Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Models

This research introduces a framework to quantify the miscalibration between rhetorical intensity and epistemic grounding in Large Language Models. Applying an epistemic-rhetorical marker taxonomy to argumentative texts, the study reveals a distinct LLM epistemic signature, showing models overuse certain rhetorical devices and perform hesitancy markers more frequently than human authors.