Puzzles and paradoxes

Puzzles and paradoxes
(Or: If I was teaching a critical creative thinking class)

I. Historic Differences
A. There are/were historic technological differences which correlate with geography [1].
B. The contemporaneous technological differences correlate with differences circa 1000 BC [2]

II. National G differences
A. There are contemporaneous national (G) differences (a positive manifold of IQ and student achievement tests) [3,4]
1. The national G differences are spatially related [5]
2. The national G differences correlate with mean temperature; mean temperature explains a large portion of the variance in national IQs [6]
a. Cold climate exerts selection pressure for cognitive capabilities in non-human animals. [7]
b. Paleoclimate correlates with cranial capacity (.41) [8]

B. The national G differences correlate with latitude (.5) [9]
1. Latitude correlates with cranial capacity (.61) [8]

C. The national G differences correlate with parasite load [10]
1. In the US, parasite load correlates with IQ and partially explains the north, south IQ difference [11]
2. Parasite load correlates with cranial capacity (.47) [8]
3 Given enough time and constancy, an ontogenic effect can translate into a phylogenic effect [10]

D. The national G differences correlate with Skin color (see below) [12]
E. The national G differences overlap with the historic technological differences
F. national G differences correlate with technological patents registered [13] and
economic growth

G. National G differences correlate with (GDP), patent rates, Nobel Prizes, numbers of scientists, political variables (government effectiveness, democracy, rule of law, political liberty), HIV, AIDS and homicide [14]
1. the National G differences are not just GPD differences and the causality does not run form GPD to National G, but from human capital to GPD. [15,16]

F. National G/IQ differences predict total national productivity, national economic performance, and national savings rate; On the individual level, IQ (g) predicts productivity, economic performance, and individual savings rates [31].

III. National G differences and Immigrant differences
A. National Gs predict immigrant wages just as well as IQ tests predict US native performance [16]
1. this finding is not influenced by Flynn effect differences

“Another important question is how the Flynn effect impacts these scores: might the Flynn correction introduce some bias?All scores used thus far in this paper employ only Flynn/adjusted IQ scores. [Using the raw data] we find that the correlation between LV’s national average IQ and year 1998 log GDP per worker (Penn World Tables) is 0.83 with unadjusted scores and 0.85 with Flynn/adjusted scores,
A minor difference.”

2. the predictive power of IQ tests is their g-loadedness [17]

B. The South/Central American National G average is .5-.8 SD below that of European Nations. [3, 14]
1. Hispanic Americans have a g-loaded IQ .5-.8 SD below white Americans [18, 20]
2. This g-loaded difference was found by the Coleman report in 1966 [19]

C. The West Indian National G average is .5 to 1.5 SD below that of European nations
1. West Indian Black immigrants to the US do no better than internal African-American immigrants; they are geneotypically selected [21]
2. Second generation Antillian immigrants to the Netherlands have a IQ (g) .8 SD below the White Dutch norm [22].

IV. The colorism Paradox
A. The national G differences correlate with Skin color [12]
B. Within the African American population there is a .15 IQ-skin color correlation; the magnitude is consistent with the hereditarian hypothesis [23]
C. Within the African American population there is a skin color – SES, prestige, crime correlation [24]
1. There is a crime nexus (see below)
2. Within the African American population the skin color – negro looking SES correlation was present in the early 19th century [25].
3. Within many Latin American countries, there is a color-SES, Education relationship [26, 27, 28]

V. The crime nexus
A. Internationally N.E Asian countries have lower crime rates than European nations, than African Nations [29]
B. In the US, UK, and Canada, Ancestral West SS African immigrants are more likely to commit crimes than whites (or be caught committing them; N.E Asians are less likely commit crimes (or be caught committing them) [29]
C. In the US, % of Blacks correlates with city violent crime rate (.69) [Whitney (1995)]; county murder, robbery rate and IQ [Bartelsa, Ryana, Urbana, and Glass (2010)]; state crime and IQ [Rhuston and Templer, in press].
D. A similar IQ, crime rate, HIV rate, GDP, skin color manifold exists between US states as exists between nations. [30]

References

[1] Diamond, 1997. Guns, Germs, and Steel: The Fates of Human Societies
[2] Comin, Easterly, and Gong, 2008. Was the Wealth of Nations Determined in 1000 bc?
[3] Rindermann, 2007. The g‐factor of international cognitive ability comparisons: the homogeneity of results in PISA, TIMSS, PIRLS and IQ‐tests across nations
[4] Lynn and Mikk, 2009. National IQs predict educational attainment in math, reading and science across 56 nations
[5] Gelade, 2008. geography of IQ
[6] Vanhanen, 2002. Climate and Democracy
[7] Roth, LaDage, and Pravosudov, 2010. Learning capabilities enhanced in harsh environments: a common garden approach
[8] Beals, et al., 1984. Brain Size, Cranial Morphology, Climate, and Time Machines
[9] Wicherts, Borsboom, Dolan, 2009. Why national IQs do not support evolutionary theories of intelligence
[10] Eppig, Fincher, and Thornhil, 2010. Parasite prevalence and the worldwide distribution of cognitive ability
[11] Eppig, Fincher, Thornhill, 2011. Parasite prevalence and the distribution of intelligence among the states of the USA
[12] Templer, 2010. IQ and Skin Color: The Old World Reexamined and the New World
[13] Gelande, 2008. IQ, cultural values, and the technological achievement of nations
[14] Rindermann, et al., 2009. The impact of smart fractions, cognitive ability of politicians and average competence of peoples on social development Between nations.
[15] Rindermann, 2007. The big g‐factor of national cognitive ability
[16] Jones, 2008. IQ in the Production Function: Evidence from Immigrant Earnings
[17] te Nijenhuis et al, 2007. Score gains on g-loaded tests: No g; Gottfredson, 2002. g: Highly general and highly practical
[18] Roth et al., 2001. Ethnic group differences in cognitive ability and educational setting: A meta-analysis
[19] Gottfredson, 2006. Social consequences of group differences in cognitive ability
[20] Hartmann, 2007. Testing the cross-racial generality of Spearman’s hypothesis in two samples
[21] Model, 2008. The Secret of West Indian Success
[22] te Nijenhuis, 2004. Are cognitive differences between immigrant and majority groups diminishing?
[23] Jensen, 1973. Educationability and group differences.

The expected mean correlation between IQ and skin color (SC) would be the square root of the product of the reliabilities (i.e square) of the correlation between IQ and individual ancestry (IA) and SC and individual ancestry (IA), assuming some between group heritability (BGH) of IQ. The average SC-IA correlation for African Americans is around .44 (ranging from .34 to .54); the reliability of skin color as a predictor of African American Ancestry is, therefore, .19. The average IQ-IA correlation obviously has yet to be determined. Assuming a BGH of 1, the IQ-IA correlation could range anywhere from .25 to .50, giving predictive validities of .05 to .25. (The IQ-IA correlation would most certainly be less than 1; consider that siblings who share the same ancestry (and half their genes) only have an IA- IQ correlations of ~.50!) Using .44 as the SC-IA correlation, the maximum and minimum expected IQ-SC correlations, assuming a BGH of 1, would be around 10% and 22%, respectively. The weighted average IQ-SC correlation found to date is ~.15 (I get .17, N= 1083), which falls comfortably within the predicted range. [Of course, given that the HH does not maintain a BGH of 1 but rather a BGH of .5 to .8 relative to 1SD of difference and that a lower predicted BGH (than 1) would decrease the expected maximum IQ-SC correlation, the expected minimum/maximum IQ-SC correlation should be less than 10%/22%.]

[24] Hochschild and Weaver, 2008. The Skin Color Paradox and the American Racial Order
[25] Hill, 2000. Color Differences in the Socioeconomic Status of African American Men: Results of a
Longitudinal Study

The data hill used were based on the following classification system:

“in all cases where the person is white, leave the space blank; in all cases where the person is black, insert the letter B; if mulatto, insert M” and “Be particularly careful in reporting the class Mulatto. The word is here generic, and includes quadroons, octoroons,and all persons having any perceptible trace of African blood” (Snip, 2003).

As quoted in Hill:
“Mulattoes always have enjoyed opportunities somewhat greater than those enjoyed by the rank and file of the black Negroes. In slavery days, they were most frequently the trained servants and had the advantages of daily contact with cultured men and women. Many of them were free and so enjoyed whatever advantages went with that superior status. They were considered by the white people to be superior in intelligence to the black Negroes and came to take great pride in the fact of their white blood…. The higher the standard of success, the lower the per cent [sic] of full-blooded Negroes. (378-79) –Reuters, 1918”

[26] Hunter, 2007. The Persistent Problem of Colorism: Skin Tone, Status, and Inequality.
[27] Harris, 2008. From color line to color chart?: Racism and colorism in the new century
[28] Lynn, 2008. PIGMENTOCRACY: RACIAL HIERARCHIES IN THE CARIBBEAN AND LATIN AMERICA
[29] Rushton and Templer, 2009. National differences in intelligence, crime, income, and skin color

“The worldwide distribution of race differences in murder, rape, and serious assault are found in the INTERPOL Yearbooks. From the 1986 Yearbook, Rushton (1990) collated the ates per 100,000 people for 12 East Asian countries, 48 European countries, and 28 African and Caribbean countries and found: for murder, 6, 5, and 9; rape, 3, 6, and 14; and serious assault, 29, 66, and 130, respectively. From the 1990 Yearbook, Rushton (1995) examined the rates per 100,000 people for 12 East Asian, 41 European, and 23 Afro-Caribbean countries and found: for murder, 3, 5, and 13; rape, 3, 6, and 17; and serious assault, 27, 63, and 213, respectively. From the 1993–96 Yearbooks, Rushton and Whitney (2002) examined the rates per 100,000 people for 7 East Asian, 45 Caucasian, and 22 Afro-Caribbean countries and found: for murder, 2, 4, and 8; rape, 3, 5, and 6; and serious assault, 31, 34, and 136, respectively.”

[30] Rushton and Templer, in press. IQ, Pigmentocracy, Crime, and Income in 50 U.S. States
[31] Jones, 2008. Cognitive Ability and Technology Diffusion: An Empirical Test
[32] Jones, 2010. IQ in the Utility Function: Cognitive skills, time preference, and cross-country differences in savings rates

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