Experimenting with urban stressors: a network-based approach to systemic resilience through the URSA framework
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding how shocks cascade through interdependent urban systems is essential for designing effective resilience strategies. We introduce the Urban Resilience and Sustainability Alliance (URSA), a network-based framework that represents a city’s physical, socioeconomic, and sociocultural dimensions as a multi-domain directed network of indicators, coupled with the URSA-RSPM (Realistic Stress Propagation Model). URSA integrates structural diagnostics with an adaptive contagion algorithm to quantify network resistance through defined metrics and to simulate both passive and policy-driven recovery. Computational experiments illustrate how URSA-RSPM identifies latent vulnerabilities and evaluates “what-if” interventions. In a Vancouver case study of a hypothetical tariff shock to the Public Finance and Business Environment indicators, the model reveals rapid cross-domain cascades when no action is taken and demonstrates that timely fiscal support can contain widespread failure. By serving as a city-scale digital living lab, URSA-RSPM enables planners and policy analysts to explore multi-hazard and compound-risk scenarios in a safe, data-driven environment, supporting iterative policy design and adaptive urban governance.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it