Climate Risk Assessment and Adaptation Considerations for Municipal Governance
Bibliographic record
Abstract
Within the last 10 years, four of the 10 most extreme and extremely expensive weather- related disasters in Canada have occurred in Alberta, and climate modelling for Western Canada projects increasing changes and weather extremes. Changing and extreme conditions will continue to affect many aspects of municipal operations over the next 10 to 30 years. The major risks and impacts of changing climate conditions directly affecting municipalities involve infrastructure performance, increasing water stress, land use change and asset management. Long-term seasonal temperature and precipitation changes punctuated by extreme weather conditions are a costly combination affecting local governments and communities. Alberta has a diverse range of climate risks, and risk assessment, adaptation and disaster response needs to reflect this diversity. Surveys done in 2019 and 2021 identified common barriers affecting municipal effectiveness in managing and adapting to climate risk which include: available staff time; access to climate risk and adaptation expertise; access to financial resources; and access to locally relevant and credible climate informationand data. Municipalities in Alberta with populations less than 10,000 are more likely to experience these barriers than larger and urban municipalities better positioned to have access to the specialized resources necessary. All Alberta local authorities are required to have an emergency management plan to respond to extreme weather events of relatively short duration. However, longer term, extreme shifts in seasonal temperatures and precipitation are projected over the next 20to 30 years that will continue to impact municipal land use planning, water availability and infrastructure costs. Climate risk and adaptation need to be integrated into municipal plans, infrastructure maintenance, capital budgets and asset management to strengthen local resilience. Municipalities in Alberta have a provincial statutory framework that can address climate risk assessment and adaptation. Eight opportunities are identified that can be used within Alberta’s municipal government model to increase municipal effectiveness including: greater use of Intermunicipal Collaboration Frameworks (ICFs) and development of a Climate Adaptation Research and Decision Support (CARDS) network to provide multi- disciplinary decision support to local government decision-makers in different geographic areas of Alberta.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".