Bibliographic record
Abstract
Based on an ethnography of French trials for trafficking in human beings and aggravated procuring, this article seeks to contribute to the analysis of the reframing, in penal terms, of the struggles engaged in the name of social justice and women’s rights, of which anti-trafficking policies are particularly emblematic. Studying the judging practices and logics at stake during trials reveals how fantasized representations of the pimp and the victim take on substance. In particular, I argue that judges invoke a set of gendered, sexualized and racialized extra-legal norms, which, along with their legal foundations, constitute their knowledge base and impose a moral and penal hierarchy among litigants. Therefore, not only does this analysis contribute to defining the contours of the elusive figures of the pimp and the victim in the penal arena, it also exposes how maintaining public order is based on the perpetuation of a gendered and sexual national order in the name of gender justice.
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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 | 0.003 | 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 | 0.004 | 0.002 |
| 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".