The Bell Curve Chapter 3 The Economic Pressure to Partition.

Why people with different levels of intelligence end up in different occupations is the subject of this chapter. It is commonly believed in liberal academic circles that it helps to have high test scores ( SAT, GRE, MCAT or LSAT) to get into professional or graduate schools, but once in a school, the intellect they measure, becomes unimportant. It is true that educational degrees are at times a ticket for jobs that could be done just as well by those without an educational degree. However, in professions like medicine, law, engineering and astrophysics one not only has to have above average intelligence to get into a school that teaches one of these disciplines but, once in, he has to have a relatively high IQ to assimilate the material they teach. Most people inherently know that one has to be pretty smart to become an electrical engineer or a doctor of medicine, but the relationship of cognitive ability to job performance in other occupations it is less well understood and often ignored entirely. As the authors of The Bell Curve point out, a smarter employee is, on average, the more proficient the employee. This tenet holds true for all professions. Lawyers with high IQs are more productive that those with lower intelligence; blue-color workers, such as carpenters, with high intelligence are more productive than carpenters with lower IQs; finally, and a relationship that is most often overlooked, an unskilled laborer with a relatively high IQ will outperform one with lower intelligence every day of the week and twice on Sunday. The message is clear, intelligence is important to job performance irrespective of the job under discussion. This holds just as true for busboys as it does to CEOs of large companies. Obviously, the consequences of hiring a dull busboy are not as great to the owner of a small restaurant as they potentially would be to the board members who hired a relatively dim-witted CEO to run their fortune 500 company. Nonetheless the intelligence factor is still there just waiting to rear its head and cause havoc to the naive and unsuspecting employer who ignores the importance IQ when he hires a new employee, irrespective of the job in question. That is the message of this chapter. A flood of new analyses on employee intelligence during the 1980s established several points with large economic and policy implications. Test scores are predictive of job performance because they measure g, Spearman's general intelligence factor, not because they identify aptitude for a specific job. In this respect, any broad test of intelligence predicts proficiency for most occupations and does so more accurately than tests designed to measure a particular skill set. After reading this chapter a prospective employer will understand that an IQ score is a better predictor of job productivity that a job interview, reference checks, or college transcripts. In short, an employer who is free to pick among applicants can realize huge economic gains simply by hiring applicants with the highest IQs. It's really as simple as that, or at least it was until 1971. In 1971 the Supreme Court of the United States mistakenly ruled that hiring based on the results of tests that measured general intelligence was unconstitutional. We will have more say about this absurd decision in a moment, but for now realize that preventing employees from hiring the brightest employees costs the U.S. economy an estimated $13 to $80 billion each and every year. Unfortunately, laws can make the economy less efficient, but laws cannot make intelligence unimportant. Cognitive ability itself- sheer intellectual horsepower, independent of education- has market value. Employers recruit at Stanford and Yale, not because graduates from these elite schools know more than graduates from less prestigious schools but for the same reason Willie Sutton robed banks. Places like Stanford, Harvard and Yale are where you find the coin of cognitive talent. The perceived wisdom in the halls of academia, however, is quite different! Referring to the SAT test, "Test scores have modest correlation with first year grades and no correlation at all with what you do with the rest of your life," wrote Derek Bok the president of Harvard in 1985. To understand the absurdity of this statement, and the statistical information presented in this book, one must know the significance correlation coefficients. As mentioned previously, correlation coefficients vary from -1 to +1. A correlation of 0 means no correlation exists, no correlation between height and weight for example. A positive correlation is one that falls between 0 and +1 with +1 indicating absolute validity. In a study of height and weight, for example, a +1 correlation would indicate that a person's weight was determined solely by his height. Correlations in the social sciences are seldom higher that +.5 or lower than -.5 because social events are usually affected by variables that are not being measured by the tests. Thus, a correlation of +.2 can be "big" for many of the topics studied by the social scientists. Looking at it from a different angle, moderate correlations mean many exceptions. The correlation between IQ and various measures of job performance are usually in the range .2 to .6 which indicates that there many exceptions to the statistical finding that intelligence and job performance are closely related; however, these exceptions do not invalidate the importance of statistically significant correlations. In any job or profession there is a restricted range of cognitive ability and the relationship between job performance and IQ scores is very weak in that setting. To understand this concept consider the importance of weight in National Football League tackles. The All-Pro tackle probably is not the heaviest player in the league. But, on the other hand, the lightest player in the league weighs at least 250 pounds. In this situation the subjects under consideration have already been pre-

selected on the basis of weight. Thus,If we were to rate the performance of every NFL tackle and then correlate those ratings with the player's weights the correlation would probably be near 0. However, this does not mean that a superbly talented athlete weighing 150 pounds could ever play tackle for the Forty Niners, not a chance. We would be right in concluding that performance and weight does not correlate much in athletes weighing upwards of 250 pounds who want to play tackle; however, it would be wrong to conclude that weight was not much of a factor in achieving excellence at tackle if the candidate pool we were considering were drawn from the general population where the average male weighed around 150 pound. Thus, president Bok of Harvard was undoubtedly correct when he asserted that, after the first year, there was no correlation between the SAT scores of his freshmen and job performance and success in later life. This is true because the students who get into Harvard already have IQs in the stratosphere. If the correlation had been made between the SAT scores of all college applicants and their success in later life the results would have been very different, now you know why. Tens of millions of people are hired for jobs each year. Employers make hiring decisions by trying to guess which applicant would be the best worker. Until 1971 many employers used tests of intelligence to help make those decisions. In that year the landmark Supreme Court decision in Griggs v. Duke Power Co. changed all that. The court held that any job requirement, including a minimal score on a mental test, must have a manifest relationship to the employment in question and it was up to the employer to prove that it did. This meant that employment tests must focus on skills specifically needed to perform the job in question. This seemed to make good common sense at the time. Unfortunately, common sense turned out to be dead wrong! The most comprehensive contemporary studies of tests used for hiring, promotion and licensing in civilian, military, private and government point to three refutable conclusions concerning worker performance. The most comprehensive of these studies were performed by the military who exempted themselves from the 1971 Supreme Court decision in Griggs v. Duke Power Co. All branches of the armed forces, to this day, continue to test every recruit to determine his IQ. Irrespective if the job is skilled or performed by a menial laborer the correlation between intelligence and job performance is about +.4. As one would expect, the correlation for skilled jobs, such as managers is higher, +.53, while the correlation for industrial workers is only +.37. The correlation between intelligence and job performance was even +.23 for the most menial "feeding/off bearing" jobs (putting something into or taking something out of a machine). Possibly the most meaningful test of all is the armed Forces Qualification Test (AFQT) which every military recruit takes. This test is highly loaded for g, the measurement of general intelligence. This data base has no equal in studies of job productivity. In this huge study of 472,539 military personal the average correlation between intelligence and job performance was a whopping +.62! An analysis of these studies showed that Charles Spearman's g accounted for nearly 60 percent of the variation in grades achieved by those who attended the 828 military schools. That's why dullards who join the military end up peeling potatoes. Does experience make up for less intelligence in time? A busboy with one months experience on the job will outperform a smarter busboy on his first day on the job. but all relevant studies show that the initial one mouth difference in experience will have ceased to matter in six months. In this respect, most studies have shown that differences in productivity due to intelligence diminish only slowly and partially with time. Thus, the cost of hiring less intelligent workers may remain as long as they stay on the job. How good are test scores compared to other predictors of job productivity such as job interviews, reference checks and college grades. As the table shows, a job interview is a relatively poor indicator of job performance. Predictor Validity In Predicting Job Performance Cognitive test score .53 Biographical data .37 Reference checks .26 Interview .14 College grades .11 Interest .10 Age -.01 The data presented in the table suggests that employees chosen on the basis of test scores will, on average, be more productive than those chosen on the basis of any other item of information. What is the dollar value cognitive ability? The short answer is a lot. A first rate secretary with an IQ in the 84th percentile is worth a 40 percent premium over an average secretary who, by definition, is in the 50th percentile. In other words. if an average secretary is worth $20,000 a year a secretary who scores one standard deviation above the mean on an IQ test is worth $28,000. Alternately, hiring a secretary for a $20,000 a year job who scores one standard deviation below the mean will cost the employer about $8,000 in lost output each and every year he continues her employment.. In higher paying jobs the costs of poor hiring practices are, of course, much more significant. An HMO who has the option of hiring one of two dentists, one of whom has an average IQ and who has an IQ one standard deviation above the mean, will make a $30,000 mistake if they select the less intelligent candidate. Statistics like this explains why the notorious 1971 Supreme Court decision outlawing IQ tests for prospective employees was so detrimental to the US economy. Finally, what about the cost of testing? We live in an era when a reliable intelligence test can be administered in twelve minutes; thus, the cost of testing can be lower, in the terms of labor, than it would be to conduct interviews or check references. The fact that it is now illegal to perform tests of intelligence test, of course, complicates the issue but it does not negate the fact that the way to get the best possible work force is to hire the smartest people you can find. Because the economic value of employees is linked to their intelligence, so are their wages which the subject matter of the next chapter. Comment: For those working in Human Resources this is, by far, the most important chapter in The Bell Curve. However, while it may seem obvious that CEOs of large companies need to be very intelligent, it may be less evident to a small business managers that they should strive to hire the smartest candidates available irrespective of how menial the job in question, even if they are hiring a busboy or someone to pull lumber from the green-chain in a saw mill. Since it is now illegal to use tests of IQ to screen job applicants, the job of a recruiter is more difficult now than it was 50 years ago before the Griggs v. Duke Power Co. decision. However, clever managers can get a pretty good idea of the relative intelligence of candidates for a given job, and it behooves them to do so. The fact that John knows why manhole covers are round but Billy doesn't tells you volumes about the relative intelligence of the two, doesn't it?