Climate change adaptation in the urban planning and design research: missing links and research agenda
Bibliographic record
Abstract
This paper investigates the extent and the nature of how the urban planning literature has addressed climate change adaptation. It presents a longitudinal study of 157 peer-reviewed articles published from 2000 to 2013 in the leading urban planning and design journals whose selection considered earlier empirical studies that ranked them these journals. The findings reveal that the years 2006–07 represent a turning point, after which climate change studies appear more prominently and consistently in the urban planning and design literature; however, the majority of these studies address climate change mitigation rather than adaptation. Most adaptation studies deal with governance, social learning, and vulnerability assessments, while paying little attention to physical planning and urban design interventions. This paper identifies four gaps that pertain to the lack of interdisciplinary linkages, the absence of knowledge transfer, the presence of scale conflict, and the dearth of participatory research methods. It then advocates for the advancement of participatory and collaborative action research to meet the multifaceted challenges of climate change.
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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 | 0.155 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.019 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.027 | 0.041 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".