Everyday urbanisms and the importance of place: Exploring the elements of the emancipatory smart city
Bibliographic record
Abstract
Two of the most striking features of smart city discourses are the centrality of technology as a driver of transformational change and the strange ‘placelessness’ of its visual narrative. Whether envisaged in Kenya or Singapore, the commercial smart city is represented as a ‘city in a box’, seemingly capable of solving complex social issues through algorithms and technical innovation. Recently a robust literature has emerged that is critical of the techno-determinism inherent in smart city discussions. This paper expands on this critique by arguing that by solely focusing on the material dimensions of technologically informed urban change, devoid of context, we miss an opportunity to uncover an important moment in contemporary urbanity. By foregrounding the human dimensions of technology appropriation and the interface with livelihoods in their particular spatial contexts, this paper consciously decentres the dominant smart city discourse by arguing for the foregrounding of local dynamics. This paper rejects the universalisms embedded in smart city promises and argues that by provincialising the idea of smart urbanism, opportunities are presented for understanding the true markers of contemporary urbanism. Critical debates on the smart city, and by extension the need to consider smart urbanism contextually and as an infrastructure, relationally, together with the conceptual insights provided by postcolonial science and technology studies, contribute to a proposed frame for researching the ongoing dynamic between contemporary urban life and technological innovation. Empirical vignettes from urban Africa are used to illustrate the multiple dimensions of the interface between livelihoods and technology appropriation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.066 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| 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".