Bibliographic record
Abstract
The “surveillant assemblage” and its attendant notion of the “data double” have held a central place within surveillance theory for nearly a quarter of a century. Haggerty and Ericson proposed the concept as a way to push back against prevailing, and limited, surveillance theory rooted in Foucauldian panopticism and Orwellian notions of “big brother.” Yet, in an informational and technological landscape that has changed significantly since 2000, and continues to change rapidly, it seems vital to ask whether a concept like the surveillant assemblage continues to have meaningful application to surveillance today. In this Dialogue, we bring together surveillance scholars from across the humanities and social sciences to look at how the “surveillant assemblage” has contributed to surveillance scholarship and informed our thinking about surveillance in society. The Dialogue includes six interventions from scholars who apply, extend, refashion, and critique the surveillant assemblage, as well as a closing response from Kevin Haggerty—the first time he has chosen to directly revisit the idea of the surveillant assemblage. In his response, Haggerty outlines a proposal for shifting our attention to understanding surveillance as a process of “surveillantization.”
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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 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".