Colorism and Crime

One of the many arguments for colorism runs: Darker African-Americans have been found to receive longer prison terms than lighter African Americans. Ergo.. Yes, that’s the argument — with the implicit premise being: And there are no plausible causes, besides anti-dark skin bias, for the correlation between color and length of sentence. Commenting on findings, one science blogger noted:

This proven correlation between skin tone and judicial outcomes doesn’t absolutely prove that skin tone directly causes shorter sentences and earlier release for recent black female prison convicts in North Carolina (“correlation is not the same as causation”). However, it’s hard for me to envision what these intervening factors may be, and there’s clearly a strong link between the two.

And yet new research sheds light on the mechanisms of one probable intervening factor:

Turning to the findings from the IQ Model, three points deserve attention. First, individual-level IQ differences were significantly related to violent misconduct. Inmates with above average IQ scores (relative to other inmates housed in the same facility) were at decreased risk of being involved in a violent incident. A one standard deviation increase in IQ score (as compared to other inmates within the same prison unit) was associated with a ten percent reduction in the odds of committing violent misconduct. The second finding of interest was that the introduction of the IQ variables led to a slight attenuation of the relationship between race/ ethnicity and misconduct. Finally, the average IQ of the prisoners within each of the 30 different prison units was found to have a significant effect on the likelihood of an inmate committing violent misconduct. Simply stated, individuals housed in a unit with a higher average IQ score were significantly less likely to engage in violent misconduct. (Diamond et al., 2012. Individual and group IQ predict inmate violence)

Since the darkest African Americans are only 0.5 SD less intelligent than the lightest, other pathways than color-> IQ-> inmate violence-> increased sentence length must account for some of the 12% of sentencing differences found (as there would only be a 5% difference in immate violence rate, as conditioned by IQ). As IQ has consistently been found to be associated with impulsivity, other pathways may lead from IQ differences to sentence length differences. Alternatively, since in large multicultural samples criminality has been found to be modestly heritable, the causal pathways may be more direct.

Intra-National IQ differences

Flynn has a paper in press which makes, once again, the Flynn effect to the rescue case:

Table 5c gives Raven’s trends from the developing world. Kenya and Dominica appear to have embarked on a period of explosive gains. Sudan has made gains on the WAIS: large fluid gains (on the Performance Scale) were accompanied by a small loss for crystallized intelligence (Daley, Whaley, Sigman, Espinosa, & Neumann, 2003; Khaleefa, Sulman, & Lynn, 2009; Meisenberg, Lawless, Lambert, & Newton, 2005). Flynn (2009c) speculates that the developing world in general may soon experience the Scandinavian decline. If that occurs, and if developing nations are entering a long period of peak gains, the 21st century will see the IQ gap between those two worlds close. (Flynn and Rossi-Casé, 2012. IQ gains in Argentina between 1964 and 1998.)

What’s uncanny, from this perspective, is the decade to decade constancy of the international differences in FSIQ. The table below, for example, lists all the studies published to date with respect to North Africa (Al-Shahomee (2012), excepting). Over the last 50 years, there has been little change in the UK/Europe-North African gap. Similar results are found for the UK/Europe-African gap and others. Flynn’s argument is that the secular increase will slow in developed countries and speed up in developing countries, leading to a complete convergence. By this same logic, one might have expected a large divergence between developed and developing countries over the last century. The quality of life/education, etc., gaps, after all, have not remained constant. For example, in the case of Sudan, in the last half of the last century, the WAIS IQs increased at 2.05 points per decade as compared to the 3 points per decade in the US, while, over the same period, Per capita income has increased almost 200% more in the US. Were per capita income behind the secular rise, we would expect a large divergence between US and Sudan scores.

Al-Shahomee, 2012. A standardisation of the Standard Progressive Matrices for adults in Libya

Whatever the case, Flynn’s argument seems plausible. Which is why intra-national IQ differences — or the possible lack thereof – are the important ones when it comes to determining the plausibility of a genetic hypothesis.

Gaps around the world

I’ve decided to take Richard Lynn up on his 2010 challenge:

“If a multiracial society is found where these race differences in intelligence are absent, the evolutionary and genetic theory of these differences would be falsified. Those who maintain that there are no genetic differences in intelligence between the races are urged to attempt this task.”

As such, I’m going to start collecting new data (i.e., from 2000 on), starting with secondary data, on the ethnic gaps in multiethnic societies. If you’re aware of any good sources feel free to let me know. I am generally only interested in data which includes a standardized measure of ability. I’m going to take my time on this, so this post will be continually updated until I find a society that substantially falsifies Lynn’s evolutionary hypothesis.

General

Sackett et al. Perspectives From Twenty-Two Countries on the Legal Environment for Selection (Chapter 30). Farr and Tippins (Eds.), 2010. Handbook of Employee Selection.

Baron et al., 2005. Ethnic group differences and measuring cognitive ability. International Review of Industrial and Organizational Psychology

Australia

(Summary: Gaps much smaller than reported in Lynn (2008); aborigine/non-aborigne gaps about 1 SD)

Dalton, 2011. US Educational Achievement on International Assessments: The Role of Race and Ethnicity. See: Table 3. TIMSS 2007 achievement differences between majority and minority students in Australia, New Zealand, and the United States

Leigh and Gong, 2008. Estimating Cognitive Gaps Between Indigenous and Non-Indigenous Australians
(See table 1. Summarizes scores from tens of thousands of individuals)

Thomson et al., 2010. Challenges for Australian Education: Results from PISA 2009 (see p. 63, 189, and 233 for reading, math, and science non-aborigine/aborigine gaps, respectively)

Canada
(Summary: Can’t find any good data; generally, “visible minorities” underperform Whites)

Chung-Yan and Cronshaw, 2005. Information Exchange Article A Criterion-Related Validation Study of Transit Operators

Hausdorf et al., 2005. Cognitive Ability Testing and Employment Selection- Does Test Content Relate to Adverse Impact?

Jain, et al. Recruitment, selection and promotion of visible-minority and aboriginal police officers in selected Canadian police services

Finnie and Meng, 2003. Minorities, Cognitive Skills and the Incomes of Canadians

Vanderpool and Catano, 2008. Comparing the Performance of Native North Americans and Predominantly White Military Recruits on Verbal and Nonverbal Measures of Cognitive Ability

Europe
(Summary: Turks don’t seem to do so bad.)

Dustmann et al., 2012. Education of second generation immigrants

Holland
(Summary: Gaps are narrowing; some differences are clearly due to psychometric bias; minorities over-perform on measures of reaction time.)

Gijsberts, et al., 2012. Bijlagen Jaarrapport integratie 2011

Helms-Lorenz et al., 2002. Cross-cultural differences in cognitive performance and Spearman’s hypothesis- g or c?

de Meijer et al., 2008. Criterion-Related Validity of Dutch Police-Selection Measures and Differences Between Ethnic Groups

Stevens et al., 2009. Researching race:ethnicity and educational inequality in the Netherlands- a critical review of the research literature between 1980 and 2008

Meijer and Marise, 2006. Applicant and Method Factors Related to Ethnic Score Differences in Personnel Selection: A Study at the Dutch Police

te Nijenhuis et al., 2004. Are Cognitive Differences Between Immigrant and Majority Groups Diminishing?

Israel
(Summary: Ethiopian immigrants underperform other Israelis by around 1.3 SD on PISA tests.)

Nesher, 2012. Report shows widening gap between Ethiopian pupils and other Israelis. Haaretz.

UK
(Summary: Ambiguous results; generally UK blacks perform below UK whites; “Asian” scores are often not disaggregated)

See references in:

Occidentalist, 2011. The General Mental Ability (GMA) of Black British

Occidentalist, 2012. Is (global) “race realism” still tenable?

Occidentalist, 2012. Partially falsified

Frederickson and Petrides, 2005. Ethnic, gender, and socio-economic group differences in academic performance and secondary school selection: A longitudinal analysis

USA (immigrant data)
(Summary: 2nd generation Blacks and Hispanics underperform 2nd and 3rd generation Whites and Yellows.)

See references in:

Occidentalist, 2012. More immigrant IQ

South Africa
(Summary: Gaps, as reported in IO, are smaller than as reported in Lynn (2008).)

See also discussion in Baron et al. (2005) (above)

Kriek and Dowdeswell. Adverse Impact & Validity Evidence in South Africa- 12 Years of Data Trends

Quirion, 2011. The predictive validity of psychological test battery for the selection of cadet pilots in a commercial airline

Sweden
(Summary: Gaps clearly due, in part, to psychometric bias.)

Kvist, 2011. Interpretation of Cognitive Test Scores in Relation to Swedish and Immigrant Groups

Kvist and Gustafsson, 2008. The relation between fluid intelligence and the general factor as a function of cultural background: A test of Cattell’s Investment theory

New Zealand
(Summary: Relative to Europeans, Pacific Islanders perform as they do in the US)

Telford and May, 2010. Pisa 2009: Our 21st century learners at age 15 (p. 12, 28, and 38 for reading, math, and science respectively)

A little bit of difference goes a long way

In response to my post about the UK Black-White difference (or lack thereof) – and its implications for race realism, I received a virtual laundry list of environmentalist explanations:

The negative effect of White UK culture:

The big thing to look into is the emergence of a gender gap over the last generation in Britain favoring teen girls in run-of-the-mill tests like the GSCE. It’s significantly bigger than in the U.S., and seems to hold across most ethnicities. It’s a smoking gun that something is going wrong with white British culture.

The positive effect of Black Mulatto culture:

Another thing to keep in mind is that while I don’t know about the UK, I know that in the U.S., a lot of West Indians are from the mulatto elite: Attorney General Eric Holder, General Colin Powell, singer Rhianna, journalist Malcolm Gladwell, etc.

Motivation:

I think a likely (partial?) explanation is that the Black students tended to be more motivated to get good grades. They probably took less challenging courses since we can see that the White advantage is much greater when English and Math are included (these are probably more rigorous subjects).

That the tests don’t measure intelligence:

The GCSE data in the Deary et al. study are from 2002. In 2002, about 47% of all students obtained fewer than 5 GCSEs at grade C or above, whereas in 2009 the proportion was only 25% (see graph 1). It’s obvious that there’s been lots of grade inflation

Low expectations for Whites:

So, my overall model of Britain’s social system v. America’s is that the former is dominated by class and the latter by race. The British system tends to be better for blacks because they have less pressure on them to Act Black all the time, while it’s worse for poorer whites because they are constantly pressured by their peers not to Act Toff by like, you know, reading.

And systematic scientific anti-racism and biased research:

The British establishment is so extreme in its anti-white position, and so desperate to degrade its own native population in favor of blacks and Asians, that we should not take any official figures from Britain seriously

Let’s put aside the fact that my original estimate of little difference now seems questionable (i.e., there possibly seems to be a UK Black-White difference of 0.5 or so standard deviations.) The first couple of responses were somewhat unbelievable, given what is typically argued by hereditarians: High within population heritability limits between population environmental influences. This is a staple hereditarian argument, which goes:

The heritability of IQ for both Blacks and Whites is high at older ages. For example, in an analysis of the nationally representative ADD health data, Guo and Stearns (2002) found respective Black and White adolescent heritabilities of .57 and .71 and respective between family environmentalities of .16 and .03; similarly high within population heritabilities have been found in other studies (Rushton and Jensen, 2005). In absence of measurement bias and unique factors which uniformly raise or lower one or the other population’s scores (i.e. X-factors), high within population heritabilities constrain between population environmental influences. . If, for example, two populations have between family within population environmentalities of 0.16 and strict measurement invariance holds, for environmental influences to create a 1 SD difference, 2.5 SDs of environmental influence are needed (i.e., 1/ sqrt(0.16)). Several studies have shown that, in the case of Blacks and Whites, there are no detectable X-factors (e.g. Rowe et al., 1994; Rowe et al., 1995; Carretta, 1995; Carretta and Ree, 1995) and several other studies have shown that differences between Blacks and Whites are not due to measurement bias (Dolan, 2000; Dolan and Hamaker, 2001; Lubke, et al 2003)…..

(See, Jensen, 1973; Jensen, 1998; Murray and Herrnstein, 1994; Levin, 1997; Sesardic, 2005…)

This applies to the presence of differences just as much as it does to the absence. Given a hereditarian model, and given the magnitude of differences typically proposed, the said environmental explanations for an absence are simply implausible.

There is, of course, an out. Flynn and Dickens (2001) have provided it. Flynn and Dickens’ social multipliers model – which is frequently cited by quasi-environmentalists — works just as well in defense of “race realism” as it does in defense of environmentalism, if one is willing to adopt what we might call “geneticism,” where this simply refers to the view that race differences are caused, directly and/or indirectly, by genes.

By the Flynn and Dickens model, small genotypic differences between individuals and/or populations (say, 0.2 SD) can multiply, by way of gene-environment covariance, to produce large phenotypic differences (Say, 1 SD). To the extent that this gene-environment covariance is active, in the sense of individuals selecting their own phenotypic shaping environments, the resulting differences can be said to be causally genetic, in an indirect sense. This model can be applied to numerous behavioral traits. Moreover, between population multiplication is not heavily contingent on within population multiplication. Now that Flynn and Dickens have established the a priori plausibility of this model, it can only be ruled out, as a mechanism of between population phenotypic differentiation, by testing populations and showing the absence of the prerequisite small genetic differences.

Geneticism, as so conceptualized, is not exclusive of hereditarianism. Hereditarianism is just a subtype of geneticism; it’s the view that race differences are largely caused by additive genetic differences (e.g., a 0.8 geneotypic SD difference to a 1 phenotypic SD difference.)

Adopting a geneticist view, expands greatly the scope of “race realism.” Doing so also changes the contours of the race-genes debate. Arguments which are potent against hereditarianism are impotent against geneticism. Malleability of between group differences; absences of differences in certain environments; unusually small differences between mixed race individuals – are all consistent with variants of geneticism that don’t posit large hereditarian differences. Such models make predictions, of course; they predict the probable occurrence of differences – as opposed to the necessary occurrence (in absence of implausibly large countervailing environmental factors) (i.e., across environmental regimes, difference of various magnitude, going in the same direction., will tend to emerge.)

The responses above, then, are not inherently unreasonable. The explanations offered are plausible given some forms of geneticism, particularly weakly hereditarian forms. I would guess, though, that these forms were not being entertained when the reposes were written.

Zachslebachlsegooglebop differentiation

fringeelements’ last video on race for the foreseeable future.

One bizarre argument which fringeelements confronts is the Loring Brace argument that populations couldn’t have differentiated, genetically, with respect to general intelligence. This argument, which Jensen debunked numerously years ago, is apparently being recycled — most likely in response to the clear evidence of Zachslebachlsegooglebop differentiation. It recently crawled out of the dustbin and presented itself to me in a discussion over at RichardDawkins.net. The version which I encountered ran:

If human intelligence is an adaptation to living within a cultural system and learning symbolic forms of communication (language), then what kind of selection pressures could have resulted in some cultural systems requiring more intelligence than others? The experiences of ethnographers during the past hundred odd years has ultimately led anthropologists to conclude that there is is no basis for the notion that the languages and cultures of people living within technologically “simple” economies, such as hunting and gathering, require less brain power than the languages and cultures of “modern” civilization.”

I pointed out, in response, that by this same argument there couldn’t be variance within a population — after all, living within a “modern” or pre-modern civilization should require no less brain power than living within that same civilization — and yet there is a tremendous amount. To get my point across, of course, I had to write the argument out in syllogistic form and show the exact deductive error.

Dealing with these absurd, cleverly silly arguments is incredibly frustrating. And, I imagine, this is why Ryan has decided to take a holiday.

Partially falsified

[Update: Kiwiguy dug up 2006-2010 UKCAT annual report scores. I added them to the discussion below. I also added 2008-2009 UK laws school test (LNAT) results]
[Update: The GL assessment pdf is behaving queerly. I'm looking into it now.]

As usual, JL managed to unearth some obscure document as counter-weight to my otherwise solid case against “race realism.” Below, I summarized the data. Pertinent are the last couple of rows, where White, Mixed, and Black IQs are presented, normed on a White mean of 100 with Standard deviations of 15. You will notice there that the UK Black-White gap is only about 0.5 SD. (Using the first regression formula presented in Wright and Strand (2005) –(.66V + .21Q + .18NV) — table 4, the FSIQ gap is 8.2 points.) And the UK Mixed-White FSIQ Gap is only 30% of that.

Source: GL assessment (2010). Cognitive Abilities Test (CAT) and GCSE grades: 2009/10. Table 4.

Wright and Strand (2005) give some background on CAT3.

The CAT-3 is now the most widely used test of reasoning abilities in the UK, used routinely in educational settings, contributing to over 850,000 pupil assessments in 2002/2003. The test battery comprises 3 scales measuring Verbal Reasoning (VR), Non Verbal Reasoning (NVR), and Quantitative Reasoning (QR) and is traditionally administered in a group classroom setting. Children are provided with answer booklets and are given extensive introductory instructions and practice examples as to how to approach each subtest in the battery. A large scale study carried out by Strand (in press) using CAT-2 (a precursor to the CAT-3), reported very high test-retest correlations over a three-year interval in children aged 10 to 13 years. Correlations ranged from 0.76 for NVR, 0.79 for QR, 0.87 for VR, and 0.86 for mean CAT-2 score. CAT scores are strongly correlated with pupils’ subsequent attainment in national tests at age 11 and 14 and public examinations at age 16-18 (Smith, Fernandes, & Strand, 2001). According to data provided by nferNelson, most children sit the CAT-3 test in year 7 (age 11-12 years) and around 20% of all children will have CAT-3 tests in both year 7, and year 9 (age 13-14 years) (S. Strand, personal communication, September 2004). Many children in primary schools will take elements from CAT-3 rather than the full battery. The widespread use of the CAT-3 as a formal test of children’s intellectual abilities therefore provides a potential method of estimating children’s premorbid IQ. (Estimation of Premorbid Intellectual Abilities in Children)

I find the data ambiguous. The kids are only ages 11-12 here. As made clear in a figure which I pointed to previously, the White-Black African GCSE point gap decreases with age, from which we might infer that the IQ gap decreases with age.

I was also able to find a tiny sample (n=11) coming from a longitudinal study conducted in 2000. Age 11 verbal reasoning test scores were reported. These kids would have been born around 1983. As can be seen, the difference is .78 SD.

Frederickson and Petrides, 2005. Ethnic, gender, and socio-economic group differences in academic performance and secondary school selection: A longitudinal analysis

More data comes from wave 4 of the the nationally representative Millennium Cohort Study. The kids were tested in 2008 with the British Ability Scale. The children in this wave of the study are 7. The first column shows the gQ score, the second column shows the standard error, and the last shows the sample sizes. The Black-White difference, here, is a mere .33 SD. For comparison, Flynn and Dickens (2005) give an age 7 US difference of .5 SD.

I was able to find some UK SAT data based on year 13 (age 17) students. The kids took the tests in 2006:

Source: Kirkup, et al. (2007). Use of an Aptitude Test in University Entrance – A Validity Study Relationships between SAT® scores, attainment measures and background variables

What’s noticeable (Table 5.5 page 30) is that the SAT and GSCE score gaps match; we might infer then that since as of 2010 there is little GSCE gap, there would be little SAT gap. But the sample sizes are small here and probably unrepresentative, so it’s difficult to make much of this.
What’s needed then are CAT scores for adults. And the only ones which I found, dating from 2000, show such outlandishly high gaps, that they are hardly credible indexes of 2nd generation adult Black performance. My interpretation would be that these represent the scores of mostly first generation immigrant Blacks, which evidences how unselected Black immigrants are — a point which I was making before:

Source: Evers, te Nijenhuis, van der Flier (2005). Ethnic Bias and Fairness in Personal Selection: Evidence and Consequences pg. 309.)

The magnitude of these gaps do more or less match with those found based on Situational Judgment tests (STTs). With SJTs, test-takers are presented with realistic scenarios and asked to identify the appropriate response. These tests are found to show less mean ethnic/racial differences than traditional cognitive ability tests. (See: Whetzel, et al., 2008. Differences in Situational Judgment Test Performance: A Meta-Analysis.)

Source: Dewburry et al. Situational judgment tests and adverse impact in the UK: A large sample study

Some other data comes from a decade ago:

Source: Baron et al. (2005). Chapter 6: Ethnic group differences and measuring cognitive ability. International Review of Industrial and Organizational Psychology.

You will notice here that the gaps are only 0.5 SD; see also table 6.2. These samples are likely unreliable as the sizes are so minute.

A commenter pointed me to UKCAT annual report scores; the UKCAT is a dental and medical school entrance exam. The test is said to be a measure of aptitude and not knowledge (UKCAT Annual Report, 2007. pg. 2). It measures Verbal Reasoning (VR), Quantitative Reasoning (QR), Abstract Reasoning (AR), and Decision Analysis (DA). I transformed the total scores into UKCATIQ scores, normed on a White mean of 100 with standard deviations of 15. The year, sample size, and scores are listed:

Source: UKCAT Annual Report 2006; UKCAT Annual Report 2007; UKCAT Annual Report 2008; UKCAT Annual Report 2009/2010

It can be seen that there are consistent score differences. On these exams, Blacks score approximately 1 SD below Whites. Medical school applicants are not representative of the population at large, though, so it’s not clear how much analytic leverage this data gives us.

Other medical tests, though, do show similar differences. Here are the results from a recent pilot study of the Clinical Problem Solving Test — with higher rank scores representing worse results:

Dacre, et al., 2008. Clinical Problem Solving Test Pilot Project Report.

I was able to find LNAT test results from 2005 and 2009. The LNAT is the UK law school test. I transformed the total scores into LNATIQ scores, normed on a White mean of 100 with standard deviations of 15. Standard deviations were not provided, but the data allowed for their calculation. I calculated them for the total sample. The White SDs are lower, so the actual standardized difference between Blacks and Whites, based on the pooled White-Black SD, is higher than shown below. The first table below lists the results in detail for the 2008-2009 cycle; the second summarizes the results from 2005-2009.

LNAT: National Admissions test for Law. 2010. Analysis of LNAT results 2008-9 by gender, ethnicity, school and parental occupation. Accessed February 2012.

This data agrees with the Bar rankings. The qualification rank differences comes out to between 0.5 and 1 SD.

Sauboorah, 2011. An analysis of full-time students enrolled on the 2009/10 BVC See also: Dewberry, 2001. Performance disparities between whites and ethnic minorities: Real diVerences or assessment bias?

I did find some data on university attainment. Averaging across degree classes, Whites obtain approximately 0.5 standard deviations higher degree classes than Blacks. But it will be noticed, based on the Chinese sample, that there doesn’t seem to be a horribly good association between IQ differences and attainment differences:

Source: Richardson (2008). The attainment of ethnic minority students in UK higher education. See also: Richardson, 2010. Widening participation without widening attainment: The case of ethnic minority students

Overal, to my mind, the data is ambiguous. What is noticeable is that to the extent the CAT data captures the UK Black-White difference, the gap has greatly narrowing in the last couple of decades. Compare here. Based on the data Lynn provided I calculated a 0.9 SD difference. So the gap possibly narrowed 0.4 SD. This is rather amazing since, undoubtably Black immigrants to the UK have become much less selected, as the government now virtually sweeps African Blacks out of refugee camps into the UK.

When I get a chance, I will look into UK immigrant selection.

Is (global) “race realism” still tenable?

I’ll note that I put up one the the strongest defenses of a genetic hypothesis, period. I went beyond even academics such as Rushton and Lynn and cleverly re-analyzed decades old studies using contemporary genetic findings. See, for example, my updated versions of “Witty and Jenkins (1936)” and “Scarr et al. (1977).” Moreover, I added new data to that decades old; see for example Blacks, IQ, and Color in the NLSY97 and “It Could be Culture, part I (The NAEP Black-Mixed-White gap).” Few places on the web will you find a more extensive defense of “race”, debunking of race debunking, defense of the genetic racial hypothesis, defense of within population hereditatianism, and so on. As I spend an undue amount of time on this issue, I write the following with deep disatisfaction…

Before attempting to explain the following, consider:

(1) The correlation between GCSE and g is substantial. To quote from Deary et al. 2006:

“This 5-year prospective longitudinal study of 70,000+ English children examined the association between psychometric intelligence at age 11 years and educational achievement in national examinations in 25 academic subjects at age 16. The correlation between a latent intelligence trait (Spearman’s g from CAT2E) and a latent trait of educational achievement (GCSE scores) was 0.81. General intelligence contributed to success on all 25 subjects. Variance accounted for ranged from 58.6% in Mathematics and 48% in English to 18.1% in Art and Design.” (Intelligence and educational achievement.)

Here was the 2004 relation between Cognitive ability tests and GCSE performance:

(source: http://www.gl-assessment.co.uk/education/resources/cat3/cat3.asp)

(Yes, I’m aware of the data reported by Lynn (2008). I discussed it here “The General Mental Ability (GMA) of Black British.” I most likely know more about this issue than you so don’t assume otherwise.)

(2a) African Immigrants to the UK are only so immigrant selected. Here’s a pick from “Is the brain drain good for Africa?”:

Generally, it is rather unlikely that Black African migrants represent more than the upper third of the African phenotypic g distribution (i.e., that they are more that 1.1 SD selected for g — or, to put it otherwise, that they fall, on average, above the 86th percentile.

A more reasonable scenario, to my mind, is that they represent no more than the 70th percentile of the g distribution or are no more than 0.55 SD above the phenotypic mean.

(2b) For a trait like g, with a typical narrow heritability of 0.6, children will regress 40% towards their parental population’s mean.

(2c) To put (2b) another way, parents need to be 1.7 standard deviation units selected per every 1 standard deviation units that their children are selected.

(2d) To put (2c) and (2a) in context, if we are dealing with large sample sizes, we can roughly estimate the genetic difference between European Whites and African/other Blacks as the difference between European Whites and 2nd+ generation Blacks in Europe minus 0.6 times our estimate of immigrant selectivity.

(3) The sample sizes are large. As of 2009/2010, Blacks represent 5% of the UK Age 16 school population. In comparison, Chinese, who do exceedingly well, only represent .4%. You can compare the Black sample size here (>24,000) to the summed sample size for IQ tests over a 40 year period reported by Lynn (2008) (>16,000).

(4) Academic Hereditarians agree that immigrant performance is a tests of the hereditarian hypothesis. To quote Lynn (2010):

The evolutionary theory does however predict that when different races occupy approximately similar environments, such as for instance in the United States, Britain and the Netherlands, the intelligence differences will remain. This prediction has been examined in twenty three societies worldwide in Lynn (2008) and has been confirmed in every case. If a multiracial society is found where these race differences in intelligence are absent, the evolutionary and genetic theory of these differences would be falsified. Those who maintain that there are no genetic differences in intelligence between the races are urged to attempt this task. (Consistency of race differences in intelligence over millennia: A comment on Wicherts, Borsboom and Dolan)

To quote Greg Cochran (2011):

As some of you already know, Henry and I have put forth the hypothesis that the observed high intellectual achievement of Ashkenazi Jews is a result of natural selection for intelligence over the Middle Ages. We think there’s a pretty good case. One important supporting fact is that high Ashkenazi intelligence shows up everywhere they live. You see it in Russia, the US, Latin America, Israel, etc. It doesn’t spring from a single cultural milieu: you saw it in Jewish kids raised in turn-of-the-century Vienna, in Israeli kibbutzes, in Bronx tenements, and in Stalinist Russia. It’s not a consequence of Talmudic study – you see the same results in religious and irreligious people of Ashkenazi descent….

…As Neil Risch forcefully put it, in an interview with Karen Kaplan on our paper about Ashkenazi Jews, “What are their theories about those on the opposite end of the spectrum? Do they have genetic theories about why Latinos and African Americans perform worse academically?” A truly perspicacious question – to ask it is to answer it. (Risch’s Conjecture).

Now, the findings needing explanation:

This is for 16 year olds; I included gender as a reference; since no g differences in gender were found in Deary’s study, the Male-Female difference is an index of non-g influences:

For reference, here are the standardized GSCE score differences based on the Longitudinal Study of Young People in England. Under KS2 is listed the average age 14 test score gaps (year 2004); under KS4 is listed the average age 16 point score gaps (year 2006). The calculation of point scores is described here: http://www.education.gov.uk/performancetables/schools_04/sec3b.shtml Value added technical information.

The difference of interest is the age 16 Black-African White gap, which is about 0.10 SD or virtually nonexistent.

Convergent evidence supports the non-existence of a gap. See: Strand and Lindsay, 2009. Ethnic disproportionality in special education: Evidence from an English population study.

Compare with the prediction of Lynn (2008): “Mental retardation is also partly the tail end of the normal distribution of intelligence and the incidence of this would be expected to be greater among the ethnic minorities because these have lower mean IQ and hence a greater proportion at the low end of the distribution.”

It seems that, in the UK, White Liberals closed the Black-White gap:

I will shortly contact a couple of UK academics and request CAT3 scores by ethnicity on the chance that the GCSE scores might not accurately represent g scores, for the populations in question. After I have certainty on this issue, assuming agreement between the two, I will discuss and evaluate possible modified versions of race realism (e.g., non-additive genetic models such as a race realist version of the Flynn and Dickens (2001) model, models which distinguish between local and global populations, etc.).

In the mean time, I will be happy to hear HBDish explanations for the above which take into consideration points 1-4. (If you comment please specify the magnitude of the genetic Black African-White European racial gap that you think is tenable.)

(The good news is that, to the extent the g gap can be closed, the West as an economic entity will not be doomed by massive Black immigration and “integration.” The bad news is that the West as an ethnic entity now surely is. From a philosophical point of view, it appears that science in the mode of “scientific racism” can not save White people. As I discussed a while back, Western science is so interwoven with Western philosophy, that the two are virtually inseparable:

Jung’s point here is important — in the West, “the real” was largely narrowly identified in terms of the rational and objective. In general, this applied not just to Western philosophy but also to Western spirituality and theology, which was one reason why the scientific revolution and the enlightenment had such a deleterious impact on the traditional Western world-views, and why they precipitated the radicalism that they did (Nihilism, positivism, philosophical Liberalism, biological nationalism, Marxism, etc.). Given the strong association, in the West, between the rational and objective and the philosophical, spiritual, and theological, reevaluations of the former radically affected the later, in a manner not comparable to the affects that equivalent reevaluations had in other cultures, often inducing systematic re-valuations and with them pervasive dysnomia. One can compare, for example, the impact that the scientific revolution had on Christianity to the impact it had on Hinduism; the later, though equally non-empirical, was never shaken in the degree that the former was. Hindus never experienced the angst that (European) Christians did over the conflict between science and religion, since, for Hindus, religion and science largely existed in different mental spaces. I would extend Jung’s point: Western man’s great silliness was his superficiality. I tangentially discussed this here, in Why the West Discovered the Modern World; in short, as Nietzsche noted, the very thing that led to the stellar rise of the West, underlies its undoing, not unlike the ring of Niblung and the fate of Gods of Asgard.

The cultural association between science and philosophy, specifically between the objective and subjective, is why White people, as and ethnic group, can be empirically disproved out of existence, in a way that no other group can. To put it another way, the existence of White people is contingent on the existence of biological racial difference, which is why many of us have invested so much energy in trying to establish the latter and establish it by showing differences in one of the supreme Western values*. Based on my analysis above, the support for existence of White people, then, is greatly weakened.)

*I, for one, have made it clear over the past 2 years that this was part of my agenda — I am — or was — an unapologetic scientific racialist, where that means using science to establish metascientific positions, such as the psychological importance of “race.” This type of activity is what more intellectually sophisticated antiracists — who also try to use science to establish metascientific positions, just in the reverse way — mean when they speak of “scientific racism.” I post the above — about “race realism” — because I am interested advancing intellectually defensible versions of “racialism.” If “race realism,” in this or that objective sense, is untenable, then defenses must be retuned.