Paying for Urban Infrastructure Adaptation in Canada: An Analysis of Existing and Potential Economic Instruments for Local Governments
Bibliographic record
Abstract
As is the case in many other countries in the Western hemisphere, local governments in Canada have a significant role to play in minimizing the impacts of climate change on their population, economy, and fiscal budgets. Simultaneously, local governments typically experience limited capacity, expertise, and limited financial resources.\nThis report examines a number of instruments that local governments in Canada may use to generate revenues in support of adaptation in general, and in support of the development of climate resilient infrastructure in particular. The report also examines instruments aimed at incentivizing behavioural changes at local levels that may reduce the need for public investments in adaptation, and could thereby reduce the need to generate revenues in support of such investments. The most effective combination of incentives and investments is likely to vary across local governments.\nFor local governments, it is recommended that they: include adaptation in long-term strategic planning using downscaled climate change projections; reduce incremental costs associated with climate change by incorporating adaptation actions into existing municipal processes (e.g., into infrastructure maintenance and replacement programs, or in updates of community plans); act strategically and be creative with the current tools available.\n 
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".