Circular cities: exploring local government strategies to facilitate a circular economy
Bibliographic record
Abstract
Cities are growing rapidly, and the systems of production and consumption that support this growth are contributing to the depletion of natural resources and pollution of the environment. The circular economy model offers an alternative to the predominant take-make-dispose economic system. Local municipalities are seen to have the capacity to encourage sustainable development of the built environment. This paper aims to explore the role of strategic planning in facilitating a circular economy in urban settings. In particular, this research asks: How are local governments facilitating circular economy initiatives through strategic planning? What are the opportunities and barriers when applying circular economy principles through local strategic planning? The research approach used for this paper is a comparative case study of two international municipalities: the City of Melbourne, Australia and the City of Malmö, Sweden. Current strategic planning practice was examined with a focus on circular economy themes. The findings reveal that strategic urban planning can translate circular economy objectives into actions within specific urban areas, although barriers still exist to fully integrating the circular economy model.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".