The Bell Curve: Intelligence and Class Structure in American Life (16 page)

Let us try to put these data in the framework of everyday experience. Why should it be that variation in general cognitive ability,
g,
is more important than job-specific skills and knowledge? We will use the job of busboy as a specific example, asking the question: At a run-of-the-mill family restaurant, what distinguishes a really good busboy from an average one?

Being a busboy is a straightforward job. The waiter takes the orders, deals with the kitchen, and serves the food while the busboy totes the dirty dishes out to the kitchen, keeps the water glasses filled, and helps the waiter serve or clear as required. In such a job, a high IQ is not required. One may be a good busboy simply with diligence and good spirits. But complications arise. A busboy usually works with more than one waiter. The restaurant gets crowded. A dozen things are happening at once. The busboy is suddenly faced with queuing problems, with setting priorities. A really good busboy gets the key station cleared in the nick of time, remembering that a table of new orders near that particular station is going to be coming out of the kitchen; when he goes to the kitchen, he gets a fresh water pitcher
and
a fresh condiment tray to save an extra trip. He knows which waiters appreciate extra help and when they need it. The point is one that should draw broad agreement from readers who have held menial jobs: Given the other necessary qualities of diligence and good spirits, intelligence helps. The really good busboy is engaged in using
g
when he is solving the problems of his job, and the more
g
he has, the more quickly he comes up with the solutions and can call on them when appropriate.

Now imagine devising a test that would enable an employer to choose the best busboy among applicants. One important aspect of the test would measure diligence and good spirits. Perhaps the employer should weigh the results of this part of the test more heavily than anything else, if his choice is between a diligent and cheerful applicant and a slightly smarter but sulky one. But when it comes to measuring performance in general for most applicants, it is easy to see why the results will match the findings of the literature we just discussed. Job-specific items reveal mostly whether an applicant has ever been a busboy before. But that makes very little difference to job productivity, because a bright person can pick up the basic routine in the course of a few shifts. The
g-
loaded items, on the other hand, will
reveal whether the applicant will ever become the kind of busboy who will clear table 12 before he clears table 20 because he relates the needed task to something that happened twenty minutes earlier regarding table 15. And that is why employers who want to select productive busboys should give applicants a test of general intelligence rather than a test of busboy skills. The kind of test that would pass muster with the courts—a test of job-specific skills—is a less effective kind of test to administer. What applies to busboys applies ever more powerfully as the jobs become more complex.

The busboy example leads to another question that bears on how we should think about cognitive ability and job productivity: How much can experience counterbalance ability? Yes, the smart busboy will be more productive than the less-smart busboy a week into the job, and, yes, perhaps there will always be a few things that the smart busboy can do that the less smart cannot. But will the initial gap in productivity narrow as the less-smart busboy gains experience? How much, and how quickly?

Separately, job performance relates to both experience and intelligence, but the relationships differ.
³¹
That is, people who are new to a job learn quickly at first, then more slowly. A busboy who has, say, one month on the job may for that reason outperform someone who started today, but the one-month difference in experience will have ceased to matter in six months. No comparable leveling-off effect has been observed for increasing intelligence. Wherever on the scale of intelligence pairs of applicants are, the smarter ones not only will outperform the others, on the average, but the benefit of having a score that is higher by a given amount is approximately the same throughout the range. Or, to put it more conservatively, no one has produced good evidence of diminishing returns to intelligence.
³²

But what happens when both factors are considered jointly? Do employees of differing intelligence converge after some time on the job? If the answer were yes, then it could be argued that hiring less intelligent people imposes only a limited and passing cost. But the answer seems to be closer to no than to yes, although much remains to be learned.

Some convergence has been found when SATs are used as the measure
of ability and grade point average is used as the measure of achievement.
³³
Students with differing SATs sometimes differ more in their freshman grades than in later years. That is why President Bok granted predictive value to the SAT only for first-year grades.
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On the other hand, the shrinking predictive power may be because students learn which courses they are likely to do well in: They drop out of physics or third-year calculus, for example, and switch to easier courses. They find out which professors are stingy with A’s and B’s. At the U.S. Military Academy, where students have very little choice in courses, there is no convergence in grades.
³⁵

When it comes to job performance, the balance of the evidence is that convergence either does not occur or that the degree of convergence is small. This was the finding of a study of over 23,000 civilian employees at three levels of mental ability (high, medium, and low), using supervisor ratings as the measure of performance, and it extended out to job tenures of twenty years and more.
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A study of four military specialties (armor repairman, armor crewman, supply specialist, cook) extending out to five years of experience and using three different measures of job performance (supervisor’s ratings, work sample, and job knowledge) found no reliable evidence of convergence.
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Still another military study, which examined several hundred marines working as radio repairmen, automotive mechanics, and riflemen, found no convergence among personnel of differing intelligence when job knowledge was the measure of performance but did find almost complete convergence after a year or so when a work sample was the measure.
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Other studies convey a similarly mixed picture.
³⁹
Some experts are at this point concluding that convergence is uncommon in the ordinary range of jobs.
⁴⁰
It may be said conservatively that for most jobs, based on most measures of productivity, the difference in productivity associated with differences in intelligence diminishes only slowly and partially. Often it does not diminish at all. The cost of hiring less intelligent workers may last as long as they stay on the job.

How good a predictor of job productivity is a cognitive test score compared to a job interview? Reference checks? College transcript? The answer,
probably surprising to many, is that the test score is a better predictor of job performance than any other single measure. This is the conclusion to be drawn from a meta-analysis on the different predictors of job performance, as shown in the table below.

The data used for this analysis were top heavy with higher-complexity jobs, yielding a higher-than-usual validity of .53 for test scores. However, even if we were to substitute the more conservative validity estimate of .4, the test score would remain the best predictor, though with close competition from biographical data.
⁴¹
The method that many people intuitively expect to be the most accurate, the job interview, has a poor record as a predictor of job performance, with a validity of only .14.

Readers who are absolutely sure nonetheless that they should trust their own assessment of people rather than a test score should pause to consider what this conclusion means. It is not that you would select a markedly different set of people through interviews than test scores would lead you to select. Many of the decisions would be the same. The results in the table say, in effect, that among those choices that would be different, the employees chosen on the basis of test scores will on average be more productive than the employees chosen on the basis of any other single item of information.

We arrive finally at the question of what it all means. How important is the overall correlation of .4, which we are using as our benchmark for the relation between intelligence and job performance? The temptation may be to say, not very. As we showed before, there will be many exceptions to the predicted productivity with correlations this modest. And indeed it is not very important when an employer needs just a few new employees for low-complexity jobs and is choosing among a small group of job applicants who have small differences in test scores. But the more reality departs from this scenario, the more important cognitive ability becomes.

How much is the variation in job performance worth? To answer that question, we need a measure in dollars of how much the workers in a given occupation vary. (Some of the methods for making this measurement are recounted in the notes, to which we refer readers who would like more detail.)
⁴²
To cut a long story short, think now of a particular worker—a secretary, let us say. You have a choice between hiring an average secretary, who by definition is at the 50th percentile, or a first-rate one—at the 84th percentile, let us say. If you were free to set their salaries at the figures you believe to reflect their true worth, how different would they be? We imagine that anyone who has worked with average secretaries and first-rate ones will answer “a lot.” The consensus among experts has been that, measured in dollars, “a lot” works out, on the average, to about a 40 percent premium.

Put more technically and precisely, one standard deviation of the distribution of workers’ annual productivities in a typical occupation is worth 40 percent of the average worker’s annual income.
⁴³
New work suggests the premium may actually be twice as large. Since the larger estimate has yet to be confirmed, we will base our calculations on the more conservative estimate.
⁴⁴
To take a specific example, for a $20,000-a-year job, which is correctly priced for an average worker, the incremental value of hiring a new worker who is one standard deviation above the mean—at the 84th percentile—is $8,000 per year.
⁴⁵
Hiring a worker for a $20,000-a-year job who is one standard deviation
below
the mean—at the 16th percentile—would cost the employer $8,000 in lost output.

The standard deviation for output is usually larger for more complex jobs.
⁴⁶
This makes intuitive sense: an assembly-line worker can do his job well or poorly, but ordinarily the gap that separates the proficiency of the 16th and 84th percentiles of assembly-line workers is not as great measured in the dollar value of the output as the gap that separates the proficiency of the 16th and 84th percentiles of engineers. But when we match this fact against an additional fact—that engineers make a lot more money than assembly-line workers—we are faced with what is known in statistics as an interaction effect. Getting high quality for a complex job can be worth large multiples of what it is worth to get equally high quality for a simpler job.

We may make this concrete with some hypothetical calculations. Imagine a dental office, consisting of dentist and receptionist. Assume that the annual salary of an average dentist is $100,000 and that of the receptionist $25,000, and that these are correctly priced. For whatever reasons, society finds the dentist to be worth four times as much as the receptionist.
⁴⁷
Suppose further that you are an employer—a Health Maintenance Organization (HMO), for example—who hires both dentists and receptionists. By using a certain selection procedure, you can improve the quality of your new hirees, so that instead of hiring people who are, on average, at the 50th percentile of proficiency (which is what would happen if you picked randomly from the entire pool of receptionists and dentists looking for jobs), you instead could hire people who are, on average, at the 84th percentile. What is this screening procedure worth to you?

For the value of the output produced, we use a standard deviation of .5 of the annual income for dentists and of .15 for that of receptionists, based on values actually observed.
⁴⁸
The answer, given these numbers, is that it is worth $50,000 a year for the dentist and $3,750 per year for the receptionist to hire people who are one standard deviation above average in proficiency—not the ratio of four to one that separates the dentist’s wages from the receptionist’s but a ratio of more than thirteen to one.
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