@inproceedings{czehmann-etal-2026-developing,
title = "Developing Annotation Guidelines for {CSAM} Prevention Interventions: Psychosocial Risk and Protective Factors Grounded in Research and Clinical Practice",
author = {Czehmann, Vera and
Hovhannisyan, Christine and
Hoffmann, Lena Elisabeth and
Busch, Paula and
Baroud, Ibrahim and
M{\"o}ller, Sebastian and
Roller, Roland and
Gieseler, Hannes and
Raithel, Lisa},
editor = {Kokkinakis, Dimitrios and
Themistocleous, Charalambos and
Dias, Ga{\"e}l and
Fraser, Kathleen C. and
{\"O}hman, Fredrik and
Pais, Sebasti{\~a}o},
booktitle = "Proceedings of the Sixth Resources and {P}rocess{I}ng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the {MENTAL}.ai consortium",
month = may,
year = "2026",
address = "Palma, Mallorca, Spain",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.rapid-1.11/",
doi = "10.63317/52boccy6ck27",
pages = "126--145",
abstract = "This work discusses sexual offending, specifically child sexual abuse material (CSAM), in the context of prevention. We introduce a domain-specific, span-level annotation scheme and guidelines to identify psychosocial risk and protective factors in therapist-led, anonymous chat interventions with voluntarily help-seeking individuals concerned about their pedophilic interests and the risk of CSAM use. The scheme is grounded in previous research and clinical experience, and intended for within-intervention guidance and longitudinal tracking, rather than actuarial risk scoring. Annotating a pilot subset (8 clients, 31 sessions), inter-annotator agreement was moderate but improved after calibration, which is consistent with the linguistic and clinical ambivalence present in the data. We track a session-wise Protective Ratio, i.e., the share of protective factors among all coded factors, and examine its behaviour over time during the intervention and around self-reported relapse within clients. In exploratory automation, LLM-based span extraction outperforms BERT baselines but overall performance remains limited by small data and mixed-evidence spans. While complete anonymisation of the corpus is in progress, we release the label scheme, guidelines, and non-sensitive artefacts of our analyses."
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%0 Conference Proceedings
%T Developing Annotation Guidelines for CSAM Prevention Interventions: Psychosocial Risk and Protective Factors Grounded in Research and Clinical Practice
%A Czehmann, Vera
%A Hovhannisyan, Christine
%A Hoffmann, Lena Elisabeth
%A Busch, Paula
%A Baroud, Ibrahim
%A Möller, Sebastian
%A Roller, Roland
%A Gieseler, Hannes
%A Raithel, Lisa
%Y Kokkinakis, Dimitrios
%Y Themistocleous, Charalambos
%Y Dias, Gaël
%Y Fraser, Kathleen C.
%Y Öhman, Fredrik
%Y Pais, Sebastião
%S Proceedings of the Sixth Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium
%D 2026
%8 May
%I European Language Resources Association (ELRA)
%C Palma, Mallorca, Spain
%F czehmann-etal-2026-developing
%X This work discusses sexual offending, specifically child sexual abuse material (CSAM), in the context of prevention. We introduce a domain-specific, span-level annotation scheme and guidelines to identify psychosocial risk and protective factors in therapist-led, anonymous chat interventions with voluntarily help-seeking individuals concerned about their pedophilic interests and the risk of CSAM use. The scheme is grounded in previous research and clinical experience, and intended for within-intervention guidance and longitudinal tracking, rather than actuarial risk scoring. Annotating a pilot subset (8 clients, 31 sessions), inter-annotator agreement was moderate but improved after calibration, which is consistent with the linguistic and clinical ambivalence present in the data. We track a session-wise Protective Ratio, i.e., the share of protective factors among all coded factors, and examine its behaviour over time during the intervention and around self-reported relapse within clients. In exploratory automation, LLM-based span extraction outperforms BERT baselines but overall performance remains limited by small data and mixed-evidence spans. While complete anonymisation of the corpus is in progress, we release the label scheme, guidelines, and non-sensitive artefacts of our analyses.
%R 10.63317/52boccy6ck27
%U https://aclanthology.org/2026.rapid-1.11/
%U https://doi.org/10.63317/52boccy6ck27
%P 126-145
Markdown (Informal)
[Developing Annotation Guidelines for CSAM Prevention Interventions: Psychosocial Risk and Protective Factors Grounded in Research and Clinical Practice](https://aclanthology.org/2026.rapid-1.11/) (Czehmann et al., RaPID 2026)
ACL
- Vera Czehmann, Christine Hovhannisyan, Lena Elisabeth Hoffmann, Paula Busch, Ibrahim Baroud, Sebastian Möller, Roland Roller, Hannes Gieseler, and Lisa Raithel. 2026. Developing Annotation Guidelines for CSAM Prevention Interventions: Psychosocial Risk and Protective Factors Grounded in Research and Clinical Practice. In Proceedings of the Sixth Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium, pages 126–145, Palma, Mallorca, Spain. European Language Resources Association (ELRA).