Rethinking public participation in the smart city
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
In efforts to become “smart cities,” local governments are adopting various technologies that promise opportunities for increasing participation by expanding access to public comment and deliberation. Scholars and practitioners encounter the problem, however, of defining publics—demarcating who might participate through technology‐enhanced public engagement. We explore two case studies in the city of Calgary that employ technologies to enhance public engagement. We analyzed the cases considering both the definition of publics and the level of citizen participation in areas of participatory budgeting and secondary suites. Our findings suggest that engaging the public is not a straightforward process, and that technology‐enhanced public engagement can often reduce participation towards tokenism. City councillors and planners need to critically confront claims that smart cities necessarily enhance participation. Moving beyond tokenism requires understanding “public” as a plural category. Municipal governments should seek to proactively engage citizens and communities utilizing helpful resources including, but not limited to, digital tools and smart technologies. This would allow planners to keep a “finger on the pulse” of publics' concerns, better identifying and addressing issues of equity and social justice. It is also important to consider how marginalized publics can best be recognized in order to bring their concerns to the fore in decision‐making processes.
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 | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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