Circular economy strategies in cities as a value‐driven approach to infrastructure management
Bibliographic record
Abstract
Abstract The circular economy (CE) is a promising paradigm for reducing the environmental impact and preserving value within modern production systems, including civil infrastructure. However, there is a mismatch between common assumptions in CE thinking, largely developed for smaller‐scale consumer products, and infrastructure systems characterized by their permanency and complexity. This paper discusses the applicability of CE for infrastructure provisioning and operation while examining how CE is being used in urban infrastructure policies. Our analysis of six large American and European cities reveals that current CE policy for construction focuses on closing material loops, even in cases where it may have limited effectiveness. Notably, London and Amsterdam lead efforts to narrow resource loops through life extension strategies. Yet, for urban infrastructure value to be meaningfully preserved, more attention should be given to the specific contexts of growth and existing infrastructure stock, and higher‐order circularity strategies such as retrofitting and use intensification.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".