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Discrimination Charge Statistics by State – Relatively Speaking

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Murray Simpson, Ph.D
on July 13, 2012

After reporting a record number of discrimination charges received nationally in 2011 (99,947 charges) in January 2012, the Equal Employment Opportunity Council (EEOC) website now provides information on total charges from 2009-2011 by state as well as charges by type of discrimination, including sex, race, national origin, color, religion, retaliation, equal pay, age, disability and genetic information. Statistics on charges of genetic discrimination debuted in 2010, corresponding to the passage of the Genetic Information Non-Discrimination act (GINA).

At first glance, the top three states in terms of total discrimination charges have remained unchanged since 2009. Texas leads all states, followed by Florida and then California. Illinois and Georgia round out the top five, taking turns at the fourth and fifth rankings over the three-year period. Given the relatively large employed populations in these states, it is not surprising that they rank at the top of the list with regard to total charges.

Conversely, the bottom five states – when ranked according to total charges – vary slightly from year to year. Those eight states also have relatively small employed populations: Montana, Maine, Vermont, North Dakota, New Hampshire, Wyoming, Rhode Island and South Dakota. 

When looking at total charges as a percentage of each state’s employed population, the top rankings change considerably. In 2011, Texas, Florida, and California dropped in ranking. In their place, Alabama, Mississippi and New Mexico moved up. There is a lack of variance within the bottom rankings, and the race-related charges followed similar changes when reviewed as a percentage of minority population within the states.   

Anyone interpreting these statistics must understand that there is more to the story than meets the eye. You can’t deny that the states with the largest populations (such as Texas, Florida and California) tend to have the largest absolute number of discrimination charges filed with the EEOC, both in total and with regard to race.  On the other hand, when such charges are expressed as a percentage of each state’s employed or minority population, Southern states (such as Alabama, Arkansas, Mississippi and Tennessee) tend to rise to the top of the rankings, with New Mexico and Indiana being notable exceptions. Georgia is the lone state that appears among the top five in both total charges and total charges as a percentage of the employed population.

This is valuable information and should be a wake-up call to all employers. Presenting the numbers of filed discrimination charges is one thing. The key for executives, managers or recruiters today is to dive into their own HR practices to determine how to reduce the chances of contributing to such statistics. Many of today’s leaders are dissecting their own employment metrics to identify and eliminate potential problems.

 For instance, managers with the ability to compare the race and gender composition of their hires to that of the applicants from which the hires were selected can readily determine if any adverse impact exists.  Further analysis that isolates the steps in the hiring process where the adverse impact is arising can help decision makers take proactive measures to prevent discrimination.  Moreover, analysis of the hiring process may prompt assessments of other areas such as performance evaluations, compensation planning or terminations that could pose a high risk for discrimination claims.

Once management has isolated and corrected any disparities by race or gender in the company’s HR practices, the process to drive and support a culture of inclusivity becomes easier.

Visit to read the full article with more details of the trends found and links to charts.

Author: Murray Simpson, Ph.D., Manager, Consulting Services, Peoplefluent Research Institute 
Contributors:Lisa Harpe, Ph.D., Principal Consultant, Peoplefluent Research Institute David Biggs, Senior Applications Programmer, Peoplefluent Research Institute

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