Formalizing a Federal Role for Canadian Transportation Investment: Toward Fiscal Policy that Links Transportation, Health, and the Environment
Bibliographic record
Abstract
Canada is the only country, amongst 29 other member countries, in the Organisation of Economic Co-operation and Development that does not have a permanent source of national funding and investment in transportation infrastructure projects. Canada is the only country in the G-7 (a group which comprises over 49% of the global financial market) that fails to invest in supportive transportation infrastructure over a long time horizon. If all of these countries have significantly invested in transportation infrastructure, why has Canada failed to do so? The Federal government has not historically played a role in financing urban transportation systems. This responsibility is jurisdictionally allotted to the provinces. There has been a commensurate decline in provincial funding of municipal transportation infrastructure and as the necessary funding has dwindled transit fares have increased and transit service hours have decreased (McCormick Rankin Corporation 2002). But, in the last few years there has been a shift in federal policy that has resulted in municipalities (via the provinces) receiving much needed funding for urban transportation infrastructure. Through a literature review, stakeholder, programmatic and case study analysis this report explores the challenges facing Canada’s urban transportation systems. Transportation related externalities are threatening to undermine the environment and the overall health of Canadians through urban sprawl, congestion, the acute and disbursed environmental effects of emissions. Stakeholders in the transportation system have made their desires for a national policy/strategy on transportation funding well known. The current federal transportation funding programs are disparate, do not provide enough long term funding, and are limited in scope. A comparative analysis of the US, UK, and Germany provides valuable insight into successes and failures of urban transportation funding.
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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 | 0.017 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".