in a general case like this ... where the plaintiff has to show proof of
discrimination ... the burden is especially difficult
there are some preliminaries of course ...
if the women make more than the males ... then we would agree it would be
"hard" to argue sex discrimination in terms of salaries ... though i guess
the women could "try" to argue that the difference is NOT large enough (but
in any case, the "court" is not going to waste it's time if this cursory
test is not confirmed ... ie, men have higher salaries than women)
it is like age discrimination ... if someone brings an age discrimination
case to EEOC ... and the facts show that older people ARE being hired or
retained ... when this person is being let go ... it will be essentially
impossible to win an age discrimination case
but, in the current situation, let's say that we have identified 15
measures that relate to work and work productivity ... 1 to 15 ... and
let's just assume that for each ... higher values mean better ...
scenario A: on all of these, women have lower mean values than males ...
AND male salaries are higher ... it will be very hard if not impossible to
argue (and win) sex discrimination ...
scenario B: on all of these, women have higher mean values than males ...
BUT have lower salaries
if 1 to 15 are valued ... it might be rather easy to argue and win a sex
discrimination case
the overall problem in cases like these will be that it would rarely if
ever be a situation like scenario B ...
it seems to me that only in certain cases ... would statistical information
really be that helpful in arguing and persuading on the side of
discrimination ...
so, ultimately, it will not generally boil down to anything statistical
but, rather ... some logical and rational conclusion that is made based on
the facts of the case ... many of which are "behind the scenes" and
unobservable through any real data source
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