The challenges of aligning the scales of urban climate science and climate policy in London and Manchester
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
The longevity of our urban buildings and streetscapes means that they will need to perform to a satisfactory standard in a context of climate change, with an increasing propensity for higher temperatures and extreme weather events accentuated by the urban heat island. Research funded to explore future climate in cities is frequently required to work directly with stakeholders to co-produce useful knowledge and tools. This study considers the relationship between a suite of projects linking future climate to the city, neighbourhood and building scales and the policy contexts of London and Manchester. It is contended that successful knowledge translation is aided by multi-scalar, strategic approaches to urban climate, and on the clear designation of the desired policy outcomes and supporting evidence and resources required. This, in turn, highlights the role of sustained government support for city-region spatial planning and building standards to facilitate successful translation into policies.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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