Knowing and governing smart cities: Four cases of citizen engagement with digital urbanism
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
Research on smart urbanism predominantly focusses on the production of digital knowledge. In response, this paper probes the potential and limitations of digital devices producing the kinds of knowledge needed for governing urban environments. Based on four case studies in Europe, the paper investigates what kinds of knowledge become privileged and what kinds of knowledge get overlooked when digital devices are deployed to inform urban governance. We find that non-digital knowledges are easily eclipsed, yet remain vital to effective and inclusive urban environmental governance. Our findings suggest that digital technologies need to be developed in ways that are attentive towards the different kinds of knowledge (digital and non-digital) that may be necessary for effective and inclusive urban governance. This holds for the knowledges that are used to develop digital devices and the knowledges intended to be generated through them, as well as openness towards unanticipated or overlooked knowledges that still matter.
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