The Cayman Islands, a British Overseas Territory, boasts one of the world’s highest standards of living and per capita GDP, largely due to its status as a major tax haven. Its average Human Development Index (HDI) from 2010, 2015, and 2020 was 0.876 (Economic and Statistics Office, 2021), compared to the United Kingdom’s 0.919 over the same period—both rated as very high human development. The 2021 census recorded a population of 68,811, with 53% identified as Caymanian residents, of whom only 62% were born on the island. These demographic shifts, detailed in Figure 1, complicate efforts to estimate ancestry proportions.
Although my colleagues are international, their research predominantly focuses on differences within the USA, a tendency I find perplexing. Years ago, at an LCI conference, a British colleague asserted that further research on ethnic or racial differences was unnecessary, claiming the matter was settled. Yet, within a year, he contacted me seeking data on the performance of various ethnic groups in the UK. Similarly, a French colleague, whose work almost exclusively examines differences in the USA, argued that such data was unavailable in France. However, after just ten minutes of searching, I located several French government reports detailing the performance of first- and second-generation immigrants by region of origin. Evidently, he didn’t try too hard. In my view, a logical approach, if one were to pursue this topic seriously, would involve first collecting a broad international dataset—potentially requiring effort such as submitting freedom of information requests—then identifying patterns, and finally hypothesizing about possible causes. After all, the USA is not the world, and we should not assume it reflects global trends. The lack of such comprehensive data is why I remain largely agnostic about the existence of worldwide race differences in cognitive ability, and even more so about their causes
. . .
France governs three overseas departments in the Americas—French Guiana, Guadeloupe, and Martinique—along with three overseas American collectivities: Saint Barthélemy (St. Barth), Saint Martin, and Saint Pierre and Miquelon. The populations of these territories display a rich diversity of ancestries, making them an interesting case study.
Saint Pierre and Miquelon, located off the coast of Canada, has a population of approximately 5,819 and is the most European-influenced of France’s overseas territories. Its residents are primarily descendants of French settlers from Normandy, Brittany, and other regions, supplemented by recent migrants from metropolitan France. Saint Barthélemy, a small Caribbean island that separated from Guadeloupe in 2007, has a population of around 10,000. Although France does not officially collect ethnic or racial data, visual observations of children in local primary schools and at festivals suggest the population is roughly 80% of European ancestry (mostly French), 15% of African ancestry, and 5% of other origins. This aligns with historical settlement records, which indicate a majority of French descent.
Jason Malloy previously wrote lengthy blog posts summarizing IQ and admixture data for both Puerto Rico and the U.S. Virgin Islands. The achievement data, which is the focus of this series of posts, was outdated. Here, we provide an update.
Puerto Rico
Puerto Rico is a predominantly Spanish-speaking U.S. territory. Its residents have full citizenship—allowing free movement to the mainland. Currently, more Puerto Ricans live on the mainland (5.8 million in 2023) than on the island (3.2 million). Based on the average of 16 samples, individuals on the island of Puerto Rico have an average European, African, and Amerindian ancestry of 66.67%, 19.80%, and 13.53%, respectively. The samples are summarized in Table 1 below.
According to Matthews, Tabery, & Turkheimer (2025), our Admixture in the Americas project is “abhorrent” because nothing good could come from investigating “alarming hypotheses regarding the genomic basis of differences in cognitive abilities between racial and ethnic groups.” While Eric Turkheimer’s position is predictable given his well-known motivations, it is surprising to see philosophers like James Tabery also resorting to sloppy, moralistic reasoning. Notably, in the two Admixture in the Americas papers cited by Matthews et al. (2024), we explicitly stated that our research does not test a genetic model. Instead, drawing on Putterman and Weil’s Post-1500 Population Flows and the Long-Run Determinants of Economic Growth and Inequality and a large body of “deep roots” economic literature, we examined a genealogical model, recognizing that various factors could explain the intergenerational transmission of differences. In The Genealogy of Differences (2016), responding to a critique from Ibarra (2016), we elaborated:
According to [our model], intergenerationally transmitted factors such as genes, epigenes and culture code for individual-level traits related to individuals’ ability to acquire knowledge and to develop better societies (e.g., a cultural appreciation of education and learning affecting the development of cognitive abilities). By this model, BGA acts as a crude index of the lines of descent along which the individual-level traits, the true causal factors, are passed… to deny a priori the possibility of our model, Ibarra equates an intergenerational model with a behavioral genetic one and then, incredibly, adopts a Blank Slate position. This is, of course, a doubly absurd argument. First, we stipulated that our model was an intergenerational, or genealogical, transmission, and not necessarily a behavioral genetic one. We made that point in three separate sections of the [original] paper.
Emil Kirkegaard requested an update to the Admixture in the Americas analyses, a complex task requiring, among other things, the computation of new national cognitive scores for countries and territories in the Americas. Three existing datasets are available for this purpose:
- Antilok et al.’s Harmonized Test Score (HTS) Dataset: Used to create the World Bank’s Harmonized Test Scores (HTS), this dataset covers all but three sovereign countries—Barbados, the Bahamas, and Suriname. Scores were averaged over 5-year intervals from 2000 to 2020, except for Bolivia, where data from 1995–2000 was used.
- Becker’s 2023 National IQ Scores: These measure a construct distinct from achievement scores and rely primarily on convenience samples.
- GMAT-Based Scores: Previously utilized in an earlier paper, these scores have been updated. They cover 2000–2020 data, except for small territories (e.g., Aruba, British Virgin Islands, Guadeloupe, Martinique, Montserrat, and Netherlands Antilles), where 1980s–2020 data was included due to limited 2000–2020 sample sizes and the absence of a clear secular trend.
Academic papers’ abstracts are sometimes manipulated to display what is seemingly a good result. Alternatively, abstract conclusions are affected by faulty statistical analyses. The large profits in online publishing, especially the open-access (OA) type, are largely (but unfairly) criticized, with endless calls for regulation. In reality, the problem of monopolistic prices and quasi-monopolistic status of the most prestigious online publishers is not due to lack of regulation, but due to a combination of copyright law, OA mandates, and moral hazard driven by subsidies.
The Classical Twin Design (CTD) has always been criticized for being oversimplistic, and consistently overestimating heritability estimates due to not accounting for GxE, GxG, rGE and equal environmental effects. It is almost never mentioned the bias is not systematic. The criticism largely exaggerates the flaws of the CTD, often misleadingly so, and apparently cherry-picking their evidence whenever large discrepancies in heritabilities are reported due to ignoring key assumptions inherent to the twin design. This article will show why the CTD and its extensions are robust methods, but with a strong focus on the Equal Environment Assumption (EEA).
The classical twin design withstood past criticisms, duo to employing a large variety of methods to test the key assumptions (Plomin & Bergeman, 1991; Andrew et al., 2001; Johnson et al., 2002; Christensen et al., 2006; Kendler & Prescott, 2006, ch. 6; Segal & Johnson, 2009; Plomin et al., 2013, ch. 6 & 12 & 17), and will likely withstand current ones (Tarnoki et al., 2022) in spite of some recent developments (e.g., Sunde et al., 2024) to improve the standard ACE models used to decompose genetic (h²) and shared and non-shared environmental (c² and e²) variances.
A recent article by Samorodnitsky and co-authored by two renowned censorship champions, namely, Kevin Bird and Rebecca Sear, requests that all published papers that have ever used Lynn & Vanhanen (2006) national IQs (or subsequent, revised version, up to Becker & Lynn, 2019) to be retracted. They ignore a plethora of evidence suggesting that L&V or B&L IQ data are robust, despite the questionable data quality regarding lower-IQ countries. This is a case of non-classical measurement error. But many other variables commonly used in either economics or psychology often display a similar form of non-classical measurement error, and sometimes display quite dramatic biases in one or both tails of the distribution due to misreport bias. The right question is to ask how the biases can be corrected, not whether the research and their authors should be cancelled. Econometricians proposed a wide variety of techniques to deal with non-classical measurement error. In fact national IQ researchers already employed some robustness analyses. This article will dispel the logical fallacies used to negate IQ research.
SECTIONS
Sackett et al. (2022) recently questioned prior meta-analytic conclusions about the high IQ validity since the studies by Schmidt & Hunter decades ago. The crux of the issue is complex, but while the debate regarding range restriction correction is not (at least not completely) resolved yet, one thing is certain. The validity depends on the measure of job performance that is used in the meta-analysis. Maybe the importance of IQ has declined in recent years but the debate is not settled yet.
(updated: August 2nd 2024)
CONTENT
1. The groundbreaking study
2. The controversy
3. The choice of criterion (dependent) variable matters
Borghans et al. (2016) analyze 4 datasets with diverse measures of IQ and, shockingly, concluded that the impact of IQ on social outcomes is weak compared to personality measures, despite what the earlier reviews and meta-analyses showed (Gottfredson, 1997; Poropat, 2009; Schmidt & Hunter, 2004). Indeed, as reviewed prior, most studies found that personality measures generally have weak relationship with outcomes once IQ is accounted for. Yet their work has not been subjected to critical examination, just various uninteresting comments (Ganzach & Zisman, 2022; Golsteyn et al., 2022; Stankov, 2023) and replication failures (Zisman & Ganzach, 2022).
