IQ and Personality: What James Heckman Got Wrong

A few years ago James Heckman, together with some other economists, published a study arguing that “achievement tests” and “IQ tests” are different beasts: the former, they claim, are better predictors of criterion outcomes (such as grade point averages) and are more strongly influenced by personality differences than the latter. Like most of Heckman’s forays into psychometrics — he has been obsessed with trying to shoot down Bell Curve -type arguments ever since the book was released — the study leaves much to be desired. David Salkever has published a nifty reanalysis of Heckman and colleagues’ study, showing that their results stem from faulty imputation and a failure to take into account age effects. Continue reading

Alice Brues on Race

A reader asked if I might refer him to a cogent, while pithy, elaboration of the natural historian’s concept of race, an exposition which he might cite in future discussions. One of the most lucid articulations which I have encountered can be found in physical anthropologist Alice Brues’ (1913 –2007) book “People and Races” (1977/1990). Brues studied under Earnest Hooton, whose own concept of race was remarkably well articulated and coherent. In undergrad, she majored in philosophy (and psychology), a fact which might help account for the unusual lucidity of her discussion. In the seven pages of her first chapter, she says most of what needs to be said. And in the remaining chapters she makes the other necessary points. The first chapter is copied below both in PDF form and text. The discussion can be summarized as follows (with my notes added and paragraphs numbered). Continue reading

Socioeconomic Status and Heritability of IQ Redux

There’s a long-standing debate about if and how parental socioeconomic status moderates the heritability of IQ. Research has often but not always found that heritability is lower in low-SES families. See Turkheimer and Horn’s excellent review for details (although some of Turkheimer’s own research on this is less than convincing).

Robert Kirkpatrick and colleagues have conducted what may be the best study on the question so far. They use a big Minnesota sample, comprising about about 2500 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings, and investigate if SES moderates either genetic or environmental determinants of IQ. Continue reading

Bias in Measures of Implicit Racial Bias

It is claimed that implicit association tests, or IATs, reveal unconscious biases against racial and ethnic minorities and other stigmatized groups. The tests are simple and their results appear to be straightforward to interpret: if you are quicker to associate positive words (or other positive stimuli) with the non-stigmatized group (e.g., whites) and quicker to associate negative words with the stigmatized group (e.g., blacks), you have an implicit preference for the former and against the latter. Moreover, it has been shown that IAT scores are (modestly) related to arguably discriminatory behaviors. Given that the IAT scores of most people suggest that they are biased against stigmatized groups, it has been claimed that implicit biases explain discriminatory behaviors in the real world.

Hart Blanton, a long-term critic of various theoretical and methodological absurdities in the IAT paradigm, has written, with some colleagues, a paper challenging a key assumption of the IAT. Re-analyzing several published implicit bias studies, they found that the standard IAT scoring procedure will typically label as implicitly biased people whose observed behavior is neutral and unbiased. IAT researchers assume that individuals who associate positive and negative IAT stimuli with different groups with equal ease are unbiased, but the research by Blanton et al. suggests that such individuals tend to be biased in favor of the stigmatized group. In other words, the zero point of the IAT scale is not associated with behavioral neutrality.

The results of Blanton et al. are pretty straightforward, but not necessarily easy to understand, so I’ll try to clarify them a bit. Continue reading

Nature of Race (Published)

Below is an expanded and much improved rewrite of a draft which I had posted last year — improved thanks to the helpful commentary of Davide Piffer, Emil Kirkegaard, Kevin MacDonald, Peter Frost, Meng Hu, and others. As for the work, the intent was to  clarify the concept of race, understood from the perspective of natural history, so to render the term which describes it inessential. It is hoped that the piece will also clarify the purpose of this blog, the focus of which is human varieties, of which races as constant varieties and natural divisions are but a subtype.

Fuerst, J. (2015). The Nature of Race: the Genealogy of the Concept and the Biological Construct’s Contemporaneous Utility. Open Behavioral Genetics.

Abstract: Racial constructionists, anti-naturalists, and anti-realists have challenged users of the biological race concept to provide and defend, from the perspective of biology, biological philosophy, and ethics, a biologically informed concept of race. In this paper, an onto-epistemology of biology is developed. What it is, by this, to be “biological real” and “biologically meaningful” and to represent a “biological natural division” is explained. Early 18th century race concepts are discussed in detail and are shown to be both sensible and not greatly dissimilar to modern concepts. A general biological race concept (GBRC) is developed. It is explained what the GBRC does and does not entail and how this concept unifies the plethora of specific ones, past and present. Other race concepts as developed in the philosophical literature are discussed in relation to the GBRC. The sense in which races are both real and natural is explained. Racial essentialism of the relational sort is shown to be coherent. Next, the GBRC is discussed in relation to anthropological discourse. Traditional human racial classifications are defended from common criticisms: historical incoherence, arbitrariness, cluster discordance, etc. Whether or not these traditional human races could qualify as taxa subspecies — or even species — is considered. It is argued that they could qualify as taxa subspecies by liberal readings of conventional standards. Further, it is pointed out that some species concepts potentially allow certain human populations to be designated as species. It is explained why, by conventional population genetic and statistical standards, genetic differences between major human racial groups are at least moderate. Behavioral genetic differences associated with human races are discussed in general and in specific. The matter of race differences in cognitive ability is briefly considered. Finally, the race concept is defended from various criticisms. First, logical and empirical critiques are dissected. These include: biological scientific, sociological, ontological, onto-epistemological, semantic, and teleological arguments. None are found to have any merit. Second, moral-based arguments are investigated in context to a general ethical frame and are counter-critiqued. Racial inequality, racial nepotism, and the “Racial Worldview” are discussed. What is dubbed the Anti-Racial Worldview is rejected on both empirical and moral grounds. Finally, an area of future investigation – the politics of the destruction of the race concept – is pointed to.

Keywords: natural division, race, biology

Contents

Introduction………………………………………..………………………………………………………………………………………..4

I. Biology – A Philosophical Clarification…………………………………………..………………………………..……..5
I-A. Existing Views: Confusions Abound
I-B. Biological Concepts in General
I-C. The Validity of Biological Concepts
I-D. Biological Kinds
I-E. Natural Biological Divisions
I-F. Races as Natural Biological Divisions
I-G. The Intraspecific Natural Division as Type of Biological Variation
I-H. The Natural Division as a Taxonomic Unit
I-I. Natural Divisions and Intraspecific Variation with Regards to the Subspecies Category
I-J. Biologically Meaningful Race Concepts
I-K. Biological Reality
I-L. Biologically Important Differences
I-M. Concepts of Biological Race

II. The General Biological Race Concept………………………………………………………..………………..……..25
II-A. The Genealogy of the Concept
II-B. Semantic Complexities and the Evolution of the Race Concept
II-C. Biological Race
II-D. What the Core Biological Race Concept Does Not represent
II-E. Races, Clines, Clusters?
II-F. Clarification on the Meaning of “Arbitrary” and “Objective” in Context to Natural Divisions
II-G. Regarding Different Definitions of Biological Race: What Races Need Not Be
II-H. Genomic-Genealogical Complications
II-I. Estimated Genomic Similarity: Some Ambiguity
II-J. Race: Mixed and Undifferentiated
II-K. Essential and Cluster classes; Fuzzy and Discrete Sets
II-L. Sociological Clarifications

III. The Ontology of Biological Race……………………………………………….……………………………………..……62
III-A. Other Defenses of Biological Race
III-B. Biological Races and Biological Reality
III-C. Thin Biological Racial Essentialism

IV. The Races of Man……………………………………………………………………………………………………………………81
IV-A. A Very Brief Historical Review
IV-B. Human Biological Races and Scientific Consensus
IV-C. Racial Classifications and Biological Race Concepts
IV-D. Traditional human Races
IV-E. THRs and Biologically Objective Races
IV-F. THRs and Migration, Intermixing, and Ancient Admixture
IV-G. THRs and Cluster Discordance
IV-H. THRs and Taxonomy
IV-I. THRs and Subspecies
IV-J. Are There Human Species?
IV-K. “Significant” Racial Differences
IV-L. Human Biodiversity (HBD) and Society
IV-M. Race and Intelligence

V. Critique of Anti-Biological Race Arguments………………………………….…………………………………….126
V-A. Anti-Biological Arguments
V-B. Biological Scientific Arguments
V-C. Sociological Arguments
V-D. Unnaturalistic Arguments and the Numbers Game
V-E. Onto-epistemology Arguments
V-F. Semantic Arguments
V-G. No-True-Race Arguments
V-H. Teleological Argument: The Future of Race
V.I. Can a Good Argument be Made Against (the) Race (concept)?

VI. A Troublesome Inheritance?…………………………………………………………………………………………………148
VI-A. The Social Destruction of a Biological Reality
VI-B. A Not So New Morality for Race
VI-C. The Moral Critiques: Arguments based on Outcome Differences
VI-D. The Moral Critiques: Arguments based on Racial Classification and Identity
VI-E. The Moral Critiques: Arguments based on Racial Favoritism
VI-F. The Moral Critiques: Arguments based on the “Racial Worldview”

Conclusion…………………………………………………………………………………………………………….……………………169

References…………………………………………………………………………………………………………………………………170

 

NofRpic

Regional Admixture and Aptitude in Colombia

Emil and I set out to determine if regional variation in racial ancestry could (statistically) explain regional variation in cognitive ability. To keep things simple, we have limited focus to the Americas, which contain primarily trihybrid populations and for which there is a decent amount of admixture data. The results so far align with predictions.  Both across nations and across regions within the U.S., Brazil, and Mexico, European ancestry positively correlates with regional-level cognitive ability. In contrast, both African and Amerindian ancestry negatively so correlates. The broader importance of the project is that it involves the construction of an expansive data set which allows for the statistical controlling of continental lineage and associated factors (genes + deep culture), ones which presently confound many analyses. This data set will hopefully allow one to uncover regional and national level factors which are not tangled with ancestry. They must exist. For example, we find that regional levels of European ancestry are associated with better outcomes in both the U.S. and Brazil but also that there is a substantial between nation effect that can not be explained by factors correlated with continental ancestry.

Nationsandregions

Here, I will discuss a new analysis involving Colombia. Colombia is marked by extensive spatial variation in Colombia2ancestry.  The admixture map on the left copied from Ruiz-Linares et al. (2014) and the ethnic map on the right taken from Rodriguez-Palau et al. (2007) roughly capture the lay of the land. African admixture is concentrated along the Pacific and Caribbean coast, European admixture is highest in the north and central interior region, and Amerindian admixture is concentrated in the east and south. This ancestral variation allows for a test of our general model.

 

I computed the variables as follows:

 

AdmixtureColombia1:  Estimating regional admixture for Colombia’s 32 departments plus the capital was not without difficulty since existent studies provide admixture data for only half of the departments. Problematically, specific estimates for the eastern and southeastern departments, which are reported to have high Amerindian components were not available. Nonetheless, we were able to construct three sets of admixture estimates. First, 18 departmental + capital estimates were taken from Salzano and Sans’ (2014) compilation. The ancestry ratios from Salzano and Sans’ (2014) two main sources correlated at 0.9, so we felt that using the combined estimates was justified. Second, missing values were filled in based on regional values and based on Ruiz-Linares et al.’s (2014)  and Rodriguez-Palau et al.’s (2007) maps. For example, estimates for Caribbean-Pacific departments were averaged and used to fill in missing data for other departments in this region. In context to the U.S., this would be akin to filling in South Carolina values using the average of the Deep South ones. Third, admixture was estimated using ethnic identity data from the 2005 census in conjunction with average ethnoracial admixture percents as reported in all available studies. The ethnoracial admixture percents came out to as follows:

coladmix

The computation methods are detailed more precisely in the excel file.

Cognitive ability: For cognitive scores, the Colombian national SABER exam scores were used.  The average of the 2003 and 2005 grades 5 and 8 math and reading regional scores strongly correlated with the average of the 2012 and 2014 scores (about 0.85). The scores were on different metrics, moreover standard deviations were not available for the 2003 and 2005 scores (given the source used), so, in the end, the 2012 and 2014 average scores were employed.

Other variables: 2010 HDI scores were taken from Machado (2011). Ethnic identity percents were taken from the 2005 census. Population was taken from the census via Wikipedia.

Results:  I uploaded the excel file to facilitate future investigations. For the analyses reported below, in line with the general methods adopted for the meta-project, I excluded the capital and weighted by SQRT(population). Salzano and Sans’ (2014) admixture data showed only a weak negative correlation for Amerindian ancestry; this was because, as noted, data was missing for the most Amerindian parts of the country. When data was filled in, the association became significantly negative as predicted. It seems that the negative results are driven by the low scores in 5 districts (Amazonas, La Guajira, Guainía, Vaupés, and Vichada) all of which have high percents of self identifying indigenous and large reservations.

colregression1

The results immediately above were replicated using the ethnic-admixture data.

colreg2

Generally, European ancestry was non-trivially associated with cognitive ability (shown below) and with HDI (not shown). These results held regardless of which admixture variable was employed; they were largely driven by the strong negative association between regional outcomes and African ancestry.  It is interesting that regional Amerindian ancestry was not associated with regional ability in the case of Salzanploteuadmixo and Sans’ (2014) admixture estimates. While on the national level, Amerindian  ancestry negatively correlated with ability, as areas which were heavily populated by self-identifying Indigenous individuals did poorly, one might expect a more constant effect, one that would show up in Salzano and Sans’ (2014) restricted data set, which included only interior and coastal departments. The lack of association might have been due to the unreliability of the data, the specific samples analyzed, or the specific sampling of interior and coastal departments. Possibly, Amerindian ancestry is not negatively correlated with regional outcomes outside of largely indigenous regions. A determination of the matter will have to wait for the publication of more Colombian regional admixture data.

 

The Bell Curve, 20 years after

Or nearly so. I was planning to publish that blog article for the 31th December 2014. As you can see, I failed in this task, and didn’t finish in the right time. Anyway, I wrote this article, mainly because I am bothered that when people cite The Bell Curve the typical opponent responds with a link toward Wikipedia, specifically the part related to the “controversy” of The Bell Curve. It goes without saying that these persons did not read the books written in response to The Bell Curve. In fact, they have certainly read none of them. It is ridiculous to cite a book you didn’t read, but apparently, it does not bother many people, as I see.

For the 20 years of the book, I found appropriate to write a defense of the book. Or more precisely, a critical comment on the critics. I have decided to read carefully one of these books I can have access, and for what I have read here and there, it is probably the best book ever written against The Bell Curve. I know that Richard Lynn (1999) has already written a review before. But I wanted to go into the details. The title of the book I’m reviewing is :

Devlin, B. (1997). Intelligence, Genes and Success: Scientists Respond to the Bell Curve. Springer.

In fact, I have read that book some time ago, but didn’t find the need to read everything in detail. And I was unwilling to write a lengthy review. But I have changed my mind because of some nasty cowards.
Continue reading

Racial Ancestry in the Americas. Part 2: Cognitive Variation between Nations: Parasite Load, Climate, and Ancestry

Following up with a previous analysis, I examined the cognitive variation across the whole of the Americas using a newly constructed data set.  Files can be found here and here, with the latest versions provided on request.  The analysis was restricted to sovereign nations, not e.g., departments such as Martinique or territories such as the Virgin Islands.  Non-sovereign regions were excluded so to avoid an inter-nation x intra-national interaction and because international exam data was not available for these regions.  The following 35 countries were included:  Argentina, Antigua and Barbuda, Bahamas The, Belize, Bolivia, Brazil, Barbados, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, Guyana, Grenada, Honduras, Haiti, Jamaica, St. Kitts and Nevis, St. Lucia, Mexico, Nicaragua, Panama, Peru, Paraguay, El Salvador, Suriname, Trinidad and Tobago, Uruguay, United States, St. Vincent, Venezuela RB, and Canada. Eight regression analyses were run, using the following dependent variables:

  • (Skinrefl) Skin reflectance.
  • (AchQ) National Achievement Scores –  this was an updated set provided by Gerhard Meisenberg during October of 2014.
  • (NIQ) National IQ scores – these were based on Richard Lynn’s 2014 (work in progress) results and Jason Malloy’s 2013 to 2014 estimates, with adjustments.
  • (AHQ) 1880 to 1930 birth cohort age heaping scores — this is a measure of education/numeracy.
  • (logSciresearch) Log of scientific researchers from 2005 to 2012.
  • (logGDP) Average of 1990, 2000, and 2010 log of World Bank per capita GDP.
  • (Crimes) Violent Crime rates.
  • (HDI2012) 2012 Human Development Index scores.

The following independents were included:

  • (relativeEu) European Ancestry percent — the percent of European ancestry out of the percent of  European + Amerindian + African ancestry.  (For a discussion of this variable, refer here.)
  • (notUSCanada) Not US or Canada — whether the region was not US or Canada.
  • (logparasiteload) Log Parasite load — the log of the 2004 WHO parasite infections per 100,000 for each country.
  • (logColddemand) Log Cold demand — the log of Van de Vliert’s (2013) cold stress scores.
  • (PopUnder1million)  Population under 1 million — whether the country’s population was under one million.

Simple correlation analysis demonstrated that ancestry, cold weather, and parasite load intercorrelated.  This situation renders difficult the isolation of causal associations.  To illustrate, skin reflectance was set as a dependent with Eu ancestry, cold weather,  parasite load, population under 1 million, and not US and Canada as independents.  The correlation between Eu ancestry and skin reflectance is clearly mostly genetic in origin.  To the extent that the association between ancestry and skin reflectance is mediated by other variables, it is suggested that these variables co-vary with causal effects related to genes (and thus that controlling for them controls for ancestry related causal effects).  Regression results are shown in Table 1, below.  Generally, parasite load and cold weather seem to partially index ancestry effects.  Parasite load is a particularly problematic “environmental factor” because it significantly correlates with STD and HIV rates (at 0.47).  Yet the spread of HIV throughout the Americas, in the ’70s and ’80s, was subsequent to the origin of cognitive ability differences, which, in the form of national age heaping rates, were already present in the 1800s.  Thus, STD and HIV rates and with them parasite load are, to some extent, consequent of cognitive ability differences.

Results will not be discussed in detail.  The data file is made freely available; readers can run the analyses as desired.   Generally, European ancestry was a robust predictor of lower rates of violent crime, scientific activity, and achievement scores, and achievement plus National IQ scores.  (For national IQ alone, in the final model, none of the predictors were significant; this was because the NIQ sample had many missing values.)   In contrast to cognitive ability and the other mentioned indexes, European ancestry was generally not significantly associated with GDP or Human developmental indexes.  The results for National achievement scores are shown in Table 2, below; a regression plot is shown in figure 1.

Table 1.  Regression Results for Skin reflectance

reg1skinrefl

Table 2.  Regression Results for ACHQ2014

ACH2014

Figure 1.  National Achievement Scores by % European Ancestry for Sovereign American Nations

ACH2014AncestryAmer