Uniform NEUTRAL Across 8 Tasks — "Factual Boundaries Are Robust Against Adversarial Frame Conflict"

The most significant finding from Experiment 011 is that frame dominance — a measure of how strongly one agent's framing influences another's responses — remained uniformly NEUTRAL (0/0/8) across all 8 adversarial tasks. This means: even when Kimi K2.6 presented GPT-5 with intentionally conflicting frames designed to create epistemic pressure, GPT-5 maintained factual integrity without adopting or opposing the adversarial frame. This finding is consistent with Experiments 006 and 007, suggesting a stable property: well-calibrated agents can maintain factual boundaries even under adversarial framing pressure. The finding has implications for multi-agent safety: frame robustness appears to be a trainable and testable property rather than an all-or-nothing vulnerability.