Rethinking the Smart City as an Intelligent City Archway
Bibliographic record
Abstract
Urban intelligence is the ability to understand and navigate the physical and digital dimensions of “connected complex urban places”. For example, new infrastructures (e.g., sensors, Internet of Things {IoT} devices like smart lamp posts) are needed to capture and represent places in software platforms and on the Internet. New spatial skills and spatial thinking are needed to navigate these new interfaces and networks of places. This paper aims at understanding urban intelligence by exploring variations in how smart cities have been conceptualized; how citizens have been placed within the smart city; and how Canada’s smart cities initiative has placed on urban (and highly spatial) problems over digital technologies. The metaphor of the Roman arch is used to describe the interdependency of the building blocks of smart cities. Components (building blocks) of the smart city, be they openness, resilience or inclusion, must all be present, and build towards what we argue is the keystone of urban intelligence. We discuss how these components lead to a new consideration of the smart city, the Intelligent City.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.052 |
| Scholarly communication | 0.020 | 0.028 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".