Child pornography offenders detected by surveillance of the Internet and by other methods
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Notice bibliographique
Résumé
BACKGROUND: Availability of child pornography on the Internet has created new opportunities for offending. It has been noted that many people charged with offences relating to this had not previously been identified as sexual offenders against children. AIM: Our aim was to compare the characteristics of people charged with child pornography offences as a result of police monitoring of the Internet with those detected by other means. We hypothesised that those apprehended via the Internet would be more likely to be older and less likely to have severe psychiatric disorder or to have been previously charged with a sexual offence involving contact with a child than those identified by other means. METHODS: Data were extracted from the findings of clinical examinations by the authors either in the course of preparing reports for court, or in the course of providing treatment. RESULTS: There were 52 men detected by police Internet surveillance and 53 men detected by other means, the latter including 16 men who had not been charged with an offence at the time of referral. Those detected via the Internet were more likely to be in possession of very large quantities of child pornography. Those detected by other means were more likely to have major psychiatric and substance abuse disorders and to report childhood sexual abuse. A subgroup analysis of the 89 people who were facing charges at the time of the assessment found that the only significant differences were in the amount of material and the history of sexual abuse. CONCLUSIONS: The men recruited to this study, conducted over a period of nearly 10 years, reflect the changing nature of the technology used to commit this type of offence in that time. The characteristics of the subjects did not confirm the stereotype of an Internet child pornography offender who was high functioning and otherwise well adjusted and carried a low risk of other types of offences.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle