Who benefits from this interpretation of validity? Follow the incentive: even if Kolmogorov-Smirnov tests are relevant, the absence of data normalization before application can distort the perception of similarity. This often benefits sponsors seeking to mask divergences by manipulating the distribution context, turning a non-significant result into a success.