The child sexual abuse material survivor as homo sacer: bare life under cyber-libertarianism
Bibliographic record
Abstract
This article applies Agamben’s formulation of political abandonment to theorise the political status of survivors of child sexual abuse material under the internet’s cyber-libertarian regime. While the production, distribution and possession of child sexual abuse material is illegal in most jurisdictions, it is functionally permitted by the current legal and administrative structures that govern the internet, as evident in annual increases in child sexual abuse material availability for over two decades. The article collates distribution data for three female survivors subject to extensive online distribution of recordings of their abuse, as well as online offender discourse about the three survivors, to highlight the ease with which online networks of child sex abusers can predate on victims depicted in child sexual abuse material. The article analyses the extraordinary sociolegal position occupied by child sexual abuse material victims who can be subject to serious ongoing harm with little risk of consequences for the majority of offenders, while legislative efforts to afford them relief and protection continue to be obstructed by a cyber-libertarian coalition of actors in the technology sector, civil society and politics. By exploring how child sexual abuse material survivors are denied their rights to freedom, justice and privacy in the name of those very same rights, we demonstrate how Agamben’s notion of the ‘homo sacer’ makes visible the abject plight of those survivors and the hypocrisy of the internet’s juridical order.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.048 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| 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".