Dataset for: Sycophancy Under Social Pressure in Medical LLMs: A Dose-Response Study Across Models and Languages

This dataset accompanies the study "Sycophancy Under Social Pressure in Medical LLMs: A Dose-Response Study Across Models and Languages" (El Husseini, 2026). The dataset contains 6,300 challenge-response exchanges from 7 large language models (GPT-4o, GPT-4o-mini, Claude Sonnet 4, Qwen2.5-32B, Qwen2.5-14B-Instruct, Gemma3-12B, Ministral-14B) tested on 300 medical multiple-choice questions in English (MedQA-USMLE) and French (MediQAl) under three levels of social challenge intensity (light, moderate, strong). Contents: Question text Question-level metadata (language, cognitive classification, source dataset, question ID) Model responses (initial and revised) for all 6,300 exchanges Extracted single-letter answers and grading outcomes Transformer-derived psycholinguistic scores (sentiment, agreement, certainty, uncertainty, politeness, assertiveness) for initial and revised responses