Transnational Governance and the Urban Politics of Nature-Based Solutions for Climate Change
Bibliographic record
Abstract
Abstract Multiple visions for how urbanism can respond to the climate crisis and foster sustainability have emerged on the international agenda, including the ecocity, low-carbon city, smart city, and resilient city. These competing visions have been joined by one deploying “nature-based solutions.” We examine how nature-based solutions are emerging as a linchpin holding together the nature and climate agendas and what this means for where and by whom nature-based solutions are forming part of transnational urban governance. We argue that this field is animated by four frames connecting urban nature and climate: nature for resilience, nature for mitigation, the integrated benefits of nature, and nature first. Diverse actors, from conservation organizations to design firms to transnational municipal networks, draw on these frames and adopt new governance arrangements such that what it means to govern climate in the city is shifting. How this emerging nature–climate governance complex is structured will generate new momentum for governing urban nature over the coming decade.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".