Between Smart Images and Fast Trucks: Digital Surveillance and Obscured Labour in Hyderabad, India
Bibliographic record
Abstract
In Hyderabad, India, the growing information technology (IT) sector relies on ensuring safe and efficient movements of people and objects, and the city government and private actors have embraced the promise of digital surveillance to reach these goals. The new Telangana State, created in 2014, has built a new city-wide network of smart cameras, and at ‘hackathons’ programmers develop new digital tools, often connected to this network, that will technologically ‘solve’ social problems. In this article, I examine the system of CCTV cameras and programmers’ investments in these systems, and explore how migrant Vaddera stonecutters use cellphones to evade patrolling officers monitoring the streets where they carry the granite stones that they cut and load to construct the city’s buildings. Expanding on what Gilbert Simondon calls ‘the margin of indeterminacy’, this article reveals gaps in the digital infrastructure of surveillance—even as its integration and completion combine human and technical elements.
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.
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 | 0.001 | 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 | 0.002 |
| 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 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".