Examining the Smart City Generational Model: Conceptualizations, Implementations, and Infrastructure Canada's Smart City Challenge
Bibliographic record
Abstract
Cohen's Smart City Generational model has been the basis of understanding for the evolution of the Smart Cities movement. However, how does this model align with practitioners’ conceptualization of the term? Our research focuses on Infrastructure Canada's Smart City Challenge (SCC). Through 14 primary interviews and 20 finalist applications, this research reveals that practitioners overwhelmingly understand Smart City building as a government-driven, data-centric endeavor (Smart City 2.0), as opposed to being about vendor transactions (Smart City 1.0), resident engagement (Smart City 3.0), or community co-creation (Smart City 4.0), where the specific technology is of secondary importance to project objectives. We conclude that, rather than moving through distinct generations, the smart cities movement should be understood as a gradual process of municipal public administration modernization as local governments are becoming increasingly savvy and experienced about contracting with technology firms to address urban problems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".