Anticipatory climate governance: Limits to current practices in Montreal
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
City leadership appears key in driving the transition towards a liveable future. Trying to bring specific visions of the future into present decisions and actions is what anticipatory governance is about. However, the literature has highlighted a lack of discussion of the use of anticipatory practices in urban climate governance. What anticipatory practices do cities employ to tackle climate change and work towards a desirable future? What limitations does it involve? The City of Montreal provides an effective case study as, recently, it has been the locus of large projects representative of the three dominant approaches of climate action-climate planning, carbon control and reporting and experimentation. Our results indicate that traditional tools such as reporting, urban planning regulations and bylaws are the strategies urban actors rely on to advance towards desirable futures. And yet, they seem to be missing opportunities to act in the present for these desirable futures, especially to increase equity in urban climate action. This research offers a concrete and empirical exploration of cities' anticipatory practices regarding climate change, ultimately contributing to the literature on anticipatory urban climate governance.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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