Does college entry depend on intelligence or ballot rigging?

Entrance to tertiary education is presumed to be based on the capacity to think. If the brightest get the opportunity to study longer, some good may result for society. If the less bright take up scarce places, less good will result.

April Bleske-Rechek and Kingsley Browne have looked into this in: Trends in GRE scores and graduate enrollments by gender and ethnicity

http://dx.doi.org.libproxy.ucl.ac.uk/10.1016/j.intell.2014.05.005

Does college entry depend on the capacity to think? The Graduate Record Examination (GRE) is a cognitive abilities test that predicts success in graduate training (Kuncel and Hezlett, 2007, Kuncel et al., 2001 and Kuncel et al., 2010). Because of its reliability, validity, and predictive utility, it is used by many graduate schools to inform admissions decisions. However, some critics describe the GRE as a gatekeeper that limits equitable access across groups to higher education (Dutka, 1999, Pruitt, 1998 and Toyama, 1999).We explored how scores on the GRE have fared over time as a function of test-taker gender and ethnicity, and we investigated whether enrolment patterns over time implicate the GRE as obstructing efforts toward increasing parity in higher education. First, we found that the gap between men's and women's GRE quantitative reasoning scores has changed little since the 1980s, although female representation in science, technology, engineering, and math (STEM) graduate programs has increased substantially. Second, ethnic gaps on the GRE persist, especially in quantitative reasoning, although representation of historically disadvantaged ethnic groups in graduate programs has increased. Enrolment gaps have narrowed despite ethnic and gender GRE gaps persisting, so it appears that continued use of the GRE for admissions decisions has not blocked efforts toward equalizing representation in higher education.

In a nutshell, the authors find that although sex and race differences in intelligence have not changed, and intelligence is the best predictor of college success, admission to university has increased for racial minorities. So, something other than intelligence is determining entry for these racial groups. With some understatement the authors observe: Such a finding would raise a subsidiary issue, however, which is whether and to what extent efforts to achieve diversity by de-emphasizing GRE scores have impaired the first goal of selecting those applicants who are most likely to benefit from advanced training.

The GRE functions as an intelligence test, and not a test of interests, preferences or motivation. It correlates with the Scholastic Aptitude Test and with other intelligence tests. It has been in use since the 1950s and has a good track record of predicting educational outcomes.

In 1982,men outscored women by 79 points, and in 2007 by 78 points, so no change over a generation.

First, here is a graph of their findings for men and women:

 

 

Men are ahead on verbal intelligence, and even more ahead on quantitative intelligence.

Despite this, more and more women have entered courses which require quantitative skills, though the effect is less pronounced for mathematics and computing. This suggests that entry criteria have been lowered for women entrants or equivalently, wider participation of women generally has resulted in more women entering courses with lower ability scores.

Next, here are the scores by race:

They show the familiar pattern, though with no Asian advantage on Verbal intelligence, but confirming the usual hierarchy in quantitative skills. The latter are very substantially different. Asians consistently earned higher GRE-Quantitative scores than did test-takers from any other ethnic group. In 1982, Asian test-takers scored 49 points higher on average than did White test-takers, who scored
171 points higher than Black test-takers; 25 years later, Asian test-takers scored 55 points higher than White test-takers, who scored 143 points higher than Black test-takers. In other words, the Asian-Black gap in quantitative reasoning was 220 points and 25 years later was 198, a narrowing, but still a very substantial difference.

Women are given modest preferences, minorities substantial preferences. Bluntly, some candidates either play the genetic card or the colleges play it for them. Ballot rigging at the entry stage can then lead unjustified complaints at the exit stage: weak entrants can claim that later weak performance at work or in academia is due to unfair assessments later in life.

One might expect that if the GRE is a valid predictor of graduate school success, and if universities accept applicants with lower GRE scores for demographic reasons, then those students may not have the same success as students with stronger records even if they are admitted in equal proportions. This is especially a concern in STEM disciplines, because gender and ethnic gaps in quantitative ability increase in magnitude farther along the right tail (Hedges & Nowell, 1999; Lakin, 2013; Wai et al., 2010), and exceptional levels of achievement in STEM are closely linked to exceptional levels of quantitative reasoning ability (Park, Lubinski, & Benbow, 2008). If women in STEM careers are highly able but still discrepant, on average, from their male counterparts, one would expect average gender differences in rates of tenure, publication, citation counts, and funding (Ceci & Williams, 2011). The same logic applies to ethnic differences, although perhaps to a larger degree given the magnitude of the test-score discrepancies. If not understood, these discrepancies
could lead to unwarranted perceptions of discrimination. As noted by Ceci and Williams (2011), gender differences in rates of tenure, publication, citation counts, and grant funding in STEM disciplines are tied to women's abilities and preferences; and interventions that focus on discrimination as the primary cause are unlikely to be successful.

Ability distribution differences are also key for understanding concerns about attrition of minorities from the academic pipeline (Griffith, 2010). The foundation for this concern is buttressed by Garrison's (2013) finding that racial disparities in STEM fields, including in graduate education, are more a product of differences in graduation rate than matriculation rate. Suggesting that attrition rates are influenced by qualifications, Baker (1998) found that substantial race differences in Ph.D. completion rates disappear once measures of “ability” (GRE scores, GPA, and NSF Graduate Fellowship panel evaluations) are controlled for. Degree completion is not the only outcome measure that varies by ethnic group. Price and Price (2006) found, for example, that minority graduate students in humanities and social sciences are less likely than non-minorities to publish as graduate students or within three years of finishing graduate school.

Although over 25 years white scores have gone up from 535 to 562, white entry to college has fallen from 84% to 75% and apart from losing some spaces to brighter Asians it is mostly to make way for students with lower scores.

These are sobering findings. If you tell lies to all students about their abilities at entry then you are open to accusations of bias when disappointment sets in later. You cannot defend the apparent later disparity in outcomes because you have suppressed the original differences in ability.

There is one thing the authors could have done, which is to show what the sexual and racial composition of tertiary education would have been like if it had been based on merit. For sex differences, if we set the entry point at the 2007 male mean of 599 points on the quantitative measure, then that accepts 50% of the men but only 29% of the women.

The quick calculation for racial differences for 2007, the most recent year for which we have data, is as follows.  I have taken white students as the reference group, because they are the largest group by far, and for simplicity have assumed that those who are even 1 point below the white mean on the quantitative measure should not be admitted to university, on the grounds that they will probably not do well. By definition, this will lead to only 50% of white applicants being allowed to enter university. 66% of Asians will get in, 32% of American Indians, 28% of Mexicans, 25% of Puerto Ricans, and 14% of Black Americans.

So, are entrants to university in the USA being selected by ability or by representativeness in genetic terms? The latter, it would seem.