Color of Money as Compared to Color of Principals: An Assessment of Pay for Male Elementary School Principals Varying in Surname (Hispanic vs. Non-Hispanic)
Restricted accessResearch articleFirst published online December, 2008
Color of Money as Compared to Color of Principals: An Assessment of Pay for Male Elementary School Principals Varying in Surname (Hispanic vs. Non-Hispanic)
Background: Pay is an important human resource function that has attracted considerable interest within the professional literature and this study addresses pay discrimination.
Purpose(s): To address pay for a particular protected group unaddressed in existing literature (Hispanic-surnamed principals).
Setting: The setting for this study is public school districts located in the state of California.
Subjects: All-male public school elementary principals served as potential participants.
Interventions: Different models for pay discrimination are explored in this study.
Research Design:A randomized group design involving a single independent variable (surname of principals) is used in this study.
Data Collection:Within this study, data are obtained from an archival source and through self-reported measures.
Findings: A regression analysis indicates that pay discrimination is a multifaceted concept that must consider not only protected status of individuals along with traditional control variables (organizational and human capital endowments) but the interaction of these effects on pay outcomes when assessing pay discrimination.
Conclusions: By examining pay from a main effect as well as from an interaction effect, a new definition for pay discrimination is provided, and specific methodological advancements are suggested.
Achen, C.H. (1982). Interpreting and using regression. Newbury Park, CA: Sage.
2.
American Educational Research Association. ( 1999). Standards for educational and psychological testing. Washington, DC: American Educational Research Press .
3.
Arbuckle, J.L., & Wothke, W. (1999). Amos 4.0 user's guide. Chicago : SmallWaters Corporation.
4.
Barrett, G.V., Alexander, R.A., Anesgart, M.A., & Doverspike, D. (1986). Frequently encountered problems in the application of regression analysis to investigation of sex discrimination in salaries. Public Personnel Management, 15(2), 143-157.
5.
Berry, W.D., & Feldman, S. (1985). Multiple regression in practice. Newbury Park, CA: Sage.
6.
California State Department of Education. ( 2006). California public schools directory information. Sacramento, CA: California Department of Education Press.
7.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. New York: Academic Press .
8.
Currall, S.C., Towler, A.J., Judge, T.A., & Kohn, L. (2005). Pay satisfaction and organizational outcomes. Personnel Psychology, 58(3), 613-640.
9.
Darlington, R.D. (1990). Regression and linear models. New York: McGraw-Hill.
10.
Equal Employment Opportunity Commission. (n.d.). Equal pay and compensation discrimination. Retrieved September 3, 2007, from www.eeoc.gov/types/epa.html
11.
Equal Pay Act, 29 U.S.C. § 206(d) (1963).
12.
Gardner, J.W. (1968). No easy victories. New York : Harper and Row.
13.
Gerhart, B., & Milkovich, G.T. (1992). Employee Compensation: Research and practice. In M. D. Dunnette & L. Hough (Eds.), Handbook of industrial and organizational psychology (2nd ed., pp. 481-570). Palo Alto, CA: Consulting Psychologist Press.
14.
Hardy, K. (1993). Regression with dummy variables. Newbury Park, CA: Sage.
15.
Heneman, H.G. (1985). Pay satisfaction. Research in Personnel and Human Resources Management, 3, 115-139.
Hollenbeck, J.R., Ilgen, D.R., Ostroff, C., & Vancoouver, J.B. (1987). Sex differences in occupational choice, pay, and worth: A supply-side approach to understanding the malefemale wage gap. Personnel Psychology, 40(4), 715-743.
18.
House Hennessy-Fiske, M. (2006, December 3). Gender earnings gap narrows. Los Angeles Times. Retrieved December 5, 2006, from http://www.latimes.com/news/printedition/asection/la-na-wagegap3dec03,1,4524631.story?ctrack=1&cset=true
19.
Huffman, M.L. (2004). Gender inequality across local wage hierarchies . Work and Occupations, 31(3), 323-344.
20.
Jaccard, J., & Turrisi, R. (2003). Interaction effects in multiple regression. Newbury Park, CA: Sage.
21.
Kmec, J.A. (2005). Setting occupational sex segregation in motion . Work and Occupations, 32(3), 322-354.
22.
National Education Association. (2006). Educational statistics: Rankings and estimates 2006. Retrieved September 5, 2007, from http://www.nea.org/edstats/index.html
23.
Owings, W.A., & Kaplan, L.S. (2006). American public school finance. Belmont, CA: Thomson Wadsworth Corporation.
24.
Parade. (2007). What people earn. Fresno Bee.
25.
Pedhazur, E.J. (1982). Multiple regression in behavioral research: Explanation and prediction (2nd ed.). New York: Holt, Rinehart & Winston.
26.
Pounder, D.G. (1988). The male/female salary differential for school administrations: Implications for career placement of females. Educational Administration Quarterly, 24(1), 5-19.
27.
Pounder, D.G. (1989). The gender gap for salaries of educational administration professors. Educational Administration Quarterly, 25(21), 181-201.
28.
Rice, R.W., Phillips, S.M., & McFarlen, D.B. (1990). Multiple discrepancies and pay satisfaction. Journal of Applied Psychology, 75(4), 368-393.
29.
Schwab, D.P., Rynes, S.L., & Aldaq, R.J. (1987). Theories of research on job search and choice . Personnel and Human Resource Management, 5, 129-166.
30.
Stone, J.A. (1985). Determinants of administrators' salaries in public schools: Differences for men and women. Economics of Education Review, 4(2), 105-109.
31.
Terpstra, D.E., & Honoree, A.L. (2003). The relative importance of external, internal, individual and procedural equity to pay satisfaction. Compensation Benefits Review, 35, 67-74.
32.
Title VII of the Civil Rights Act of1964. 42 U.S.C. § 1981-2000h-6 (Lexis-Nexis2006).
33.
Wang, G.G., & Holton, E.F. (2005). Neoclassical and institutional economics as foundation for human resource development theory. Human Resource Development Review, 4(1), 86-108.
34.
Webb, L.D., & Norton, M.S. (2003). Human resources administration, personnel issues and needs in education. Upper Saddle, NJ: Merrill Prentice Hall.
35.
Williams, A.R. (2005). Principals' salaries, 2004-05. Principal - Training Tomorrow's Principals - Research Supplement, 84(5), 45-50. Retrieved September 5, 2007, from http://www.naesp.org/ContentLoad.do?contentId=1605
36.
Young, I.P. (2007). Salaries for new superintendents: A public relations concern for many school boards. Journal of School Public Relations , 28(2), 124-136.
37.
Young, I.P. (2008). The human resource function in educational administration (9th ed.) Upper Saddle, NJ: Prentice Hall.
38.
Young, I.P. (1999). Salary discrimination: A test of the paradoxical female hypothesis. Educational Administration Quarterly, 35(3), 379-397.
39.
Young, I.P., & Brown, J. (1996). Compensation bias in educational administration: Female and male equity. Educational Administration Quarterly , 32(1), 142-149.
40.
Young, I.P., Delli, D.A., Miller-Smith, K.A., & Alhadeff, A.B. (2004). An evaluation of the relative efficiency for various relevant labor markets: An empirical approach for establishing teacher salaries. Educational Administration Quarterly, 40(3), 66-387.
