  Probability Quantification (PQ) predictions of the efficacy of
safety-critical protective systems is challenging. Yet, the popularity of PQ
methodologies (e.g., Probabilistic Risk Assessment (PRA), Quantitative Risk
Analysis (QRA) and Probabilistic Safety Analysis (PSA)) is growing and can now
be found written into regulatory rules. PQ in predictive modeling is attractive
because of its grounding in probability theory. But, certain important safety
related events are not probability-measurable which is problematic for
risk-analytic methodologies that rely on PQ computations. Herein, we identify
why the dynamics of available information play an essential role in governing
the fidelity of PQ, and why PQ in the analysis of safety-critical protective
systems is limited by the un-measurability of certain critical events. We
provide an historical example that provides a practical context for our
observations. Finally we discuss the implications of measurability for
regulatory decision-making governed by recent nuclear industry legislation
advocating increased use of risk informed, performance-based regulation for
advanced reactor licensing.
