Smart Cities as Hybrid Spaces of Governance: Beyond the Hard/Soft Dichotomy in Cyber-Urbanization
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
This paper problematizes the dichotomy of hard (technocratic) and soft (societal) approaches to the smart city. Smart cities are reviewed as hybrid spaces that transcend the sum of the social and the technical. By providing platforms for enabling, monitoring, digitalizing, formalizing, and amassing information about collective and personal experiences and behaviors, smart cities accelerate the customization of existing urban services and establish new spaces of socialization, accumulation and regulation, including in hitherto hard-to-reach realms of everyday and personal life. These experiences signify the emergence of cyber-physical-social spaces, featuring the hybridization of the digital, governance, and sociocultural domains. The production of such hybrid spaces of governance is reviewed through 50 urban-level strategies for smart cities in different countries across the world. The analysis confirms the tendencies towards a hard/soft fusion and the ever-deepening interpenetration of the digital, physical, and social elements in smart cities. This suggests epistemological problems of separating the hard and soft domains. However, this integration still creates political and analytical tensions that are arguably evident in the early stages of the digital transition.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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