Sunday, February 11, 2007

Wherever the abilities involved are sufficiently distinct--and that is in the great majority of cases--our tetrad equation is satisfied with surprising exactitude, so that here each ability must be divisible into g and s. The letter g becomes, in this manner, a name for the factor--whatever it may be--that is common to mental tests of such a description. This is the very definition of g. (Spearman, 2005, p. 161)

General intelligence (g) has been one of the most, if not the most, aggressively studied constructs in psychology. Type the search string "general intelligence" in PsycInfo and you will return over 2000 entries, and a similar search in Pubmed pulls up over 400. If you broaden the term to just "intelligence", the respective number of entries are 65405 and 37166. While not all of the results focus on g , (e.g., AI, "social intelligence"), a large portion of them do, and the prospect of meandering your way through can be intimidating. Fortunately, the overall literature is consistent and, at least for me, highly engaging.

The study of g can be bifurcated into two distinct areas: vertical and horizontal g . Vertical g is the domain that studies g's biological relationships. It is the area that is going to eventually assimilate enough data and literature to elucidate, unquestionably, the causal mechanisms of g . From this field of study, we know that g is correlated with a variety of neural mechanisms, such at glucose metabolism (Haier, 2003), cortical development (Shaw et al., 2006), and biochemical activity (Jung et al., 2005). We know that g is highly heritable, both when measured psychometrically (Plomin & Spinath, 2002) or chronometrically (Beaujean, 2005). We know that g decreases with inbreeding (Jensen, 1983) and increases with hybrid vigor (Nagoshi & Johnson, 1986). As genome scanning becomingmore popular, we are now even beginning to see some specific genes that are implicated g.

As interesting as vertical g is, however, this entry is going to instead focus in the horizontal aspects of g . That is, how does g play out into "everyday life." Specifically, we will look three different, although related, areas: education, occupation, and general life outcomes. The reasons for doing so are twofold: (a) the more the science of horizontal g is positively promulgated, then, perhaps, the more likely people are to support the needed research into vertical g and (b) even though this area of research has been around for over a century (e.g., Galton, 1869), there are still new, important findings.

Before delving into horizontal g, however, it would behoove us to delineate a mechanism by which g could influence education, occupation, and general life outcomes.For our purposes, that mechanism is information processing. Generally defined, information processing is the pathway and mechanisms by which stimuli are perceived, attended to, retrieved, and/or used to solve problems and/or cope with exigencies in the environment (Jensen, 1998a). The cognitive psychology literature is chalked full of the nuances of the various information-processing theorists, the specifics are which cannot be delineated here (an easy-to-read intro: Ormrod, 2004). Yet, within all these theories lies the idea that people respond to stimuli in a way that involves many mechanisms (e.g., sensory register, primary memory)and a variety of neurological regions (e.g., hippocampus, amygdala, mammillary bodies). The consequence? There is ample room for individual differences in the speed and efficiency in which information is processed.

From another perspective (e.g., Kline, 1998), information is processed in irreducibly small pieces (often called bits) and the time it takes to process those bits is the BIP, the Basic period of Information Processing. Now, the time it takes Johnny to process the fact that the only integer between 2 and 4 is 3 is going to be different than the time it takes Jane. Multiply those differences by the number of people processing the fact, and voila! individual differences.

Educational Outcomes

This is probably the area most replete with data and, unsurprisingly, the g-educational achievement relationship is strong. In fact, although it differs by grade level (with it decreasing as grade level increases), most of the non-random variance in scholastic performance is accounted for by g (Thorndike, 1984). Jensen (1989, 1998b) writes that this is so due to the fact that "school learning" is, itself, quite g -loaded. Of course, there are those who write that g is just a product of education (e.g., Ceci, 1991; for a review of others, see Gottfredson, 1986), or, perhaps more egregious, that g and educational achievement are just products of the tests designed to measure them (for review and rebuttal, see Jensen, 1984). But these arguments quickly dissipate when looking at the evidence.

For example, in the latest issue of Intelligence, there were two longitudinal studies (Deary, Strand, Smith, & Fernandes, 2007; Watkins, Lei, & Canivez, 2007) that showed a strong IQ --> Educational Achievement relationship (approx. 70 from Deary), but reverse (i.e., EA --> IQ) was not there (from the Watkins study). Further evidence comes from the two major "We can improve you Education by improving your IQ" projects: Head Start and the Abecedarian Study. With regard to the former, Head Start just does not produce long-term IQ gains and, hence, does not produce long-term academic gains (Caruso, Taylor, & Detterman, 1982; Holden, 1990; Kreisman, 2003). With regard to the latter, while there has been acrimonious debate, the overall conclusion is that, like Head Start, the initial IQ gains do not last, giving even more evidence that educational achievement cannot be raised independently of g (Spitz, 1986, 1992, 1993b, 1993a).

Yet another line for arguing against the prominence of g in education is the idea that there are other traits that are just as necessary for academic success, such as motivation, personality, etc. To risk sounding like to broken record, the data shows that these traits are not nearly as potent predictors as g in predicting academic outcomes. For example, Gagne and St. Pere (2002) gives us reason to believe that motivation might just be an impotent variable in predicting academic achievement. Likewise, Laidra, Pullmann, and Allik (2007) have shown that while personality factors contribute some to the variance in educational achievement, they are dwarfed in comparison to the contribution of g.

Occupational Outcomes

There are many theories as to how g and occupational outcomes relate (see Gottfredson, 1986), but the one that is most supported by data is best explicated by Frank Schmidt and John Hunter

[g] predicts both the occupational level attained by individual and their performance within their chosen occupation. [g] correlates above .50 with later occupational level, performance in job training programs, and performance on the job. Relationships this large are rare in psychological literature and are considered "large" . . . weighted combinations of specific aptitudes (e.g., verbal, spatial, or quantitative aptitude) tailored to individual jobs do not predict job performance better than [g] measures alone, thus disconfirming the specific aptitude theory. It has been proposed that job experience is a better predictor of job performance than [g], but the research findings . . . support the opposite conclusion. . . . Nearly 100 years ago Spearman (1904) proposed that the construct of [g] is central to human affairs. The research . . . supports his proposal in the world of work, an area of life critical to individuals, organizations, and the economy as a whole.(Schmidt & Hunter, 2004, p.171; cf.Schmidt & Hunter, 1998)

One could argue that, given the high g -education relationship, that the g-occupation relationship is just a natural outgrowth.That is, once education is controlled, the g-occupation relationship significantly shrinks. But to make that argument, one would have to have a Sternberg-like approach to intelligence (Sternberg & Wagner, 1993). That is, that the cognitive skills needed for a successful education are somehow vastly different than those needed for everyday life. The data, however, indicate that the same generative process that tends to makes one successful in the educational arena is also the mechanism that tends to make one successful in the occupational arena: g (Kuncel, Hezlett, & Ones, 2004). This is not to say that other things are not important in occupational or educational outcomes; but, as with education, they are not nearly as potent predictors (Gottfredson, 2002).

Life Outcomes

Over the last decade or so, an area that has become of more interest to the intelligence community is the influence of g on general life outcomes. That is, beyond educational and occupational outcomes, does g contribute to life success? The answer here, too, seems to be a resounding yes.

IQ scores [a proxy for g] predict a wider range of important social outcomes and they correlate with more personal attributes than perhaps any other psychological trait. The ubiquity and often-considerable size of g's correlations across life's various domains suggest g truly is important in negotiating the corridors of daily life. (Gottfredson, 2003, p. 326)

But how does g relate to general life outcomes? Believe it or not, it appears that the same information-processing mechanisms that are so potent for educational and occupational outcomes also play a role in day-to-day life (Gottfredson & Deary, 2004). Gottfredson (2003, 2004b) elaborates this mechanism as follows: Life is is made up of many tasks with a wide array of complexity (Gordon, 1997). In the US and most Western nations, society is "free enough" for competence (read: g ) to make a substantial difference in who succeeds in life. As those who have "higher g" are more able to tackle the day-to-day activities of life successfully with less exerted effort, they are able to progress in life with fewer impediments (e.g., untreated illness, accidents; Gottfredson, 2004a), thus allowing them to (a) have more resources to successfully compete and (b) be able to use their resources more efficiently. This then not only allows for a higher probability of achieving satisfying life outcomes (e.g., adequate income, occupational autonomy), but also allows for a lower probability of being involved with unsatisfying life outcomes (e.g., having children without means to support them, crime/delinquency) (cf. Ellis & Walsh, 2003; Herrnstein & Murray, 1996)


Given the ubiquity of g in fostering success in many life outcomes from education achievement to occupational success, from health outcomes to criminal recidivism, social science in general and psychological science in particular would be remiss to "pretend it doesn't matter" (Gottfredson, 2000). Rather, if these fields want to strengthen their scientific integrity and acumen, they should do exact opposite. That is, bring the large, cumulative database on g and its influence on life outcomes to the forefront of a wide array of research agendas so that this corpus of data can serve as the strong underlying foundation of a generation of new investigations on g's life implications. While this line of investigation may never get to the underlying (vertical) mechanisms by which g operates, it can help foster the acceptance of doing such research and pave the way for its societal implications, whatever they may be.


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