“It's Just an Image, Right?”: Practitioners’ Understanding of Child Sexual Abuse Images Online and Effects on Victims
Bibliographic record
Abstract
Child sexual abuse images online (CSAIO) present new and daunting challenges for practitioners working in the field of child sexual abuse (CSA). Current understanding of the phenomenon is severely limited due to a lack of theoretical and empirical research in the area. This article reports findings from a study that examined practitioners’ experiences with, and views of, CSAIO. Participants differed in how they conceptualized what constituted online CSA images and held varying degrees of concern regarding the potential effects of CSAIO on the child. Some practitioners were uncertain about whether child victims of CSAIO experience particular effects different from or over and above those caused by conventional (non-Internet related) CSA. A key finding was that most practitioners did not have a clear understanding of CSAIO. This article includes recommendations for future research regarding the implications of technology in the field of CSA.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".