Advancing Resilience and Equity in Canadian Municipal Climate Adaptation
Bibliographic record
Abstract
Effective climate adaptation must build resilience and advance social equity. Most municipalities now recognize the importance of furthering resilience and equity in their climate adaptation planning. To date, however, there has been limited attention to whether municipalities are currently incorporating resilience and equity into their planning and how to assess status and track progress towards resilience and equity in climate adaptation. Accordingly, this research responds to the need to better understand how principles of resilience and equity are articulated in Canadian municipal climate adaptation plans (Study One) and to develop a framework to strengthen resilience and equity in municipal climate adaptation (Study Two). Study One evaluates ten Canadian municipal adaptation plans through a content analysis. Plans were evaluated using a coding protocol consisting of 26 indicators based on 10 principles of resilience and equity. The analysis revealed three key findings that are important for policy and practice: (1) Canadian municipal adaptation plans prioritize resilience over equity, (2) complex theories of resilience were less commonly operationalized, and (3) distributional equity is insufficiently operationalized in Canadian municipal adaptation plans. Study Two conducts a literature review and survey with municipal practitioners (n=15) to develop an index to assess resilience and equity in municipal climate adaptation planning. The Climate Resilience and Equity (CRE) Index is comprised of 10 principles and 26 indicators. The index is a first step in advancing an approach to strengthen our understanding of how indicators of resilience and equity are integrated into municipal adaptation planning. The CRE Index could be used by researchers and practitioners to mainstream resilience and equity in municipal climate adaptation planning and decision-making. Overall findings have many implications for theory and practice including, but not limited to, improved climate adaptation, enhanced community well-being, and the fostering of more inclusive and sustainable urban development. This thesis highlights the value of centring resilience and equity in adaptation planning, emphasizing that a comprehensive approach not only bolsters municipalities' capacity to navigate climate challenges but also contributes to broader societal goals, ensuring that no community is left vulnerable in the face of environmental change.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".