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Enron Mail |
When looking at representation and determining if there is advserse impact = you need to look at the percentages as below: Total 1 =09 2 =09 = =09 3 4 5 NR = =20 Males 26=09 4=09 (15.4%) 16 (61.7%) 6=09(23.= 1%) 0 (0.0%) 0 (0.0%) 0 (0.0%) =20 Females 6 0 ( 0.0%) 3 (50.0%) 2 (33.3%)= 1 (16.7%) 0 (0.0%) 0 (0.0%) You want to determine if women (or minorities, or over 40), based on their = representation, are being adversely effected. You look at the total women = and how their distribution over the ratings equates, then you look at the t= otal men and how their distribution equates--you are looking at them indivi= dually and not overall. After this is calculated you determine by rating c= ategory if women are within 80% of the ratings men received-- if they are w= ithin 80% there is no adverse impact. If it is less than 80% there is adve= rse impact. For example, let's look at the "2" category. There are 16 of = 26 men that received "2's" or 61.5% of the male representation. There are = 3 of 6 females that received "2's" or 50% of the female representation. T= o determine if the females are being adversely effected you take 50% and di= vide it by 61.5% and get 81.3%--as this is more than 80% there is no advers= e impact. Now, let me throw a curve ball. In calculating adverse impact i= t is assumed that if women (or minorites) are being effected more it is a b= ad thing. In the case of looking at ratings this may not be the case so a = standard formula cannot be applied. For example, if more women are gettin= g "1's" than the males this is not a bad thing but if more women are gettin= g "5"s this is a bad thing! You have to use some judgement on this because= if more female's based on their representation are getting 3's maybe that = is bad and maybe that is good--you have to look at the overall picture. Wh= en you are calculating adverse impact on employment actions like hires or t= erminations it is very straight forward but when looking at it from a ratin= g perspective it can get tricky because you are making comparisions over mu= tiply categories which mean different things--the 1's being good and the 5'= s being not so good.=20 I would recommend that you proceed with the chart as I typed it above and n= ot try to build in the adverse impact piece. The HR person looking at the = data in the PRC meeting will need to do some quick calculations based on ho= w the distribution is for determining adverse impact. If you have any ques= tions or if I can help please let me know. =20 -----Original Message----- From: =09Yowman, Andrea =20 Sent:=09Tuesday, June 05, 2001 10:05 AM To:=09Acevedo, Felecia Subject:=09FW: PRC Demographics Please give me your thoughts -----Original Message----- From: =09Inglis, Elspeth =20 Sent:=09Tuesday, June 05, 2001 9:28 AM To:=09Yowman, Andrea; Cash, Michelle Cc:=09Corteselli, Gina Subject:=09FW: PRC Demographics FYI this is the revised demographic screen. Please review and advise. thanks Elspeth << OLE Object: Picture (Device Independent Bitmap) <<=20 <Embedded Picture (Metafile)<
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