Canadian smart cities: Are we wiring new citizen‐local government interactions?
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
Governments around the world are developing smart city projects, with the aim to realize diverse goals of increased efficiency, sustainability, citizen engagement, and improved delivery of services. The processes through which these projects are conceptualized vary dramatically, with potential implications for how citizens are involved or engaged. This research examines the 20 finalists in the Canadian Smart Cities Challenge, a Canadian federal government contest held from 2017 to 2019 to disburse funding in support of smart city projects. We analyzed each of the finalist proposals, coding all instances of citizen engagement used to develop the proposal. A significant majority of the proposals used traditional types of citizen engagement, notably citizen meetings, round tables, and workshops, to develop their smart city plans. We also noted the use of transactional forms of citizen engagement, such as apps, and the use of social media. Despite the general rhetoric of innovation in the development of smart cities, this research finds that citizens are most commonly engaged in traditional ways. This research provides cues for governments that are developing smart city projects, placing an emphasis on the importance of the process of smart city development, and not simply the product.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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