1. Analytical Framework: Adapting the C40 Taxonomy

To enable systematic cross-jurisdictional comparison, we are using the C40 Cities’ 13 thematic areas—familiar for global cities that are work with C40 and adopted by leading Canadian municipalities (Toronto, Montréal, Vancouver). Each thematic area is decomposed into 4-7 observable indicators (total: 84 indicators), creating a granular scoring matrix. This framework allows for international comparability and is flexible for Canadian-specific nuances.

2. Data Acquisition
The New Climate’s data acquisition strategy relies on publicly accessible sources so that there is full transparency and replicability for solid policy analysis. The base data includes:

• Primary Documents: Ratified CAPs, council minutes, budget annexes
• Secondary Evidence: Performance dashboards (e.g., Fredericton), auditor reports (e.g., Vancouver), implementation records (e.g., Ottawa LRT contracts)

The ratified CAP and council minutes have an initial priority in the analysis, while budget allocation decisions (which may have a time lag) and subsequent implementation-related procurements or programs have a later priority in the analysis. This prioritising allows for the findings to be focused on accountability and approved directions rather than political claims and aspirations.

3. Quantitative Scoring Approach
A 5-point ordinal scale is used to assess the effectiveness, strength, and maturity level associated with each indicator. This approach for comparative policy analysis (e.g., Climate Policy Tracker) translates complex actions into auditable metrics for comparability:

Score Effectiveness / Maturity
Example

1 Aspirational (no binding mechanism)        –      “Exploring bike lane options”

3 Operational (funded, measurable) – “50 EV chargers by 2025”

5 Transformative (regulatory shift) – “Zero-emissions building code (2024)”

Reliability safeguards: Inter-rater testing (Cohen’s κ >0.8), emissions-impact weighting (IPCC AR6 GWPs).

4. Advanced Analytical Techniques
To uncover latent patterns within this multidimensional dataset, we are using established methods. This allows for descriptive summaries to identify causal drivers, clusters, cohorts, and predictive relationships:
Method – Example/Application

• Hierarchical Clustering – Identifies city archetypes (e.g., “Equity-Focused Innovators”)
•  Fixed-Effects Regression – Tests drivers of policy ambition (e.g., β=0.38** for climate staff size → justice scores)
•  Rationale Framing – Extracts business-case rationale patterns (e.g., “co-benefit framing” vs “cost savings framing” prevalence)
•  Correlation – Detects geographic innovation clusters (e.g., Atlantic tidal energy corridor)

5. Visualization & Knowledge Translation
To maximize accessibility and impact across audiences, this project utilizes interactive visual analytics tools. These outputs transform complex findings into intuitive, explorable formats – bridging technical depth and executive decision-making:

• Dynamic Policy Radars: Compare cities across 13 themes (filterable by region/population size and other dimensions)
•  Relationships, contrasts and clustering based on various dimensions and factors
•  Investment Flow Maps
•  Geospatial allocation of capital by sector
•  Outlier Case Studies: Deep dives into novel technology and program approaches that may have broader applicability.

6. Methodological Approach

• Policy Traceability: All scores linked to public sources (indexed).
•  Actionable Findings: 84 indicators surface implementable insights (e.g., Cities with >3 FTEs in climate equity adopt 2.1× more anti-displacement policies).
• Mixed-Methods Depth: Integrates statistical validity with contextual intelligence.  

Full methodological appendices—including codebooks, regression specifications, and sensitivity analyses—will accompany the final report.
Methodology Anchors: Framework: C40 Cities • Scoring: ICLEI Pathways • Validation: FCM Green Fund Guidelines • Peer Review: SSHRC Climate Policy Consortium