Toward a Dracula urbanism: Smart city building in Flint and Jakarta
Bibliographic record
Abstract
We study two places experiencing the rise of both the real-estate state and smart city building, Jakarta, Indonesia and Flint, USA. Our core thesis: these real-estate states work through and make a kind of urbanism that we term Dracula urbanism. We identify Dracula urbanism as a deep-reaching, human-punishing unfolding that is simultaneously a state of mind, a mode of institutional operation, a vision of people, one gaze onto growth's true needs and a kind of growth produced. Our Dracula urbanist notion that is seen to engulf real-estate states has four central features. First, the political and economic resources to drive smart city building are secured through ever-thickening parasitic relations, particularly with upper-level sources of power and authority. Second, city building involves unrelenting drives to kill and destroy (not rehabilitate or therapeutize) supposedly deep civic ‘cancers’, such as the poor's presumed anti-civic, morally and culturally deficient dispositions and ways. Third, city building is promoted through strategically deploying the materiality and discursive terrors of decline. Fourth, local real-estate states are decisively integrated into ‘planetary urbanizations’ through circuits of smart-growth capital investment and techno-scientific claims to expertise. All of these, we chronicle, are vintage characteristics of Stoker's rendition of Dracula. The results suggest that the cultural politics of in-your-face revanchism that Neil Smith helped us to see, and is still present in cities such as Flint and Jakarta, is today accompanied by an equally punishing, complicated and adroitly adapting state politics in these places.
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How this classification was reachedexpand
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".