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The Uniform Guidelines Are a Detriment to the Field of Personnel Selection

Published online by Cambridge University Press:  07 January 2015

Michael A. Mcdaniel*
Affiliation:
Virginia Commonwealth University
Sven Kepes
Affiliation:
Virginia Commonwealth University
George C. Banks
Affiliation:
Virginia Commonwealth University
*
E-mail: [email protected], Address: Virginia Commonwealth University, Snead Hall, 301 W. Main St., PO Box 844000, Richmond, VA 23284-4000

Abstract

The primary federal regulation concerning employment testing has not been revised in over 3 decades. The regulation is substantially inconsistent with scientific knowledge and professional guidelines and practice. We summarize these inconsistencies and outline the problems faced by U.S. employers in complying with the regulations. We describe challenges associated with changing federal regulations and invite commentary as to how such changes can be implemented. We conclude that professional organizations, such as the Society for Industrial and Organizational Psychology (SIOP), should be much more active in promoting science-based federal regulation of employment practices.

Type
Focal Article
Copyright
Copyright © Society for Industrial and Organizational Psychology 2011 

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Footnotes

This paper has benefited substantially from the feedback of several individuals. Their help has been appreciated.

References

Aguinis, H., Culpepper, S. A., & Pierce, C. A. (2010). Revival of test bias research in preemployment testing. Journal of Applied Psychology, 95, 648680. doi:10.1037/a0018714.Google Scholar
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (1999). Standards for educational and psychological testing (2nd ed.). Washington, DC: American Educational Research Association. Google Scholar
Banks, G. C., & McDaniel, M. A. (in press). Meta-analyses and selection procedures. In Schmitt, N. (Ed.), The Oxford handbook of personnel assessment and selection. Oxford, UK: Oxford University Press. Google Scholar
Barrick, M. R., & Mount, M. K. (1991). The Big Five personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44, 123. doi:10.1111/j.1744-6570.1991.tb00688.x.Google Scholar
Barrick, M. R., Mount, M. K., & Judge, T. A. (2001). Personality and performance at the beginning of the new millennium: What do we know and where do we go next? International Journal of Selection and Assessment, 9, 930. doi:10.1111/1468-2389. 00160.Google Scholar
Bartlett, C. J., Bobko, P., Mosier, S. B., & Hannan, R. (1978). Testing for fairness with a moderated multiple regression strategy: An alternative to differential analysis. Personnel Psychology, 31, 233241. doi:10.1111/j.1744-6570.1978.tb00442.x.Google Scholar
Biddle, D. A. (2010). Should employers rely on local validation studies or validity generalization (VG) to support the use of employment tests in Title VII Situations? Public Personnel Management, 39, 307326. Google Scholar
Boehm, V. R. (1977). Differential prediction: A methodological artifact? Journal of Applied Psychology, 62, 146154. doi:10.1037/0021-9010. 62.2.146.Google Scholar
Borneman, M. J. (2010). Using meta-analysis to increase power in differential prediction analyses. Industrial and Organizational Psychology: Perspectives on Science and Practice, 3, 224227. doi:10.1111/j.1754-9434.2010.01228.x.Google Scholar
Bray, D. W., & Moses, J. L. (1972). Personnel selection. Annual Review of Psychology, 23, 545576. doi:10.1146/annurev.ps.23.020172.002553.Google Scholar
Burton, S., Creyer, E. H., Kees, J., & Huggins, K. (2006). Attacking the obesity epidemic: The potential health benefits of providing nutrition information in restaurants. American Journal of Public Health, 96, 16691675. doi:10.2105/AJPH.2004.054973.Google Scholar
Cascio, W. E., & Aguinis, H. (2001). The federal uniform guidelines on employee selection procedures (1978). An update on selected issues. Review of Public Personnel Administration, 21, 200. doi:10.1177/0734371X0102100303.Google Scholar
Ceci, S. J., & Papierno, P. B. (2005). The rhetoric and reality of gap glosing: When the “have-nots” gain but the “haves” gain even more. American Psychologist, 60, 149160. doi:10.1037/0003-066x. 60.2.149.Google Scholar
Cohen, M. S., Aamodt, M. G., & Dunleavy, E. M. (2010). Technical advisory committee report on best practices in adverse impact analyses. Washington, DC: Center for Corporate Equality. Google Scholar
Copus, D. A. (2006). Validation of cognitive ability tests. Letter to Charles James, Office of Federal Contract Compliance Programs (March 27, 2006). Morristown, NJ: Ogletree Deakins.Google Scholar
Daniel, C. (2001). Separating law and professional practice from politics. Review of Public Personnel Administration, 21, 175. doi:10.1177/0734371X0102100301.Google Scholar
Equal Employment Opportunity Commission (EEOC). (1966). Guidelines on employment testing procedures. Federal Register, 31, 6414. Google Scholar
Equal Employment Opportunity Commission (EEOC). (1970). Guidelines on employee selection procedures. Federal Register, 35, 1233312336. Google Scholar
Equal Employment Opportunity Commission (EEOC), Civil Service Commission, Department of Labor, & Department of Justice. (1978). Uniform guidelines on employee selection procedures. Federal Register, 43, 3829039315. Google Scholar
Ewoh, A. I. E., & Guseh, J. S. (2001). The status of the uniform guidelines on employee selection procedures. Review of Public Personnel Administration, 21, 185. doi:10.1177/0734371X0102100302.Google Scholar
Foldes, H. J., Duehr, E. E., & Ones, D. S. (2008). Group differences in personality: Meta-analyses comparing five U.S. racial groups. Personnel Psychology, 61, 579616. doi:10.1111/j.1744-6570.2008.00123.x.Google Scholar
Food and Drug Administration (FDA). (2006). FDA announces plan to strengthen advisory committee processes. Retrieved from http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/2006/ucm108697.htm.Google Scholar
Food and Drug Administration (FDA). (2008). Guidance for industry: Diabetes mellitus—Evaluating cardiovascular risk in new antidiabetic therapies to treat type 2 diabetes: U.S. Food and Drug Administration.Google Scholar
Food and Drug Administration (FDA). (2011a). About science & research at FDA. Retrieved from http://www.fda.gov/ScienceResearch/AboutScienceResearchatFDA/default.htm.Google Scholar
Food and Drug Administration (FDA). (2011b). Science board to the food and drug administration. Retrieved from http://www.fda.gov/AdvisoryCommittees/CommitteesMeetingMaterials/ScienceBoardtotheFoodandDrugAdministration/default.htm.Google Scholar
Gatewood, R. D., Feild, H. S., & Barrick, M. R. (2008). Human resource selection (6th ed.). Mason, OH: South-Western. Google Scholar
Grutter v. Bollinger. (2003). 539 U.S. 306.Google Scholar
Guion, R. M. (1965). Personnel testing. New York, NY: McGraw-Hill. Google Scholar
Guion, R. M. (1975). Recruitment, selection and job placement. In Dunnette, M. D. (Ed.), Handbook of industrial and organizational psychology. Chicago, IL: Rand McNally. Google Scholar
Hartigan, J. A., & Wigdor, A. K. (Eds.). (1989). Fairness in employment testing: Validity generalization, minority issues, and the General Aptitude Test Battery. Washington, DC: National Academy Press. Google Scholar
Herrnstein, R. J., & Murray, C. (1994). The bell curve: Intelligence and class structure in American life. New York, NY: Free Press. Google Scholar
Hunter, J. E., & Hunter, R. F. (1984). Validity and utility of alternative predictors of job performance. Psychological Bulletin, 96, 7298. doi:10.1037/0033-2909.96.1.72.Google Scholar
Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings. (2nd ed.). Newbury Park, CA: Sage. Google Scholar
Hunter, J. E., Schmidt, F. L., & Hunter, R. (1979). Differential validity of employment tests by race: A comprehensive review and analysis. Psychological Bulletin, 86, 721735. doi:10.1037/0033-2909.86.4.721.Google Scholar
Hunter, J. E., Schmidt, F. L., & Le, H. (2006). Implications of direct and indirect range restriction for meta-analysis methods and findings. Journal of Applied Psychology, 91, 594612. doi:10.1037/ 0021-9010.91.3.594.Google Scholar
Hurtz, G. M., & Donovan, J. J. (2000). Personality and job performance: The Big Five revisited. Journal of Applied Psychology, 85, 869879. doi:10.1037/0021-9010.85.6.869.Google Scholar
Jeanneret, P. R. (2005). Professional and technical authorities and guidelines. In Landy, F. J. (Ed.), Employment discrimination litigation: Behavioral, quantitative, and legal perspectives (pp. 47100). San Francisco, CA: Wiley. Google Scholar
Jencks, C., & Phillips, M. (Eds.). (1998). The BlackWhite test score gap. Washington, DC: Brookings Institution Press. Google Scholar
Jensen, A. R. (1969). How much can we boost IQ and scholastic achievement? Harvard Educational Review, 39, 1123. Google Scholar
Kirkpatrick, J. J., Ewen, R. B., Barrett, R. S., & Katzell, R. A. (1968). Testing and fair employment. New York, NY: New York University Press. Google Scholar
Kleiman, L. S., & Faley, R. H. (1985). The implications of professional and legal guidelines for court decisions involving criterion-related validity: A review and analysis. Personnel Psychology, 38, 803833. doi:10.1111/j.1744-6570.1985.tb00568.x.Google Scholar
Kravitz, D. A. (2008). The diversity-validity dilemma: Beyond selection—the role of affirmative action. Personnel Psychology, 61, 173193. doi:10.1111/ j.1744-6570.2008.00110.x.Google Scholar
McDaniel, M. A. (2007). Validity generalization as a test validation approach. In McPhail, S. M. (Ed.), Alternative validation strategies: Developing new and leveraging existing validity evidence. (pp. 159180). Hoboken, NJ: Wiley. Google Scholar
McDaniel, M. A. (2009). Gerrymandering in personnel selection: A review of practice. Human Resource Management Review, 19, 263270. doi:10.1016/ j.hrmr.2009.03.004.Google Scholar
McDaniel, M. A. (2010, July). Abolish the uniform guidelines. Paper presented at the annual meeting of the International Personnel Assessment Council, Newport Beach, CA.Google Scholar
McKay, P. F., & McDaniel, M. A. (2006). A reexamination of Black–White mean differences in work performance: More data, more moderators. Journal of Applied Psychology, 91, 538554. doi:10.1037/ 0021-9010.91.3.538.Google Scholar
Meade, A. W., & Tonidandel, S. (2010). Not seeing clearly with Cleary: What test bias analyses do and do not tell us. Industrial and Organizational Psychology: Perspectives on Science and Practice, 3, 192205. doi:10.1111/j.1754-9434.2010. 01223.x.Google Scholar
Michaels, D., & Monforton, C. (2005). Manufacturing uncertainty: Contested science and the protection of the public's health and environment. American Journal of Public Health, 95, S39S45. doi:10.2105/AJPH.2004.043059.Google Scholar
Morris, S. B., & Lobsenz, R. E. (2000). Significance tests and confidence intervals for the adverse impact ratio. Personnel Psychology, 53, 89111. doi:10.1111/j.1744-6570.2000.tb00195.x.Google Scholar
National Center for Education Statistics. (2010). Digest of education statistics; Table 386. Literacy skills of adults, by type of literacy, proficiency levels, and selected characteristics: 1992 and 2003. Retrieved from http://nces.ed.gov/programs/digest/d09/tables/dt09_386.asp.Google Scholar
O’Boyle, E. H., & McDaniel, M. A. (2008). Criticisms of employment testing: A commentary. In Phelps, R. P. (Ed.), Correcting fallacies about educational and psychological testing. (pp. 181197). Washington, DC: American Psychological Association. Google Scholar
Pearlman, K., Schmidt, F. L., & Hunter, J. E. (1980). Validity generalization results for tests used to predict job proficiency and training success in clerical occupations. Journal of Applied Psychology, 65, 373406. doi:10.1037/0021-9010.65.4.373.Google Scholar
Phillips, M., Brooks-Gunn, J., Duncan, G. J., Klebanov, P., & Crane, J. (1998). Family background, parenting practices, and the Black–White test score gap. In Jencks, C. & Phillips, M. (Eds.), The Black–White test score gap. Washington, DC: Brookings Institution Press. Google Scholar
Ployhart, R. E., & Holtz, B. C. (2008). The diversity-validity dilemma: Strategies for reducing racioethnic and sex subgroup differences and adverse impact in selection. Personnel Psychology, 61, 153172. doi:10.1111/j.1744-6570.2008.00109.x.Google Scholar
Pyburn, K. M. Jr., Ployhart, R. E., & Kravitz, D. A. (2008). The diversity-validity dilemma: Overview and legal context. Personnel Psychology, 61, 143151. doi:10.1111/j.1744-6570.2008.00108.x.Google Scholar
Rosenstock, L., & Lee, L. (2002). Attacks on science: The risks to evidence-based policy. American Journal of Public Health, 92, 1418. doi:10.2105/ AJPH.92.1.14.Google Scholar
Roth, P. L., Bevier, C. A., Bobko, P., Switzer, F. S., & Tyler, P. (2001). Ethnic group differences in cognitive ability in employment and educational settings: A meta-analysis. Personnel Psychology, 54, 297330. doi:10.1111/j.1744-6570. 2001.tb00094.x.Google Scholar
Roth, P. L., Bobko, P., & Switzer, F. S. III. (2006). Modeling the behavior of the 4/5ths rule for determining adverse impact: Reasons for caution. Journal of Applied Psychology, 91, 507522. doi:10. 1037/0021-9010.91.3.507.Google Scholar
Sackett, P. R., Schmitt, N., Ellingson, J. E., & Kabin, M. B. (2001). High-stakes testing in employment, credentialing, and higher education: Prospects in a post-affirmative-action world. American Psychologist, 56, 302318. doi:10.1037/0003-066x.56.4.302.Google Scholar
Schenkel, R. (2010). The challenge of feeding scientific advice into policy-making. Science, 330, 17491751. doi:10.1126/science.1197503.Google Scholar
Schmidt, F. L. (1988). The problem of group differences in ability test scores in employment selection. Journal of Vocational Behavior, 33, 272292. doi:10.1016/0001-8791(88)90040-1.Google Scholar
Schmidt, F. L., Gast-Rosenberg, I., & Hunter, J. E. (1980). Validity generalization results for computer programmers. Journal of Applied Psychology, 65, 643661. doi:10.1037/0021-9010.65.6.643.Google Scholar
Schmidt, F. L., & Hunter, J. E. (1977). Development of a general solution to the problem of validity generalization. Journal of Applied Psychology, 62, 529540. doi:10.1037/0021-9010.62.5.529.Google Scholar
Schmidt, F. L., & Hunter, J. E. (1981). Employment testing: Old theories and new research findings. American Psychologist, 36, 11281137. doi:10.1037/ 0003-066x.36.10.1128.Google Scholar
Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262274. doi:10.1037/0033-2909.124. 2.262.Google Scholar
Schmidt, F. L., & Hunter, J. E. (2003). History, development, evolution, and impact of validity generalization and meta-analysis methods, 1975–2001. In Murphy, K. R. (Ed.), Validity generalization: A critical review (pp. 3165). Mahwah, NJ: Erlbaum. Google Scholar
Schmidt, F. L., Pearlman, K., & Hunter, J. E. (1980). The validity and fairness of employment and educational tests for Hispanic Americans: A review and analysis. Personnel Psychology, 33, 705724. doi:10.1111/j.1744-6570.1980.tb02364.x.Google Scholar
Schmitt, N., & Quinn, A. (2010). Reductions in measured subgroup mean differences: What is possible? In Outtz, J. L. (Ed.), Adverse impact: Implications for organizational staffing and high stakes selection (pp. 425451). New York, NY: Routledge. Google Scholar
Sharf, J. (2006). Letter to Cari M. Dominguez, Chair, Equal Employment Opportunity Commission (May 10, 2006). Alexandria, VA: Author. Google Scholar
Sharf, J. (2008, February). Enforcement agencies' response to validity generalization. Paper presented at the annual meeting of the Personnel Testing Council of Metropolitan Washington, Washington, DC.Google Scholar
Shoben, E. W. (1978). Differential pass-fail rates in employment testing: Statistical proof under Title VII. Harvard Law Review, 91, 793813. Google Scholar
Slavin, R. E. (2002). Evidence-based education policies: Transforming educational practice and research. Educational Researcher, 31, 1521. doi:10.3102/0013189X031007015.Google Scholar
Society for Industrial and Organizational Psychology (SIOP). (2003). Principles for the validation and use of personnel selection procedures (4th ed.). Bowling Green, OH: Author. Google Scholar
Society for Industrial and Organizational Psychology (SIOP). (n.d.). SIOP bylaws. Retrieved from http://www.siop.org/reportsandminutes/bylaws.pdf.Google Scholar
Steinbrook, R. (2004). Peer review and federal regulations. New England Journal of Medicine, 350, 103104. doi:10.1056/NEJMp038230.Google Scholar
Stillwell, R. (2010). Public school graduates and dropouts from the common core of data: School year 2007-08. NCES 2010-341. Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Google Scholar
U.S. Census Bureau. (2007). Latest SUSB annual data: U.S . & states, totals. Retrieved from http://www.census.gov/econ/susb/.Google Scholar
Walberg, H. J., & Tsai, S.-L. (1983). Matthew effects in education. Educational Research Quarterly, 20, 359373. doi:10.2307/1162605.Google Scholar
Wigdor, A. K., & Garner, W. R. (Eds.). (1982). Ability testing: Use, consequences, and controversies. Washington, DC: National Academy Press. Google Scholar