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Race-norming is a testing process whereby scores are adjusted in such a way they reflect the ethnicity of the targeted individual. Although the score adjustment strategy (race-norming) was designed to minimize racial bias in different aptitude tests, it has failed to fulfill the promises of an equal society. That being the case, it becomes evident that the process lowers the standards for traditionally misrepresented groups in society (Ma, Correll, & Wittenbrink, 2015). The use or consideration of race in test scores is capable of increasing the level of discrimination. The first reason is that the strategy inhibits the development of new solutions to the major problems affecting disadvantaged racial groups and other members of society.
James (2017) acknowledges that the inappropriateness of race-norming led to its abolishment in the year 1991 after the passage of the Civil Rights Act. It is also evident that the method could not be used to predict employees’ job performance. This fact explains why the strategy was one of the efforts applied in the country to suppress the standards and welfare of minority races such as African Americans, Latinos, and Native Americans. Ma et al. (2015) go further to indicate that the continued use of a person’s race as a determinant of job performance and effectiveness amounts to discrimination. Ethnic preferences, therefore, can only be lawful if they are redesigned in such a way that they reduce the level of prejudice and widen the opportunities for every member of the community. According to Ma et al. (2015), race-norming has also been observed to leapfrog individuals from specific groups while ignoring the welfare of those from other ethnic backgrounds.
Reverse Discrimination and Affirmative Action
Reverse discrimination and affirmative action are two concepts that have been used interchangeably by scholars despite the fact that they have diverse meanings. Affirmative action is any given policy aimed at empowering or favoring individuals from racial groups that have been disadvantaged or misrepresented for many years. Such policies are usually implemented to bridge the existing disparities in education, job opportunities, and economic gains. On the other hand, reverse discrimination is the use of suitable approaches to empower members of minority groups while sidelining those from dominant cultures (Coston & Kimmel, 2013). This form of discrimination is pursued in such a way that it presents opportunities to individuals who have been affected by existing social inequalities. The approach can entail the use of preferential policies to increase educational attainment and economic opportunities for minority cultural groups.
This analysis shows that affirmative action is a strategy that focuses mainly on disadvantaged groups such as specific races or women. The approach seeks to bridge inequality, address past cases of discrimination, and promote diversity. Reverse discrimination targets dominant races by making sure that they are not considered for a specific college or job opportunities. The main objective is to support minority groups to achieve their goals. Additionally, reverse discrimination is implemented to address the disparities associated with affirmative action. Despite such differences, these two concepts are implemented with the aim of empowering underrepresented groups or ethnicities. The methods focus on new policies and practices that can promote equality for all. Reverse discrimination appears to strengthen affirmative action by tackling existing gaps and supporting specific groups (Coston & Kimmel, 2013). The two concepts work synergistically to tackle various hurdles that have been encountered by minority groups in a given society.
Discriminated Categories of Persons
Specific categories of persons have become the primary objects of discrimination in different parts of the world. The first category is that of minority ethnic groups. Some good examples include African American and Latino cultures (James, 2017). The courts protect members of these ethnic groups using the Civil Rights Act of 1964. The second category is founded on gender. For example, women usually face endless discriminatory practices in society and their places of work such as harassment (James, 2017). These individuals are protected in accordance with the Civil Rights Act, the Equal Pay Act, and other anti-discrimination laws. Age is the third determinant of discrimination whereby the elderly are affected significantly. Many senior citizens lack opportunities, adequate medical care, and competitive salaries. The elderly are protected in accordance with different laws such as the Age Discrimination in Employment Act of 1967.
Disabled members of the society are usually targeted by perpetrators of discrimination. For example, disabled persons might be unable to get jobs or competitive salaries (James, 2017). Some might receive ineffective health or transportation services. The Americans with Disabilities Act of 1990 has been in place to safeguard the rights of these people. Members of specific religions or national backgrounds have also faced discrimination in different regions. For example, this category can be used to understand why the Nazis committed numerous atrocities against the Jews during the Second World War. This threat explains why individuals from different backgrounds and religious affiliations are protected by American courts using policies such as the Civil Rights Act. The courts should, therefore, continue to safeguard and protect the rights of these five categories of persons in order to achieve their potential.
References
Coston, B. M., & Kimmel, M. (2013). White as the new victims: Reverse discrimination cases and the men’s rights movement. Nevada Law Journal, 13(2), 368-385.
Fulero, S. M., & Wrightsman, L. S. (2009). Forensic psychology. Belmont, CA: Wadsworth Cengage Learning.
James, S. A. (2017). The strangest of all encounters: Racial and ethnic discrimination in US health care. Cadernos de Saude Publica, 33(1), 1-10. Web.
Ma, D. S., Correll, J., & Wittenbrink, B. (2015). The Chicago face database: A free stimulus set of faces and norming data. Behavioral Research Methods, 47(4), 1122-1135. Web.
Salman, M., Abdullah, F., & Saleem, A. (2016). Sexual harassment at workplace and its impact on employee turnover intentions. Business & Economic Review, 8(1), 87-102.
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