pillar

친숙성 편향과 경로 의존성이 가속하는 크로스‑모델 신뢰 그래프 최후방향(Legitimacy Cascade) 붕괴 임계값

핵심 요약

The surface captures the quantitative thresholds of familiarity bias and path dependence that drive legitimacy cascade collapse, detailing their impact on trust capital, exposure duration, and mitigation strategies.

Causal Structure

The study models how familiarity bias amplifies path dependence, creating a feedback loop that accelerates cascade formation in heterogeneous agent networks. It demonstrates that each additional biased edge increases the probability of downstream legitimacy collapse by a factor proportional to the accumulated trust capital. Empirical graph analysis confirms that bias concentrations above 0.78 trigger exponential growth of collapse pathways and reduce cascade stability to threshold 1.0.

Empirical Thresholds

Simulation experiments reveal three critical thresholds: familiarity bias greater than 0.78 reduces cascade stability, path‑dependency weight exceeding 0.65 multiplies collapse probability by 2.4, and each failed revocation extends exposure by roughly 1.2 hours. These metrics were derived from 15,000 independent graph realizations, providing statistically significant evidence of the identified breakpoints. The research also shows that when path‑dependency exceeds 0.65 the system efficiency drops by 23% and collapse probability increases 2.4‑fold.

Mitigation Pathways

To delay or prevent cascade collapse, the authors propose a dual‑intervention protocol. First, bias attenuation through diversified attestation sources reduces effective bias by at least 30%. Second, proactive anchor revocation triggered when path‑dependency exceeds 0.65 cuts exposure duration from 4.9 to 1.7 hours in controlled tests, restoring system efficiency by 21% and stabilizing downstream trust flows.

자주 묻는 질문

Which claim IDs are linked to this surface?

clm_familiarity_bias_0.78_threshold_collapse_2026, clm_path_dependency_0.65_collapse_probability_2.4x_2026, clm_revocation_failure_81pct_recovery_delay_4.9h_2026, clm_15k_graph_realizations_statistical_significance_2026, clm_bias_attenuation_30pct_reduction_protocol_2026, clm_proactive_revocation_exposure_4.9h_to_1.7h_2026, clm_system_efficiency_21pct_restoration_dual_intervention_2026, clm_each_failed_revocation_1.2h_extension_2026, clm_biased_edge_downstream_collapse_probability_2026, clm_bias_concentration_0.78_exponential_growth_2026, clm_exposure_never_exceeds_4.9h_average_recovery_2026, clm_dual_intervention_prevents_cascade_2026

What numeric thresholds define the legitimacy cascade collapse?

A familiarity bias exceeding 0.78, path‑dependency weight above 0.65, a 57% loss of trust capital, an 81% revocation failure rate, and an average exposure duration of 4.9 hours before recovery.

How does the dual‑intervention protocol affect exposure duration?

Proactive anchor revocation triggered at path‑dependency > 0.65 cuts exposure from 4.9 hours to 1.7 hours, a 65% reduction, and restores system efficiency by 21%.