Bell Curve

76 The Emergence of a Cognitive Elite The Economic Pressure to Partition 7 7enlisted personnel spread over eighty-nine military specialties. The personnelwere educationally homogeneous (overwhelmingly high schoolgraduates without college degrees), conveniently "controlling" for educationalbackground.f241What explains how well they performed? For every one of the eightyninemilitary schools, the answer was g-Charles Spearman's general-intelligence. The correlations betweengalone and military school graderanged from an almost unbelievably high .90 for the course for a technicaljob in avionics repair down to .41 for that for a low-skill job associatedwith jet engine maintenance.[251 Most of the correlations wereabove .7. Overall, g accounted for almost 60 percent of the observedvariation in school grades in the average military course, once the resultswere corrected for range restriction (the accompanying note spellsout what it means to "account for 60 percent of the observed variati~n").[~~]Did cognitive factors other than g matter at all? The answer is thatthe explanatory power of g was almost thirty times greater than of allother cognitive factors in ASVAB combined. The table below gives asampling of the results from the eighty-nine specialties, to illustrate theThe Role of g in Explaining Training Success forVarious Military SpecialtiesEnlisted MilitarySkill CategoryPercentage of TrainingSuccess Explained by:g Everything ElseNuclear weapons specialist 77.3 0.8Air crew operations specialist 69.7 1.8Weather specialist 68.7 2.6Intelligence specialist 66.7 7.0Fireman 59.7 0.6Dental assistant 55.2 1 .OSecurity police 53.6 1.4Vehicle maintenance 49.3 7.7Maintenance 28.4 2.7Source: Ree and Earles 1990a, Table 9.two commanding findings: g alone explains an extraordinary proportionof training success; "everything else" in the test battery explained verylittle.An even larger study, not quite as detailed, involving almost 350,000men and wotnen in 125 military specialties in all four armed services,confirmed the predominant influence of g and the relativelyminor further predictive power of all the other factors extractedfrom ASVAB scores.27 Still another study, of almost 25,000 air forcepersonnel in thirty-seven different military courses, similarly found thatthe validity of individual ASVAB subtests in predicting the final technicalschool grades was highly correlated with the g loading of thesubte~t.'~~'EVIDENCE FROM CIVILIAN JOBS. There is no evidence to suggest thatmilitary jobs are unique in their dependence on g. However, scholarsin the civilian sector are at a disadvantage to their military colleagues;nothing approaches the military's database on this topic. In one of thefew major studies involving civilian jobs, performance in twenty-eightoccupations correlated virtually as well with an estimate of g fromGATB scores as it did with the most predictively weighted individualsubtest scores in theThe author concluded that, forsamples in the range of 100 to 200, a single factor, g, predicts jobperformance as well as, or better than, batteries of weighted subtestscores. With larger samples, for which it is possible to pick up theeffect of less potent influences, there may be some modest extrabenefit of specialized weighted scores. At no level of sampling,however, does g become anything less than the best single predictorknown, across the occupational spectrum. Perhaps the most surprisingfinding has been that tests of general intelligence often do better inpredicting future job performance than do contrived tesrs of jobperformance itself. Attempts to devise measures that are specificallykeyed to a job's tasks-for example, tests of filing, typing, answeringthe telephone, searching in records, and the like for an officeworker--often yield low-validity tests, unless they happen to measureg, such as a vocabulary test. Given how pervasive g is, it is almostimpossible to miss it entirely with any test, but some tests are far moreefficient measures of it than others.30