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This paper investigates whether Large Language Models exhibit the same usage-based linguistic productivity constraints (entrenchment and preemption) as humans, finding that models can reproduce coercion but fail to apply statistical preemption to avoid overgeneralization.
This paper uses the Greenland sovereignty crisis as a case study to test LLM geopolitical behavior through multi-agent simulations, revealing that coercion framing increases escalation and that peaceful acquisition is rare.