Legal Conceptions of Harm Related to Sexual Images Online in the United States and Canada
Bibliographic record
Abstract
This article examines the history of legal discussion of the harms of child pornography possession and viewing in the United States and Canada, with special attention to the evolving conception of direct harms to children and youth pictured in these images. The article further addresses ongoing uncertainty about harms associated with images that do not record an instance of sexual abuse, but where the harm arises solely from non-consensual distribution of nude and/or sexual images. Achieving greater understanding and recognition of both the similarities and differences between the harms that arise from the “permanent record of abuse” and from ongoing circulation and use of images beyond the subject’s control are necessary in order to equip both clinical and legal practitioners with the knowledge they need in order to provide appropriate support for victims of the varied forms of sexual abuse related to sexual image online.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.034 | 0.043 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".