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SemEval-2022 Task 4: Patronizing and Condescending Language Detection

1 Jul 2022SemEval (NAACL) 2022 7archive 2025-07-28

Carla Perez-Almendros, Luis Espinosa-Anke, Steven Schockaert

This paper presents an overview of Task 4 at SemEval-2022, which was focused on detecting Patronizing and Condescending Language (PCL) towards vulnerable communities. Two sub-tasks were considered: a binary classification task, where participants needed to classify a given paragraph as containing PCL or not, and a multi-label classification task, where participants needed to identify which types of PCL are present (if any). The task attracted more than 300 participants, 77 teams and 229 valid submissions. We provide an overview of how the task was organized, discuss the techniques that were employed by the different participants, and summarize the main resulting insights about PCL detection and categorization.

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Tasks

Binary ClassificationBinary Condescension DetectionClassificationMUlTI-LABEL-ClASSIFICATIONMulti-Label ClassificationMulti-label Condescension DetectionSemEval-2022 Task 4-1 (Binary PCL Detection)SemEval-2022 Task 4-2 (Multi-label PCL Detection)

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Datasets

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DPM

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Binary Condescension Detection DPM RoBERTa Baseline F1-score 49.1 #5 of 5 Archive leaderboard report
Multi-label Condescension Detection DPM RoBERTa Baseline Macro-F1 10.4 #5 of 5 Archive leaderboard report
SemEval-2022 Task 4-1 (Binary PCL Detection) DPM RoBERTa Baseline F1-score 49.1 #1 of 1 Archive leaderboard report
SemEval-2022 Task 4-2 (Multi-label PCL Detection) DPM RoBERTa Baseline Macro-F1 10.4 #1 of 1 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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