In the post below, Colder climates favor civilization even among Whites alone, I made a few comments about possible differences between Germans in Illinois and Germans in Texas, based on nothing much more than a hunch. I trust my hunches, but there's no reason you should, so I decided to see if there was anything here in regards to my assumption about interregional differences in intelligence and how they might track across ethnic groups. So of course I went to the GSS website, and checked the mean WORDSUM scores of various white ethnic groups broken down by region. I specifically focused on whites who stated that their ancestors were from England & Wales, Germany and Ireland. My reasoning is that these are three groups with very large N's within the GSS sample and they are well represented across the regions in absolute numbers. My main motivation was see if the differences across regions were similar for all three groups. Here are the states for each region (the Census made up these categories):

New England - Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut
Middle Atlantic - New York, New Jersey, Pennsylvania
East North Central - Ohio, Indiana, Illinois, Michigan, Wisconsin
West North Central - Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, Kansas
South Atlantic - Delaware, Maryland, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida
East South Central - Kentucky, Tennessee, Alabama, Mississippi
West South Central - Arkansas, Louisiana, Oklahoma, Texas
Mountain - Montana, Idaho, Wyoming, Colorado, New Mexico, Arizona, Utah, Nevada
Pacific - Washington, Oregon, California, Alaska, Hawaii

Obviously the breakdown isn't ideal. I think Delaware and Maryland arguably should be Mid-Atlantic. I also believe that Wisconsin is more plausibly in the West North Central than Missouri or Kansas is. But those are the regional breakdowns and I can't do anything about them.

So, WORDSUM is a vocabulary test on a 0-10 scale. For the whole GSS sample the mean was 6.00, with 1 standard deviation being 2.16. Below is a chart which shows the relationship between WORDSUM scores (Y axis) for various regions (X axis) for each of the three ethnic groups:





The tables below are pretty self-explanatory. At the top you see the mean WORDSUM scores for each ethnic group for each region. I put the N's in there as well so you can see that the sample sizes were pretty big. Note that there is more interregional variation within an ethnic group than there is interethnic variation within a region (the standard deviation across the columns is 50% bigger than across the rows). Just to be clear, I also included some tables which show the differences in WORDSUM mean scores between the regions like so: (row - column) = value.

	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific	N
England & Wales	7.4	7.09	6.71	6.65	6.66	6.2	6.87	6.84	7.1	2,462
Germany	7.7	6.31	6.01	6.33	6.16	5.83	6.2	6.37	6.36	3,316
Ireland	6.98	7.07	6.15	6.46	6.06	5.66	6.03	6.51	6.88	2,207
England & Wales
	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	0.31	0.69	0.75	0.74	1.2	0.53	0.56	0.3
Middle Atlantic	-	-	0.38	0.44	0.43	0.89	0.22	0.25	-0.01
East North Central	-	-	-	0.06	0.05	0.51	-0.16	-0.13	-0.39
West North Central	-	-	-	-	-0.01	0.45	-0.22	-0.19	-0.45
South Atlantic	-	-	-	-	-	0.46	-0.21	-0.18	-0.44
East South Central	-	-	-	-	-	-	-0.67	-0.64	-0.9
West South Central	-	-	-	-	-	-	-	0.03	-0.23
Mountain	-	-	-	-	-	-	-	-	-0.26
Pacific	-	-	-	-	-	-	-	-	-
Germany	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	1.39	1.69	1.37	1.54	1.87	1.5	1.33	1.34
Middle Atlantic	-	-	0.3	-0.02	0.15	0.48	0.11	-0.06	-0.05
East North Central	-	-	-	-0.32	-0.15	0.18	-0.19	-0.36	-0.35
West North Central	-	-	-	-	0.17	0.5	0.13	-0.04	-0.03
South Atlantic	-	-	-	-	-	0.33	-0.04	-0.21	-0.2
East South Central	-	-	-	-	-	-	-0.37	-0.54	-0.53
West South Central	-	-	-	-	-	-	-	-0.17	-0.16
Mountain	-	-	-	-	-	-	-	-	0.01
Pacific	-	-	-	-	-	-	-	-	-
Ireland	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	-0.09	0.83	0.52	0.92	1.32	0.95	0.47	0.1
Middle Atlantic	-	-	0.92	0.61	1.01	1.41	1.04	0.56	0.19
East North Central	-	-	-	-0.31	0.09	0.49	0.12	-0.36	-0.73
West North Central	-	-	-	-	0.4	0.8	0.43	-0.05	-0.42
South Atlantic	-	-	-	-	-	0.4	0.03	-0.45	-0.82
East South Central	-	-	-	-	-	-	-0.37	-0.85	-1.22
West South Central	-	-	-	-	-	-	-	-0.48	-0.85
Mountain	-	-	-	-	-	-	-	-	-0.37
Pacific	-	-	-	-	-	-	-	-	-

Labels: civilization, climate, crime, education, IQ, true redneck stereotypes

Last year I had a crazy idea about how winged insects might influence civilization. I only pointed to winged insects as an exemplar, not to suggest a "Mosquito Theory of History" or something stupid and sexy like that. The reasoning is simple: insects are more likely to be winged in certain climates, and that means more effective vectors of disease in such environments; and a greater disease burden makes you dumber, more tired, and more irritable, which stunts the growth of civilization. [1] A qualitative follow-up post looked at where civilizations have ever appeared, and in what climate types they existed.

Well, now I've done some quantitative work, and it turns out that I was right. One critique against an international study is that natural selection may have adapted people to be more or less civilized in different environments, so that the only influence of climate is as a selection pressure for genetic change. There are at least two such studies already out there: one by Templer & Arikawa (2006) and another by Vanhanen (2004). I'm arguing that it matters even when people start out pretty much the same genetically, so I will look just at the US. It varies enough in climate and degree of civilization that any correlation should jump out.

Motivation

In particular, I will look at the correlation, on the level of states, between average annual temperature and the average IQ of Whites, post-secondary degrees awarded to Whites per capita, and the percent of the White population that's imprisoned. I only look at Whites in order to avoid the confound of climate with racial composition (for example, the cold Mountain states are heavily White, while Blacks make up a larger fraction in the hot Southeast).

The reason I look at basic measures like IQ or being in jail, as opposed to the loftier things we associate with civilization, is that smarts is the key determinant of propelling the institutions of civilization forward, while crime gives us a good rough idea of how barbaric we are on a personal level. I'm sure that governments can improve or screw things up too, but it's the raw cognitive and behavioral materials that matter most, as Lynn and Varhanen show in IQ and the Wealth of Nations (see all GNXP posts on this topic). Moreover, studies of representative samples of the population always show a strong influence of IQ on how cultured a person is. See, for example, a National Endowment for the Arts report on the demographics of arts attendees (PDF p. 19), which shows that attendance increases nearly monotonically by education level.

The results







As you can see, hotter average temperature is associated with lower White IQs, fewer degrees being awarded to Whites per capita, and a higher percentage of the White population being imprisoned. The relationship looks pretty linear in each case, and the data are on an interval scale, so we check the Pearson correlation coefficient: between White IQ and temperature, it is -0.48 (p = 0.0005, two-tailed); between degrees to Whites and temperature, it is -0.57 (p = 0.00002, two-tailed); and between percent of Whites in jail and temperature, it is +.40 (p = 0.005, two-tailed). Even conservatively correcting for three independent hypotheses still leaves all results significant (and IQ and getting a college degree are not even independent). At any rate, average temperature accounts for 23%, 32%, and 16% of the variance in White IQ, degrees to Whites, and percent of Whites in jail, respectively -- pretty damn good for social science. [2]

Methods

I took the average annual temperature for each of the 48 continental states (Alaska and Hawaii were not included in the source, so I left them out). Next, I used Audacious Epigone's estimates of White IQ by state, which are based on NAEP data from 8th grade math and science test scores (read about his methods here). I turned to Statemaster.com for the per capita number of post-secondary degrees awarded to Whites. For the number of Whites in prison per 100K Whites in the state's population, I used the data from 1997 in a study by the National Center on Institutions and Alternatives (PDF here), which separates non-Hispanic Whites from Hispanics, unlike most crime data from government agencies. [3]

Discussion

Here, correlation probably is causation, as climate precedes the other three variables in causality, and again because these are unlikely to be genetic differences that reflect adaptation to different environments -- one of the few cases where natural selection "has not had enough time."

An objection is that the differences could reflect a "brain drain," whereby smart people flock to colder states, and their smart children boost the state's NAEP scores. Even in this case, where climate does not cause group differences in IQ, it still confirms the hypothesis that colder climates favor civilization -- why else would smarties flock there? But I doubt this anyway, since Montana, Wyoming, and North and South Dakota are not exactly fonts of civilization that smarties pour into, yet they have White IQs on par with the highly developed New York City metro area.

If it is causation, as seems likely, the mechanism could be anything. Pathogen load is surely part of it, hence the fields of study called "tropical disease" and "tropical medicine." Also, you might sweat too much in hotter environments, bringing you closer to dehydration. As mild as these effects may seem, when accumulated over the course of development, they could result in your body spending more resources on bodily maintenance than on luxury items like IQ and toil. Heat could also just make you more fatigued -- that wouldn't affect IQ, but it would affect your work ethic, making you less likely to complete college and more likely to pursue quick fixes like crime to get what you want.

The correlation is stronger for getting a college degree than performance on 8th grade math and science tests, and that could be because college work is more g-loaded, because it also taps into work ethic aside from IQ, and because out-of-staters show up in the college figures but not the 8th grade figures. As tough as the environment may seem to natives, it must seem unbearable to college students raised in a different climate.

To the best of my knowledge, as the saying goes, this is the first demonstration of an association between climate type and IQ, civilization-related achievement, and crime, even among a population that's pretty homogenous genetically (for the traits of interest, at least). Even what genetic diversity there is among Whites would underestimate the effect -- Whites adapted to hotter environments, such as Italians and Greeks, are far more concentrated in the colder states within the US. To put the final nail in the coffin, though, you'd want to look at babies of Whites who are adopted into White families in a state of noticeably different temperature than that of the biological parents.

Still, it seems pretty unavoidable: hotter environments are less conducive to civilization, at least for Whites, and not just in extreme cases like the failed attempt to colonize sub-Saharan Africa. Civilization may have started in hot areas, but that was then. It apparently flourishes much more in colder climates. Just as we provide iodine in table salt to prevent a nutrient deficiency from lowering IQ, it might be just as well to encourage people to settle colder areas.

It's not like they'd be abandoning civilization -- just the opposite. They could take their accents, music, and whatever else with them, but they would not suffer the environmental insults that lower their group's IQ, lower their ability to get a college degree, and make them more likely to commit crime. Fortunately for them -- and unfortunately for current residents -- the Mountain states have incredibly low population densities and could absorb some Whites from hotter states. That would certainly burden the locals for a generation, but again since lower White IQ in the Southeast is probably due to largely treatable environmental causes, it won't take long for them to contribute as citizens on the same level as the locals.

Notes

[1] Underlying this is likely a tendency for all sorts of things to be more migratory in such environments -- winged insects were chosen because there's lots of solid data to illustrate the point. Basically, environments that are highly unstable favor migratory features since your environment may go from good to bad from one day to the next, or from one spot to the next -- and being able to quickly move on to greener pastures will be well worth it. When environmental quality does not change much in space or time, then the expensive wings (or whatever) will not pay off.

[2] If you don't have statistical software, you can do a lot for free on Wessa.net, including correlation.

[3] Although I didn't run a test of normality on the distributions for temperature, iq, degrees, or crime, I did check the skewness of all, and only crime was significantly skewed: for crime, skewness is +2.1 standard errors of skewness (SES); for temperature, +1.24 SES; for degrees, +0.35 SES; and for IQ, -1.51 SES.

Addendum from Razib: I put up a related post at my other weblog.

Labels: civilization, climate, crime, education, IQ, true redneck stereotypes

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)

Conclusion

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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