Charting the design and implementation of the smart city: the case of citizen-centric bikeshare in Hamilton, Ontario
Bibliographic record
Abstract
Previous scholarship on the smart city has expressed concern at the top-down, technocratic nature of smart technologies and the lack of meaningful citizen participation in their development. In this paper, we utilize instrumentalization theory to trace the initiation, design and deployment of a specific smart city initiative: bikeshare in Hamilton, Ontario. Smart bikeshare is increasingly seen as complicit in processes of social stratification, serving a predominately white, middle-class demographic and particular locales. Our case study reveals the potential of reflexive design praxes to reconfigure bikeshare as a platform for both instrumental and social value. In particular, we highlight how collaborative, open and inclusive forms of urban governance can enroll a broad range of civic actors to create a scheme that embodies diverse but complimentary goals and ideologies. We conclude that instrumentalization theory provides a conceptual means to open up the “black box” of urban design to critical interrogation, and to identify how to enact participatory design and citizen-centric smart urbanism.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.018 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".