From Jailbird to Jailbait: Age of Consent Laws and the Construction of Teenage Sexualities
Bibliographic record
Abstract
Age of consent laws provide an obvious example of direct state intervention into the sexual lives of teenagers. But the reach of this body of law extends further than this, operating in complex and contradictory ways that generate a range of distributive effects. For example, the roles that parents and welfare officials play in enforcement decisions have an impact on broader struggles between teenagers, parents, and state officials over teenage sexual activity and sexual values. Further, in those contexts where age of consent laws do not apply or where they are not enforced, teenage sex will be left in the realm of existing power relationships where factors such as age, sex, race, and class come to the forefront. Given the multiple levels upon which they operate, age of consent laws provide an excellent vehicle for exploring the role of law not simply in the repression of teenage sex, but also in the constitution of teenage sexualities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".