which shape the future of transportation funding in Ontario.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it