I got a idea but I'm not sure whether it is right or not. The coefficients estimated by the common GLM, such as probit, logit, multinomial logit, ordered logit, etc, are "Location/Scale". We cannot estimate the locations and scales separetely, due to the identification problem. That causes many difficulties. For example, we cannot compare the estimated coefficients directly, because the difference between coefficients may be caused by the different scales, rather than the different locations. Some researches figured out some ways to overcome this problem. Now, under certain assumptions, location and scale can be estimated separately. In STATA, we use the commands - oglm or hetprob - to fullfil this goals. Therefore, I guess the Location and Scale in the SPSS are used to fullfil similar goals.
If you are want to learn about this issue a bit more, there are some reference you may be interested in.
Allison, Paul D. . 1999. “Comparing Logit and Probit Coefficients Across Groups.” Sociological Methods & Research 28(2): 186-208.
Williams, Richard. 2009. “Using Heterogeneous Choice Models to Compare Logit and Probit Coefficients across Groups.” Sociological Methods & Research 37(4): 531-559.
Buis, Maarten L.. 2011. “The Consequences of Unobserved Heterogeneity in a Sequential Logit Model.” Research in Social Stratification and Mobility 29(3): 247-262.
Logistic Regression: Why We Cannot Do What We Think We Can Do, and What We Can Do about It
Hope they are helpful, and hope I made a right guess.