Abstract
GSI:detect is a new shared task for the recognition and classification of gender stereotypes (GSs) presented at EVALITA 2026. The task adopts a perspectivist approach in order to enhance the high subjectivity of GS recognition and analysis on a dataset of challenging short texts in Italian. GSI:detect is organized in: A) a Main Task (GS Detection) in which systems have to assign to a text the GS value, a numerical score that quantifies the extent to which a given text exhibits or refers to a GS; B) an optional Subtask (GS Classification) in which systems, given six pre-defined categories (e.g. role, relational, etc.) must assign one to each text. Seven teams from academic and non-academic environments took part in the challenge, with a total of 50 submitted runs for the Main Task and a total of 43 submitted runs for the optional Subtask. We present here first an overview of the GSI:detect task, the dataset and the evaluation criteria, then outline and discuss the participants’ results.