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Chapter 4 Unintentional Discrimination: Disparate Impact Spring 2009

Employment Regulation in the Workplace: Basic Compliance for Managers by Robinson, Franklin, and Wayland. Chapter 4 Unintentional Discrimination: Disparate Impact Spring 2009. Answers to Wonderlich. Question Answer Question Answer

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Chapter 4 Unintentional Discrimination: Disparate Impact Spring 2009

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  1. Employment Regulation in the Workplace: Basic Compliance for Managersby Robinson, Franklin, and Wayland Chapter 4 Unintentional Discrimination: Disparate Impact Spring 2009

  2. Answers to Wonderlich Question Answer Question Answer 1 3 15 0.31 2 3 16 e 3 2 17 4 4 Yes 18 4 5 4 19 3 6 2 20 F 7 4 21 1 8 1 22 3,5 9 5 23 31 10 40 24 2 11 3 25 1 12 $.90 26 1500 13 4 27 2 14 3 28 1

  3. Answers to Wonderlich Question Answer Question Answer 29 3 41 1 30 1 42 1 31 1,5 43 6 32 $31.85 44 2 33 1 45 15 34 3 46 $8.40 35 20 47 1 36 .1 48 25% 37 6 49 3,7 38 2 50 $320 39 4 40 2,3,4

  4. Griggs v. Duke Power Company • Griggs v. Duke Power Company 401 U.S. 424 (1971) • Five operating departments: • (1) Labor • (2) Coal Handling • (3) Operations • (4) Maintenance, and • (5) Laboratory and Testing

  5. Griggs v. Duke Power Company • Facially Neutral Selection Criteria: • High school diploma or a GED. • Two aptitude tests. • Wonderlich Personnel Test. • Bennett Mechanical Comprehension Tests.

  6. Griggs v. Duke Power Company • High school diploma or a GED. • 1960 North Carolina census, 34% of white males had completed high school, compared to only 12% of black males • Two aptitude tests. • White candidates, 58% would pass. • Black candidates, 6% would pass.

  7. Griggs v. Duke Power Company • Even though the same standards were administered to all applicants, the standards excluded a disproportionate number of blacks from favorable consideration. • The Major Problem: The requirements were not necessary to perform two of the job categories: the coal handling and maintenance jobs.

  8. Griggs v. Duke Power Company • Employees who had not completed high school or had not taken the test (employees who had been hired before the new standards were implemented in 1965) had performed satisfactorily in the jobs which now required GED and passing test scores.

  9. Disparate Impact • Disparate Impact (unintentional discrimination) • A facially neutral selection criterion has the effect of disqualifying a disproportionate number of protected class members. • This is usually demonstrated by a manifest statistical imbalance.

  10. Disparate Impact • Prima Facie Case: (1) Identify a specific employment practice. (2) Offer reliable statistical evidence the the practice causes the exclusion of sufficiently substantial number of applicants because of their membership in a protected group. • (Wards Cove Packing Co. v. Atonio, 490 U.S. 642, 657, (1989))

  11. Employment Practices with Potential Disparate Impact • Height Requirements • Weight Requirements • Education Requirements • Physical Agility Requirements • Cognitive Ability Tests • Language Requirements • Arrest Records • Conviction Record • Marital Status • Credit Reports

  12. Methods for Establishing Statistical Imbalances • Two or three standard deviations. • Standard deviations are a measurement of the probability that a result is a random deviation from the predicted result. • A 95% confidence interval. • Four-Fifths Rule.

  13. A 95% Confidence Interval • A confidence interval gives an estimated range of values which is likely to include an unknown population parameter, the estimated range being calculated from a given set of sample data.

  14. Four-Fifths Rule • The EEOC & OFCCP have adopted a rule of thumb under which they will generally consider a selection rate for any race, sex, or ethnic group which is less than four-fifths (4/5ths) or eighty percent (80%) of the selection rate for the group with the highest selection rate as a substantially different rate of selection. (Source: 44 Fed. Reg. 11,996).

  15. Four-Fifths Rule Selection rateSelection rate of the protected < .8of the group class with the highest rate

  16. Four-Fifths Rule • For example, if the hiring rate for Whites [other than Hispanic] is 60%, for American Indians 45%, for Hispanics 48%, and for Blacks 51%, and each of these groups constitutes more than 2% of the labor force in the relevant labor area, a comparison should be made of the selection rate for each group with that of the highest group (whites). • These comparisons show the following impact ratios: • American Indians 45/60 or .75 • Hispanics 48/60 or .80 • Blacks 51/60 or .85 Source: 44 Fed. Reg. 11,996 (Mar. 2, 1979).

  17. Four-Fifths Rule • Should adverse impact determinations be made for all groups regardless of their size? • Answer: No. Section 15A(2) calls for annual adverse impact determinations to be made for each group which constitutes either 2% or more of the total labor force in the relevant labor area, or 2% of more of the applicable workforce. • For hiring, such determination should also be made for groups which constitute more than 2% of the applicants; and for promotions, determinations should also be made for those groups which constitute at least 2% of the user's workforce. • Note that there are record keeping obligations for all groups, even those which are less than 2%. Source: 44 Fed. Reg. 11,996 (Mar. 2, 1979).

  18. Four-Fifths Rule Griggs v. Duke Power Co. Of the 181 White applicants, taking the Wonderlich test, 105 pass. Of the 102 Black applicants , 6 passed. 6 105 102181 .06 < .8 (.58) .06 < .48 < .8 or .06/.58 = .103 which is less than .8

  19. Test of Significance and Four-Fifths Rule • Q: Is it usually necessary to calculate the statistical significance of differences in selection rates when investigating the existence of adverse impact? • A: No. Adverse impact is normally indicated when one selection rate is less than 80% of the other. The federal enforcement agencies normally will use only the 80% (4/5ths) rule of thumb, except where large numbers of selections are made. • Source: Equal Employment Opportunity Commission, Uniform Employee Selection Guidelines Interpretation and Clarification (Questions and Answers).

  20. Standard Deviation Rule σx= (ρ) (1- ρ) n Where: p = proportion of one group N = the number selected pn = expected value (representation) μx ± 2σx = the confidence interval

  21. Standard Deviation Rule Standard Deviation Rule Total Other Applicants Total PG Applicants Sx= Total Applicants Selected X X Total Applicants Total Applicants

  22. Standard Deviation Rule Of the 181 White applicants, taking the Wonderlich test, 105 pass. Of the 102 Black applicants , 6 passed. Sx = 102 181 X 111 X 283 283

  23. Standard Deviation Rule Of the 181 White applicants, taking the Wonderlich test, 105 pass. Of the 102 Black applicants , 6 passed. Sx = 102 181 Total applicants who passed X 111 X 283 283 = .36 X .64 X 111 % of test takers who were black 25.57 = = 5.057

  24. Standard Deviation Rule Standard Deviation Rule If the black applicants (102) were selected at the same proportion that they were represented in the test-taking (a total of 283 applicants), we would expect 40 Blacks to have been hired. Blacks were 36% of those taking the test (102/283) from which 111 total applicants passed. Hence: 111 X .36 = 40 [expected representation]

  25. Standard Deviation Rule At + 3 Sx we would expect the selection of blacks to fall within a range of 25 to 55. 40 + (5.057 X 3). Selecting only6falls more than six Sx (6.72) from the expected representation. 6 25 40 55 -6sx -3sx +3sx

  26. Applicants with High School Diplomas - Race BlacksWhites Total Applied PassedApplied Passed Applied Passed Male 110 37146 81256118 Female 48 1836 3284 50 Total158 55182 113 340 168 (.348) (.621) .348 < .8(.621) .348 < .497 or .348/.621 = .56 which is less than .8 Yes, Disparate Impact

  27. Applicants with High School Diplomas - Sex BlacksWhites Total Applied PassedApplied Passed Applied Passed Male 110 37146 81256118 Female 48 1836 3284 50 Total158 55182 113 340 168 (.461) (.594) .594 < .8(.461) [Females have the highest rate] .594 < .369 or .594/.461 = 1.29 which is greater than than .8 No Disparate Impact

  28. Applicants Passing Dexterity Test BlacksWhites Total Applied PassedApplied Passed Applied Passed Male 37 3781 76118113 Female 18 1632 2850 44 Total55 53113 104 168 157 (.96) (.92) . 96< .8 (. 92 ) [note blacks had the highest passing rate] .96 < .768 or .96/.92 = 1.04 which is greater than .8 No Disparate Impact

  29. Hired-After 2nd Test BlacksWhites Total Applied PassedApplied Passed Applied Passed Male 37 3776 4411381 Female 16 1628 2844 44 Total53 53104 72 157 125 (1.0) (.692) Note: 100% of Blacks were passing both tests were hired This is compared to 69.2% of whites passing both.

  30. Bottom Line Statistics BlacksWhites Total Applied HiredApplied Hired Applied Hired Male 110 37146 4425681 Female 48 1636 2884 44 Total158 53182 72 340 125 (.335) (.396) .335 < .8(.396) .335 < .316 or .335/.396 = .846 which is greater than .8

  31. Practice Problem BlacksWhites Total Applied PassedApplied Passed Applied Passed Male 110 47146 71256118 Female 48 1836 3284 50 Total158 65182 103 340 168 Analyze using both the Four-Fifths Rule and Three Standard Deviation Rule for Race and Gender

  32. Disparate Impact • Employer’s Rebuttal: The criterion creating the imbalance is a business necessity (job-related).

  33. Challenging Statistics • Relevant labor market: • For statistical evidence to be probative, the statistical pool or sample used must logically be related to the employment decision at issue and the statistical method applied to the pool or sample must be meaningful and suitable under the facts and circumstances of the case. • (Hazelwood School Dist. v. U.S., 433 U.S. 299, 308, (1977))

  34. Challenging Statistics • Sample Size: the sample size may be too small and thus the selection or rejection of a single individual would substantially affect proportional outcomes. • (29 C.F.R. § 1607.3D)

  35. Challenging Statistics • Sample Size • The general convention suggests that correlational studies require at least 30 subjects. • In statistical analysis, the larger the sample size, the greater the degree of precision. The smaller the size, the greater the probability of random error.

  36. Challenging Statistics • Countervailing Statistics: • Stock Analysis* (a measure of representativeness): • Employers may choose to show that their internal workforce has more protected class members than one would expect in the relevant external labor market or: Proportion of Protected Class inProportion of Protected Employer’s Internal WorkforceClass in the Relevant LaborMarket • * The basis for utilization analysis in chapter 6 >

  37. Challenging Statistics • Stock Analysis • An employer has the following relevant labor market for laborers: 116,000 individuals of whom 13,950 are African-Americans, 10,000 are Hispanic, 2500 are of Asian ancestry and the remainder are nonHispanicwhite (89,580). • Proportional estimates relevant labor market: 77.2% white, 12% Black, 8.6% Hispanic, and 2.2% Asian.

  38. Challenging Statistics • Employees holding positions classed as laborers in the employer’s workforce are as follows: • 5400 total current employees in the classification. • 950 are Black. • 390 are Hispanic • 65 are Asian • 3995 are White

  39. Challenging Statistics • Employer’s workforce: • 5400 current employees. • .176 or 17.6% are Black. • .072 or 7.2% are Hispanic • .012 or 1.2% are Asian • .74 or 74.0% are White

  40. Challenging Statistics • Comparison of relevant labor market to employer’s workforce: Black .176 < .12 or .176/.12 = 1.467 Hispanic .072 < .086or .072/.086 = .837 Asian .012 < .022or .012/.022 = .545 White .74 < .772or .74/.772 = .959

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