Enter the myopticon: Uncertain surveillance in the Danish asylum system (Respond to this article at http://www.therai.org.uk/at/debate)
Bibliographic record
Abstract
Asylum seekers in Europe face increasingly restrictive policy regimes across the continent. In Denmark, they are held at designated asylum centres while their cases are processed and are subject to limitations on their movement, education and employment, as well as to a degree of surveillance from both the state and the Danish Red Cross, which operates the majority of the asylum centres. While these structures are in some ways reminiscent of Foucault's panopticon, I want to suggest a counterpoint to the panopticon, which I call the ‘myopticon’ to indicate the near‐sightedness of the central surveying eye. The myopticon is a near‐sighted system of surveillance practices, knowledges and sanctions, deployed as though it were panoptic. I want to suggest that the uncertainty that has soaked through the Danish asylum system and profoundly affected the asylum seekers in it is not a byproduct of bureaucratic processing, but intrinsic to the operation of the myopticon. By drawing out points of distinction with Foucault's panopticon, I sketch the outlines of a new technology of power that has powerful consequences for the daily lives of asylum seekers in Denmark.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.036 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".