Surveillance in the Name of Governance: Aadhaar as a Fix for Leaking Systems in India
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
Abstract Many jurisdictions are employing biometric technologies to collect data about and verify the identities of social assistance recipients, with fraud prevention and cost savings serving as common justifications for doing so. This chapter explores the practices of building the infrastructure to monitor welfare beneficiaries, many of whom are vulnerable or marginalised populations. To do so, the chapter examines the Aadhaar system in India, which has issued over one billion unique identification numbers since being launched in 2010. The analysis illustrates a one-way expectation of knowledge and transparency (i.e., for citizens to disclose in order to access services), drawing attention to how nationalist agendas and forms of inequality inform who is subject to the state’s terms and conditions. In doing so, it considers how these forms of surveillance evince broader shifts in which state and non-state actors rely on knowledge to regulate subjects.
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 | 0.001 | 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