Policing ‘sexting’: Responsibilization, respectability and sexual subjectivity in child protection/crime prevention responses to teenagers’ digital sexual expression
Bibliographic record
Abstract
This article examines the motivations, techniques and potential consequences of the governance of teenage sexting. I examine the over-representation of white, middle-class, heterosexual, female sexters, and abstinence from sexting discourses in the ‘Respect Yourself’ child protection/crime prevention initiative. This campaign, I suggest, exploits slut shaming in an effort to responsibilize teenage girls for preventing the purported harms that may flow from sexting—including humiliation, sexual violations and criminalization—for both themselves and their peers. I examine this responsibilization effort through the lens of critical whiteness, queer, girlhood/young feminist and porn studies’ theorizations of the politics of sexual respectability and sexual subjectification and argue that this campaign simultaneously: reveals anxieties about the decline of the moral authority of the white, middle-class, heterosexual nuclear family; constitutes certain teenage girls’ unintelligibility as sexual subjects; and, undermines teenage girls’ ability to challenge a normative sexual order in which they are often blamed extra/legally for their sexual victimization.
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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 | 0.003 | 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 | 0.005 | 0.023 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".