Sweeping the city: infrastructure, informality, and the politics of maintenance
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
Uneven development in many North American cities has given rise to an increasing number of homeless encampments as residents seek shelter, sanitation, and other basic needs outside of formally recognized networks. In gentrifying cities, these informal infrastructures are also subject to the recurring violence of sweeps, wherein states remove, seize, or destroy life-sustaining necessities to decrease their visibility and designate space for other uses. The sweep is both a strategy of governance and a viscerally felt phenomenon in which infrastructural networks become terrains of contestation. In this article, we examine the cultural politics of sweeps through the analytic of maintenance. Drawing on examples from Toronto, Ontario, Canada and San Francisco, California, United States, we argue that sweeps are mechanisms of policing that often operate through the apparently benign work of routine maintenance, which in turn iteratively organizes belonging and exclusion in cities. These dynamics have thereby become important sites for infrastructural struggle. With our analysis, we join scholars in the study of infrastructure taking a critical stance toward processes of maintenance and repair, asking questions about what is being maintained, for whom, and toward what end.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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