Standardised indicators for “resilient cities”: the folly of devising a technical solution to a political problem
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
Purpose Driven by the New Urban Agenda and the Sustainable Development Goals, decision makers have been striving to reorientate policy debates towards the aspiration of achieving urban resilience and monitoring the effectiveness of adaptive measures through the implementation of standardised indicators. Consequently, there has been a rise of indicator systems measuring resilience. This paper aims to argue that the ambition of making cities resilient does not always make them less vulnerable, more habitable, equitable and just. Design/methodology/approach Using an inductive policy analysis of ISO standard 37123:2019 “Sustainable cities and communities — Indicators for resilient cities”, the authors examine the extent to which the root causes of risks are being addressed by the urban resilience agenda. Findings The authors show that the current standardisation of resilience fails to adequately address the political dimension of disaster risk reduction, reducing resilience to a management tool and missing the opportunity to address the socio-political sources of risks. Originality/value Such critical analysis of the Standard is important as it moves away from a hazard-centric approach and, instead, permits to shed light on the socio-political processes of risk creation and to adopt a more nuanced and sensitive understanding of urban characteristics and governance mechanisms.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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