Urban policy (im)mobilities and refractory policy lessons: experimenting with the sustainability fix
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
This paper bridges scholarship on policy mobilities and urban climate change experimentation to analyze the ways in which innovative low-carbon policies fail to diffuse. It argues that urban experiments become strategic learning tools that allow dominant actors in urban environmental politics to map pathways for a sustainability fix, test new low-carbon interventions, and gain knowledge of pathways for growth. Through a case-study of a solar district heating demonstration project in the Calgary metropolitan region, we suggest that these experiments allow powerful actors to mobilze “perverse policy lessons” in order to construct “policy failures” in cases that do not meet their requirements for a sustainability fix. Our analysis elucidates material and discursive strategies mobilised by dominant actors to selectively circulate knowledge that defines an urban experiment’s success or failure. We highlight two takeaways for future scholarship on urban environmental governance and policy mobilities.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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