1. Illegal for employers to discriminate (hiring, discharge, compensation, terms, conditions, or privileges of employment) because of: Race Color Religion Sex National Origin Who has to comply? Private (1964) and public (1972) companies with 15 or more employees Title VII 1964 (Basic Protections) Original protected groups (others now include age and disability)

2. Total Charges 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 1,000 Retaliation Race Sex Disability Age National Sexual Religion Pregnancy Equal (Total) Origin Pay 31,073 EEOC Claims by Discrimination Type in 2014 37,955 25,369 20,588 6,862 9,579 3,400 3,549 938 26,027

3. Differential Treatment Discrimination (intentionally treating individuals differently based on their membership in a protected group. 1) Plaintiff [Standards for a Establishing a Prima Facie Case] Applicant belongs to a protected group Applicant applied and was qualified for a job the employer was trying to fill Applicant, though qualified, was rejected for the position Employer continued to seek applicants with applicant’s qualifications 2)Defendant: A legitimate nondiscriminatory reason exists for the rejection of the person 3) Plaintiff: The organization's reason for the rejection is a pretext for discrimination

4. Green laid off as part of a large downssizing effort Green patricipated in a "stall-in" and "lock-out" aganist the company – both illegal activities Company advertised for jobs. One of the jobs was for the position of "mechanic" --- Green's former position with the company Green applied for his former job and was rejected Green filed race discrimination lawsuit McDonnell Douglas v. Green 1) Green successfully formed a prima facie case: 1) he was a member of a protected group, 2) he applied for and was qualified to perform the job 3) the company refused to hire Green, and 4) the organization continued to seek applicants for the position. 2) Company articulated a legitimate reason for their refusal to rehire Green (e.g., illegal behavior) 3) Green had the option to demonstrate that the company's reason was a pretext for discrimination (e.g., white workers were treated less harshly for performing similar behavior as Green)

5. Phase 1: Challenger --- Evidence (often statistical) that a specific, identified employment practice disproportionately excludes protected group members Phase 2: Company --- Proof that the challenged practice is job-related and consistent with business necessity Phase 3: Challenger --- Proof there is an equally valid, job-related practice with less or no adverse impact Disparate Impact Process

6. Promotion Requirements  Pass the Wonderlic Personnel Test and Bennett Mechanical Aptitude Test  Possess a high school diploma Effects of These Requirements  Tests eliminated roughly 94% of blacks as compared to 43% of whites.  12% of Blacks possessed a high school diploma in NC versus Whites (34%) Race Discrimination Lawsuit Filed The Supreme Court ruled against the company: All tests/requirements must be job related Intention to discriminate is not required for discrimination to exist All tests must meet acceptable professional guidelines for psychometric worth Employment discrimination may result from the effects of one's actions Griggs v. Duke Power

7. What Counts as a Disability?

8. Affirmative Action Programs Must meet "Strict Scrutiny" Basics of Strict Scrutiny Analysis ~ Did the university present evidence that a compelling interest was present (the goal of a diverse student body is essential to its mission)? Were the means to attain diversity (e.g., specific procedures/processes used) narrowly tailored to the stated goal? Is the use of race necessary? Are other, less restrictive (e.g., race-neutral) alternatives available to produce diversity? Affirmative Action Prohibits employment discrimination based on race, color, religion, sex, or national origin. Governs any entity with government contracts that total $10,000 or more in a 12-month period. Also, contains an affirmative action requirement. Executive Order 11246 as amended by 11375

9. CaseMajor Findings California v. Bakke (1978) --- Medical school admissions A specific % or number of openings based on race illegal Race permissible as “plus” factor Diversity can be a “compelling interest” Strict scrutiny analysis advocated United Steelworkers v. Weber (1979) Upheld AAP to increase % Black skilled workers to ~ 39% Plan was temporary and did not unnecessarily trammel the interest of white employees and goal to eliminate manifest racial imbalance Wygant v. Jackson Board of Education (1986) Plan to keep percent of minority teachers (and layoff more senior nonminorities is not narrowly tailored Role modeling is NOT a compelling state interest Majority rights trammeled upon (layoffs) Johnson v. Transportation Agency (1987) Plan was temporary and not unnecessarily trample on the rights of the majority Use of gender a “plus” factor to obtain minority representation ( manifest imbalance) Grutter v. Bollinger (2003) --- Law School admissions Diversity is a compelling state interest in the context of university admissions. Plan was narrowly tailored; Race was one of the many factors Does not unduly harm nonminority applicants Goal to terminate use of racial preferences as soon as practicable (achieving a “critical mass”) Gratz et al. v. Bollinger (2003) --- Undergraduate admissions Giving 20 points to minorities virtually guaranteed admission (race a decisive factor) AAP NOT narrowly tailored Fisher v. University of Texas (2013/2016) - Undergraduate admissions Strict scrutiny NOT applied by lower courts UT AAP is legal; Strict scrutiny analysis met Schette v. BAMN (2014) Voters in the States may choose to prohibit the consideration of racial preferences in educational admissions

10. Remedial in nature (e.g., past evidence or findings of discrimination) Narrowly tailored plan (e.g., l imited duration ; a temporary time frame exists) Use of minority status as a "plus" factor; a minor factor/one of many considered -- U. Michigan cases --- Grutter (diversity) Yes; Gratz (20 pts.) No Does not trammel on the rights of the majority (e.g., layoffs) Key Affirmative Action Factors

11. 1) Quid Pro Quo (sex as a condition of employment or basis for employment decisions) 2) Environmental harassment -- Behavior of a sexual nature that is: ~ Types of Sexual Harassment ~  Unwelcome  Unreasonably interferes with one’s work performance or creates an intimidating, hostile, or repressive work environment) Reasonable person standard

12. Recruitment Sources (Techniques) In-House (e.g., hiring or promotion from within the organization) Newspapers, Trade/Professionals Publications Outside Companies (Headhunters, Employment/Temp Agencies, Executive Search Firms Job or College Fairs Internet-based Private sites (e.g., Monster; LinkedIn) Professional Organizations Company web site

13. Some Factors in Considering Recruiting Sources Cost Time Requirements Number and Quality of Applicants Type of Job (e.g., manual labor, managerial) Type of Applicant (knowledge, skills, demographic and minority representation)

14. Recruiter Characteristics --- Demographics (e.g., gender, race, age) Functional job area (similarity to job being recruited) Personality (e.g., warmth, enthusiasm, supportive, personable) Administration of Recruitment --- Promptness of follow-up contact (short timeframe is best) Amount of information requested of applicant (more information = less # of applicants) Other Recruitment Issues Include salary in recruitment ads?

15. Realistic Job Preview Effects RJP VACCINATION OF EXPECTATIONS SELF SELECTION INTERNAL FOCUS OF CONTROL COMMITMENT TO CHOICE OF ORGANIZATION PERCEPTION OF HONESTY AND CARING ROLE CLARITY COPING MECHANISMS DEVELOP FOR NEW JOBS INVOLUNTARY TURNOVER JOB PERFORMANCE NEEDS ARE MATCHED TO ORGANIZATIONAL CLIMATE JOB SATISFACTION VOLUNTARY TURNOVER TENURE IN THE ORGANIZATION

16. Men wanted for hazardous journey. Low wages, bitter cold, long hours of complete darkness. Safe return doubtful. Honour and recognition in event of success. ~ Ernest Shackleton's advertisement for 1914 Trans-Antarctic Expedition Realistic Job Preview!!!

17. Selection Ratio (SR) = n N Job openings Applicants Test Validity [Criterion-related]: The extent to which test scores correlate with job performance scores [Range is from 0 to 1.0] Test Utility Key Points

18. Proportion of “Successes” Expected Through the Use of Test of Given Validity and Given Selection Ratio, for Base Rate.60. (From Taylor & Russell, 1939, p. 576) Selection Ratio Validity.05.10.20.30.40.50.60.70.80.90.95.00.60.60.60.60.60.60.60.60.60.60.60.05.64.63.63.62.62.62.61.61.61.60.60.10.68.67.65.64.64.63.63.62.61.61.60.15.71.70.68.67.66.65.64.63.62.61.60.20.75.73.71.69.67.66.65.64.63.62.61.25.78.76.73.71.69.68.66.65.63.62.61.30.82.79.76.73.71.69.68.66.64.62.61.35.85.82.78.75.73.71.69.67.65.63.62.40.88.85.81.78.75.73.70.68.66.63.62.45.90.87.83.80.77.74.72.69.66.64.62.50.93.90.86.82.79.76.73.70.67.64.62.55.95.92.88.84.81.78.75.71.68.64.62.60.96.94.90.87.83.80.76.73.69.65.63.65.98.96.92.89.85.82.78.74.70.65.63.70.99.97.94.91.87.84.80.75.71.66.63.75.99.99.96.93.90.86.81.77.71.66.63.80 1.00.99.98.95.92.88.83.78.72.66.63.85 1.00 1.00.99.97.95.91.86.80.73.66.63.90 1.00 1.00 1.00.99.97.94.88.82.74.67.63.95 1.00 1.00 1.00 1.00.99.97.92.84.75.67.63 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00.86.75.67.63 Note: A full set of tables can be found I Taylor and Russell (1939) and in McCormick and Ilgen (1980, Appendix B). (SR)

19. Mean Standard Criterion Score of Accepted Cases in Relation to Test Validity and Selection Ratio (From Brown & Ghiselli, 1953, p. 342) Validity Coefficient Selection Ratio.00.05.10.15.20.25.30.35.40.45.50.55.60.65.70.75.80.85.90.95 1.00.05.00.10.21.31.42.52.62.73.83.94 1.04 1.14 1.25 1.35 1.46 1.56 1.66 1.77 1.87 1.98 2.08.10.00.09.18.26.35.44.53.62.70.79.88.97 1.05 1.14 1.23 1.32 1.41 1.49 1.58 1.67 1.76.15.00.08.15.23.31.39.46.54.62.70.77.85.93 1.01 1.08 1.16 1.24 1.32 1.39 1.47 1.55.20.00.07.14.21.28.35.42.49.56.63.70.77.84.91.98 1.05 1.12 1.19 1.26 1.33 1.40.25.00.06.13.19.25.32.38.44.51.57.63.70.76.82.89.95 1.01 1.08 1.14 1.20 1.27.30.00.06.12.17.23.29.35.40.46.52.58.64.69.75.81.87.92.98 1.04 1.10 1.16.35.00.05.11.16.21.26.32.37.42.48.53.58.63.69.74.79.84.90.95 1.00 1.06.40.00.05.10.15.19.24.29.34.39.44.48.53.58.63.68.73.77.82.87.92.97.45.00.04.09.13.18.22.26.31.35.40.44.48.53.57.62.66.70.75.79.84.88.50.00.04.08.12.16.20.24.28.32.36.40.44.48.52.56.60.64.68.72.76.80.50.00.04.07.11.14.18.22.25.29.32.36.40.43.47.50.54.58.61.65.68.72.60.00.03.06.10.13.16.19.23.26.29.32.35.39.42.45.48.52.55.58.61.64.65.00.03.06.09.11.14.17.20.23.26.28.31.34.37.40.43.46.48.51.54.57.70.00.02.05.07.10.12.15.17.20.22.25.27.30.32.35.37.40.42.45.47.50.75.00.02.04.06.08.11.13.15.17.19.21.23.25.27.30.32.33.36.38.40.42.80.00.02.04.05.07.09.11.12.14.16.18.19.21.22.25.26.28.30.32.33.35.85.00.01.03.04.05.07.08.10.11.12.14.15.16.18.19.20.22.23.25.26.27.90.00.01.02.03.04.05.06.07.08.09.10.11.12.13.14.15.16.17.18.19.20.95.00.01.01.02.02.03.03.04.04.05.05.06.07.07.08.08.09.09.10.10.11 Selection Ratio Example

20. Simple Regression Equation Multiple Regression y = a + bx Test Score Slope y-intercept Predicted Score  y = a + b x + b x + b x ….. Predicted Score  y-intercept 1 1 2 2 3 3 Weights Regression Basic Process: All applicants take every test. Scores are weighted and combined to yield a predicted score for each applicant. Applicants scoring above a set cutoff score are considered for hire Key Points: Regression is a compensatory approach. That is, a high score on one test can compensate for a low score on another. Best for tests to not relate to each other, but relate highly to the criterion.

21. How Four Job Applicants with Different Predictor Scores Can Have the Same Predicted Criterion Score Using Multiple Regression Analysis Applicant Score on X Score on X Predicted Criterion Score 1 2 A 25 0 100 B 0 50 100 C 20 10 100 D 15 20 100 Note: Based on the equation Y = 4X + 2X. 1 2  Compensatory Example

22. Predictor 1 Criterion Predictor 2 R = r + r For example, if r =.60 and r =.50, then R = (.60) + (.50) =.36 +.25 =.61 22 2 c.12 1c 2c 1c 2c c.12 r r 1c 2c Independent Predictors

23. R = 2 c.12 r r - 2r r r 2 1c 2c 12 1c 2c For example, if the two predictors intercorrelate.30, given the validity coefficients from the previous example And r =.30, we will have 12 R = =.47 2 c.12 1 - r 2 12 (.60) + (.50) - 2(.30)(.60)(.50) 2 1 – (.30) 2 rr r 1c 2c 12 Interrelated Predictors Predictor 1 Predictor 2 Criterion

24. WAB 100 0 Pass Fail Cutoff score Paper & Pencil Math Test 100 0 Pass Fail Cutoff score Paper & Pencil Aptitude Test 100 0 Pass Fail Cutoff score Basic Process: All applicants take every test. Applicant must achieve a passing score on every test to be considered for hire. Key Point: A multiple cut-off approach can lead to different decisions regarding who to hire versus using a regression approach. Multiple Cutoff Approach xx x

25. Interview 100 0 Pass Fail Cutoff score Paper & Pencil Knowledge Test 100 0 Pass Fail Cutoff score Work Sample Test 100 0 Pass Fail Cutoff score Multiple Hurdle Approach Basic Process : All applicants take the 1 st test. Pass/fail decisions are made on the 1 st and subsequent tests and only those who pass can continue on to the next test [a sequential process]. Key Point : Useful when a lengthy, costly, and complex training process is required for the position. Eliminated from the selection process xxxxx xxx xxxxx xx

26. Basic concept: Small differences in test scores might reasonably be due to measurement error. Therefore, you do not want small differences in test scores to trump all other consideration in ranking individuals in hiring.” (p. 82). Banding

27. Banding (cont.) SED Banding Types FixedSliding........ Both use the top score to establish the top of the band All those from the band are selected before those from the lower band.......... Bands slide down after each person is removed from the top (bands re-established) 98 94 92 88 98 94 92 88 Example of a band of 6 points