This note intends to complement the recent discussion in Hayes and Coutts (2020) by focusing on (i) the loading equality condition for the population identity of coefficient alpha and reliability of multiple-indicator measurement scales, as well as (ii) the potential utility of alpha when this condition is not satisfied. We show that the alpha and reliability coefficients can be very close at the population level in certain cases of loading inequality. In addition, we point out that in any studied population the identity of alpha and scale reliability (coefficient omega) is an improbable event. We discuss implications for communication and behavioral research with large samples, which are becoming increasingly widely used in large-scale and nationally representative studies. Findings of the article are then illustrated using numerical data. We conclude with proposed recommendations for the use of coefficients alpha and omega by communication and behavioral scientists concerned with evaluating scale reliability.