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“Wikipedia: Race Norming Race-norming, more formally called within-group score conversion and score adjustment strategy, is the practice of adjusting test scores to account for the race or ethnicity of the test-taker. In the United States, it was first implemented by the Federal Government in 1981 with little publicity, and was subsequently outlawed by the Civil Rights Act of 1991. Prior to being banned by the federal government, race-norming was practiced by 38 U.S. states' employment services. The aim of this practice is to counteract alleged racial bias in aptitude tests administered to job applicants, as well as in neuropsychological tests. The practice converted and compared the raw score of the test according to racial groups. The score of a black candidate is only compared to the scores of those who had the same ethnicity. If the candidate's score, which is reported within a percentile range, fell within a certain percentile when compared to white or all candidates, it would be much higher among other black candidates.”

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“Gottfredson, Linda S. (1994). "The science and politics of race-norming". American Psychologist. 49 (11): 955–963 Disparate impact (racial imbalance) in employee selection constitutes prima facie evidence of unlawful discrimination. Research in personnel psychology has shown, however, that valid and unbiased selection procedures often guarantee disparate impact and that they will continue to do so as long as there remain large racial disparities in job-related skills and abilities. Employers are in a legal bind because often they can avoid disparate impact only by engaging in unlawful disparate treatment (racial preferences).”

“Race norming is the practice of converting individual test scores to percentile or standard scores within one’s racial group. In the process of race norming, an individual’s percentile score is not calculated in reference to all persons who took the test; instead, an individual’s percentile score is determined only in reference to others in the same racial group. After norming scores by percentile in separate racial groups, the lists are combined to make selection decisions. By norming within racial groups, the same raw score for Whites and Blacks can be converted to different percentile scores based on the distribution of scores for each racial group. For example, suppose that a White candidate and a Black candidate each earn a raw score of 74 points on a test. If the White candidate’s test score is converted to a percentile only in reference to other White candidates and the Black candidate’s test score is converted to a percentile only in reference to other Black candidates, then the percentile scores earned by the two candidates may not be equal even though they attained the same raw test score. Perhaps the 74-point raw score for the White candidate may be at the 60th percentile of the White distribution of scores, whereas the 74-point score for the Black candidate may be at the 65th percentile of the Black distribution of scores. When the White and Black percentile scores are combined into a common list and selection decisions are made, the candidates who scored the same 74 raw points on the test might be treated very differently. For example, if the organization decides to hire only persons who scored at the 65th percentile and above, then the Black candidate would be selected and the White candidate would not. In another circumstance, the organization could decide to hire persons with the highest percentile first, which would mean that the Black candidate would be selected prior to the White candidate.”

“Santa Barbara Independent June 30, 2021 Letters: Disparate Disparities Rick Roney … 75 percent of the basketball players in the NBA are black. Thirteen percent of the population is black. Does this imply the NBA is systemically discriminating against white people? Or are blacks, on average, better high-level basketball players? Two-thirds of speeding tickets are given to males. Men are slightly less than 50 percent of our population. Does this imply police are systemically prejudiced against men? Or do men drive faster and/or log more miles driving than women. Ninety percent of the inmates in prison are male. Does this imply the criminal justice system is systemically prejudiced against men? Or do men commit more crimes? You get the point. Disparate impact analysis is a bogus analytical methodology.”

“Christianity embodied all the moral instincts of our race, such as our concepts of personal honor, of personal self-respect and integrity, of fair play, of pity for the unfortunate, of loyalty- all of which seem preposterous to other races, at least in the form and application that we give to them. They simply lack our instincts. We think that it makes a great difference whether we kill a man in a fair fight or by treacherously stabbing him in the back or by putting poison in the cup that he accepts from our friendly hand; to at least one other race, we are simply childish and irrational: if you are to kill a man, kill him in the safest and most convenient way. Again, we, whether Christians or atheists, have an instinct for truth, so that if we lie, we have physical reactions that can be detected by a sphygmomanometer (often called a polygraph or "lie detector"). When officers of American military intelligence tried to use that device in the interrogation of prisoners during the Korean War, they discovered that Koreans and Chinese have no reaction that the instrument can detect, no matter how outrageous the lies they tell. We and they are differently constituted. We can no longer be so obtuse as to ignore the vast differences in mentality and instinct that separate us from all other races - not merely from savages, but from highly civilized races. The differences are innate, and to attempt to change their way of thinking with argument, generosity, or holy water is as absurd as attempting to change the color of their skins. That is a fact that we must accept. However, one may relate that fact to Christian doctrine, if we, a small minority among the teeming and terribly fecund populations of the globe, call all other peoples perverse or wicked, we merely confuse ourselves. If we are to think objectively and rationally, we must do so in the terms used by Maurice Samuel, who, after his discerning and admirably candid study of the "unbridgeable gulf' that separates Indo-Europeans from Jews, had to conclude that "This difference in behavior and reaction springs from something more earnest and significant than a difference of beliefs: it springs from a difference in our biologic equipment.”

“Non-Latino Latino White 60.0% 12.1% Black 12.4% 0.4% East Asian 2.4% 0.0% South Asian 1.5% 0.0% Filipino/Pacific Islander 1.1% 0.0% Native American 0.7% 0.2% Southeast Asian 0.6% 0.0% Other Asian 0.1% 0.1% Other Single Race 0.3% 4.7% White & Black 0.7% 0.1% White & Native American 0.5% 0.1% White & Asian 0.5% 0.1% Other Combination 0.8% 0.6% TOTAL 81.6% 18.4%”

“Page 42: Whatever the combination of sources of test bias might be, genuine bias against a minority will show up in a way that leaves no room for doubt: It will under-predict the test taker’s performance in the classroom or on the job. Whether predictive validity is the same for different groups can be subjected to rigorous statistical scrutiny, and it has been, repeatedly. The results are unambiguous, whether the thing being predicted is grades in school or performance on the job. The major tests do not under-predict the performance of Africans or Latins.”

“Page 67: For jobs that require a college degree, race differences in cognitive ability in the workplace should be minimized by the process of obtaining that college degree. But it hasn’t worked that way since at least the 1970s. Colleges have been complicit in transmitting the mean IQ differences by race in the general population not only through the college pipeline but through the graduate-education pipeline as well.”