Visions of Public Safety, Justice, and Healing: The Making of the Rape Kit Backlog in the United States
Bibliographic record
Abstract
Large backlogs of untested sexual assault kits have recently come to light in cities across the United States, fueling public controversies over criminal justice responses to sexual assault and sexual assault forensic services. This article examines these controversies to reveal how kit backlogs have come to matter as a political problem. Using a range of textual data, this article traces the history of the sexual assault kit backlog in New York City and contemporary national campaigns around kit backlogs to examine how sexual assault kit backlogs are being defined as threats to public safety, justice, and healing for victims of crime. Drawing on theoretical insights from actor-network theory, institutional ethnography, and feminist technoscience studies, this article examines the implications of the current framing of kit backlogs for sexual assault survivors and their allies, and current dialogues about criminal justice responses to sexual assault.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".