To Protect and Responsibilize: The Discursive Explosion of Combining Youth Sexuality, Human Trafficking, and Online Spaces
Bibliographic record
Abstract
The emergence of social media and digital technologies has resulted in new protectionist laws, policies, and mandates aimed at regulating the sexual behaviour of women and girls in online spaces. These neoliberal responsiblization strategies are aimed at shaping good, young digital citizens and have become further amplified through increased concerns about domestic human trafficking and victim vulnerability. This protectionism, however, is not always reflected in courtroom proceedings, revealing a tension between the protection and responsiblization of victims of trafficking in Canada. Using R v Oliver-Machado (2013) as a case study, we examine the ways in which the defence counsel’s reliance on commonplace defence tactics used in sexual assault cases responsibilize the young complainants in an attempt to discredit their victimhood and reconstruct them as online sexual risk takers.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.018 | 0.049 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".