Surveillance Capitalism and Platform Policing: The Surveillant Assemblage-as-a-Service
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
Based on empirical research on training webinars, interviews, and promotional material from Vigilant Solutions, this paper investigates the surveillance regime enabled by platform policing: the implementation of cloud-based platforms, designed and run by private corporations, that provide mass surveillance-driven simulations for a range of police operations, including predictive policing, targeted surveillance, and tactical and strategic governance. Building on Amoore’s (2016) work on “cloud geographies,” this paper argues that the platform model embodied by Vigilant Solutions involves multivalent processes of de- and reterritorialization in which new technological and datalogical spaces are formed and these erode older societal boundaries of private, public, and state. Specifically, Vigilant Solutions leverages its multi-sided platform business model through the deterritorializing, cloud-based concatenations of surveillant technologies. It then argues that the resultant reterritorialized cloud space, which is accessible through its Vigilant Investigative Centre (VIC) platform, fuses mass surveillance data from diverse private, public, and state sources in a simulated geography. Further, the VIC furnishes to law enforcement an array of data analytics that exploits this cloud geography to enable a boundary-crossing surveillance regime of association analysis and proximal suspicion.
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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 | 0.004 | 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 | 0.001 |
| 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 it