Genetic and Environmental Determinants of IQ in Black, White, and Hispanic Americans: A Meta-analysis and New Analysis

The PDF and data file are available at Open Behavioral Genetics. You can also read the article below the cut.

Published:  September 15, 2014

John Fuerst [1]

Dalliard

Abstract:  The authors conducted a meta-analysis of interactions between behavioral genetic variance components (ACE) and race/ethnicity for cognitive ability. The differences between the variance components for Black and White Americans were small, despite the large average test score differences. More substantial differences were found between Hispanics and non-Hispanic Whites, though results were based on only two studies. A biometric re-analysis of the CNLSY survey was then conducted and new meta-analytic results were provided. Results were discussed in light of the bio-ecological model which proposes that when the scores of subgroups are environmentally depressed, heritabilities will be likewise.

Keywords:  Race, Ethnicity, Heritability, IQ, Environment, ACE model, bio-ecological model

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The Elusive X-Factor, or Why Jonathan Kaplan Is Wrong about Race and IQ

Philosopher Jonathan Kaplan recently published an article called Race, IQ, and the search for statistical signals associated with so-called “X”-factors: environments, racism, and the “hereditarian hypothesis,” which can downloaded here. His thesis is that the black-white IQ gap could plausibly be due to racism and what he calls racialized environments. He presents simulations in support of this argument. He also argues that “given the actual state of the world there is no way to generate any reasonably strong evidence in favor of the hereditarian hypothesis.”

I have written a detailed critique of his claims. In short, he is wrong. Here’s the abstract of my article:

Jonathan Michael Kaplan recently published a challenge to the hereditarian account of the IQ gap between whites and blacks in the United States (Kaplan, 2014). He argues that racism and “racialized environments” constitute race-specific “X-factors” that could plausibly cause the gap, using simulations to support this contention. I show that Kaplan’s model suffers from vagueness and implausibilities that render it an unpromising approach to explaining the gap, while his simulations are misspecified and provide no support for his model. I describe the proper methodology for testing for X-factors, and conclude that Kaplan’s X-factors would almost certainly already have been discovered if they did in fact exist. I also argue that the hereditarian position is well-supported, and, importantly, is amenable to a definitive empirical test.

The PDF is available at Open Differential Psychology. You can also read the article below the cut.

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Racial differences in the long-term trend NAEP scores (1975/78-2012)

I analyze the LTT NAEP achievement scores, a public data set available at NCES. In general, minority-majority ethnic groups show a secular decline in d gap, for both math and reading tests, and this occurs at all ages of assessment (9, 13, 17), and at all percentile levels. Some exceptions are noteworthy. There is no secular gain at age 17 among whites, and no meaningful decline in black-white difference for the NAEP math at ages 13 and 17. Within each year of assessment, no evidence is provided for the hypothesis that the racial gaps (notably, the black-white gap) widen with age after entering schools. There was simply no trend at all.
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HVGIQ: Laos

Laos is the least populated country in Indochina; home to nearly 7 million people. It is a single-party Marxist state, and ranks close to Cambodia and Burma on the tail end of human development indices. Ethnic Lao are about 55% of the population and inhabit the lowland regions. Numerous ethnic minorities inhabit more elevated regions, including the Hmong, who are about 8% of the population.

In this post I review one small study with intelligence test data for the nation of Laos. I also summarize over a dozen studies with intelligence and achievement test scores for Laotians living in the United States. A majority of these studies are for Hmong Americans.

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Advice for Wikipedia editors

Since the beginning of the year, among readers of HBD-related blogs there’s been an increased interest in trying to improve articles related to race and intelligence at Wikipedia. The appeal of this is easy to understand, since very few books or articles written for a popular audience accurately present the scientific consensus about this topic. (Some pop-science books about it, such as The Mismeasure of Man, are infamous for the amount of misrepresentation they involve.) On the other hand, while peer-reviewed journals and academic textbooks often do present this consensus, these generally aren’t accessible to lay people. Wikipedia is the most commonly-used source of information in the world, so if it can accurately represent how this topic is presented in the professional psychology literature, it’s providing a service that’s provided almost nowhere else.

However, there’s a problem. Many of these new editors don’t realize that contributing to any topic at Wikipedia requires more than just knowledge about the topic itself–it also requires an understanding of how to conduct oneself there. This is especially true in articles on controversial topics, and race and intelligence is the ninth most controversial topic at Wikipedia. Over the past few months, several of these editors have come to me for advice about how to make a positive difference in this area, so I’ve decided to write up some of my advice for them in a blog post here.

One point needs to stated before anything else: The most useful thing anyone can do on these articles is keep watch over them, and undo vandalism when it happens. The largest problem with most of the articles is that they aren’t being watched by anyone who cares about them. This means that people can remove chunks of sourced material without giving a reason, or add material without a source, and the changes often won’t be undone.
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HVGIQ: Thailand

Thailand has a population of over 64 million people, which is comparable to the United Kingdom or France. It is the world’s 21st most populous country.

IQ and the Wealth of Nations (2002) and IQ and Global Inequality (2006) both assign Thailand an IQ of 91 based on one clinical trial from 1989. Lynn and Vanhanen (2012, p. 417) add two more studies that push their estimate down to 88. Some of their numbers are reported inaccurately and these books overlook larger, higher quality, and more recent intelligence test studies for this nation. In particular—as I noted on Gene Expression almost a decade ago—the government of Thailand has implemented broad national IQ surveys, which have been reported in relation to U.S. and U.K. test norms.

In this post I review almost 50 studies of intelligence and scholastic achievement for the nation of Thailand. Many representative studies since the 1990s give conflicting results, making a solid estimate of Thailand’s IQ a difficult task.
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