Socio-demographic signals modestly aid pluralistic offensiveness modeling, especially after aggregation and with explicit reasoning
This paper (arXiv:2610.37896v1) evaluates when and how annotators' socio-demographic information helps pluralistic offensiveness prediction using three multi-annotator datasets and prompted/trained LLMs. The authors find demographic gains are small and inconsistent for individual predictions but clearer at group/population levels after aggregation; framing prediction as an explicit decomposition into a baseline plus a demographic-specific deviation and using explicit reasoning yields better baseline and shift estimates and improves final predictions compared with direct conditioning alone.