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We utilised data from the OkCupid dating site to study preferences for body parts in attraction judgements. We found that most people (71%) have a stated preference for faces, with nonEuropeans finding other parts more important: lower parts (“butt/legs”; 8%), chest (“chest/breasts”; 3%), and Other (18%). We regressed these preferences on likely causal variables. We found that slower life history speed, female sex, and higher intelligence predict preference for faces and negatively for buttocks/legs/chest, replicating previous research. We further found that most non-European ethnicities have a stronger preference for buttocks and legs, in particular Africans, Hispanics, and Amerindians (Native Americans). We explored how these patterns may help to explain cultural differences in mating display for different body parts and how they may be explicable in evolutionary terms.

Using data from the Philadelphia Neurodevelopmental Cohort, we examined whether European ancestry predicted cognitive ability over and above both parental socioeconomic status (SES) and measures of eye, hair, and skin color. First, using multi-group confirmatory factor analysis, we verified that strict factorial invariance held between self-identified African and European-Americans. The differences between these groups, which were equivalent to 14.72 IQ points, were primarily (75.59%) due to difference in general cognitive ability (g), consistent with Spearman&rsquo, s hypothesis. We found a relationship between European admixture and g. This relationship existed in samples of (a) self-identified monoracial African-Americans (B = 0.78, n = 2,179), (b) monoracial African and biracial African-European-Americans, with controls added for self-identified biracial status (B = 0.85, n = 2407), and (c) combined European, African-European, and African-American participants, with controls for self-identified race/ethnicity (B = 0.75, N = 7,273). Controlling for parental SES modestly attenuated these relationships whereas controlling for measures of skin, hair, and eye color did not. Next, we validated four sets of polygenic scores for educational attainment (eduPGS). MTAG, the multi-trait analysis of genome-wide association study (GWAS) eduPGS (based on 8442 overlapping variants) predicted g in both the monoracial African-American (r = 0.111, n = 2179, p &lt, 0.001), and the European-American (r = 0.227, n = 4914, p &lt, 0.001) subsamples. We also found large race differences for the means of eduPGS (d = 1.89). Using the ancestry-adjusted association between MTAG eduPGS and g from the monoracial African-American sample as an estimate of the transracially unbiased validity of eduPGS (B = 0.124), the results suggest that as much as 20%&ndash, 25% of the race difference in g can be natively explained by known cognitive ability-related variants. Moreover, path analysis showed that the eduPGS substantially mediated associations between cognitive ability and European ancestry in the African-American sample. Subtest differences, together with the effects of both ancestry and eduPGS, had near-identity with subtest g-loadings. This finding confirmed a Jensen effect acting on ancestry-related differences. Finally, we confirmed measurement invariance along the full range of European ancestry in the combined sample using local structural equation modeling. Results converge on genetics as a partial explanation for group mean differences in intelligence.

Research at the individual level shows strong positive relationships between performance in video games and on intelligence tests. Together with evidence of above average IQs of players of traditional mental sports such as chess, this suggests that national IQs should be strongly related to national performance on mental sports. To investigate this, lists of top players for 12 different electronic sports (e-sports) and traditional mental sports were collected from a variety of sources (total n = 36k). Using a log count approach to control for population size, national cognitive ability/IQ was found to be a predictor (p

Socially defined racial groups usually differ in average incomes, though the causes of this are contested. We used 5 large datasets with relevant variables to distinguish between cognitive meritocracy, cultural models, and discrimination models (NLSY79, NLSY97, Add Health, GSS, ANES2012; total n = ). The use of both self- and other-perceived race/ethnicity group allowed one to distinguish between effects related to how others perceive one’s race/ethnicity vs. how individuals perceive themselves. Results indicated that other-perceived Black and Hispanic racial statuses were associated with either no differences or slightly higher incomes when cognitive ability was controlled for, whereas self-perceived Black status was negatively related to income. Other self-perceived racial statuses had no clearly detectable effect. Skin tone had no detectable or quite small validity when IQ is also in the regression. Results were interpreted as being congruent with meritocracy and inconsistent with market-irrelevant discrimination models.

Self-reported discriminatory experiences differ slightly by US social racial groups, but why? Using the public-use Add Health dataset, the matter was investigated. It was found that when accounting for cognitive ability (IQ) that differs by social race group, there no longer seemed to be any detectable differences in self-reported discrimination, nor any differences related to skin tone. This seemed to be due to a slight correlation between self-reported discrimination and cognitive ability (r = -.14).Furthermore, the validity of social racial groups were examined for the prediction of self-reported income. It was found that other-perceived social race and skin tone did not predict income when IQ was included in the model, but self-perceived social race did. Results were overall congruent with meritocracy and incongruent with racial discrimination models.

In the United States, cognitive ability, socioeconomic status (SES), and genetic ancestry vary by race/ethnic identification. However, it is not known to what degree genetic ancestry is a useful predictor of outcomes independent of those cultural factors related to race/ethnic identification. Data from the Pediatric Imaging, Neurocognition, and Genetics Study (PING) (N = 1,369 children) were used to examine this issue. In regression models using 4 different codings for SIRE as a covariate, non-trivial incremental relationships were found between genetic ancestry and both cognitive ability and SES. These relationships were reduced somewhat when parental SES was added as a predictor with cognitive ability as the outcome. These associations generally held when subgroups were analyzed separately. Results were congruent with familial models of group differences. Implications for research on race/ethnic differences in the Americas are discussed.

Stereotypes about 32 country-of-origin groups were measured using an approximately representative survey of the Danish population (n = 476 after quality control). Participants were asked to estimate each group’s net fiscal contribution in Denmark. These estimates were then compared to the actual net fiscal contributions for the 32 groups, taken from a recent study by the Danish Ministry of Finance. Syria was an outlier, and was excluded from our analyses (although doing so made little difference to the results). Stereotypes were found to be highly accurate, both at the aggregate level (r = .85) and at the individual level (median r = .65). Interestingly, participants over- rather than under-estimated the net fiscal contributions of groups from countries with a higher percentage of Muslims. Indeed, this was true at both the aggregate and individual levels (r = -.30 and median r = -.55, respectively). Participants were also asked to say how many immigrants from each group should be admitted to Denmark. There was an extremely strong correlation between participants’ aggregate immigration policy preferences and their estimates of the 32 groups’ fiscal contributions (r = .98), suggesting that their preferences partly reflect accurate stereotypes.

Sex differences in mathematical ability were examined in a nation-wide sample of 32,346 Jordanian 4th graders (age 9-10) on a 40-item mathematics test. Overall, girls were found to perform slightly better (d = 0.12), while boys had slightly more variation in scores (standard deviations of 1.02 and 0.98 for boys and girls, respectively).2 parameter item response theory analysis showed that the item parameters were almost identical across sexes; correlations were .97 [95% confidence interval: .95 to .99] and .90 [.82 to .95] for difficulties and loadings, respectively. A bootstrapping analysis revealed that these could not be explained by sampling error alone, but reflected genuine departures from measurement invariance. However, sex differences in items showed no relationship to the relative size of the departure from measurement invariance.A correlation between item difficulty and male advantage was observed, r = .57 [.32 to .75] (.68 after exclusion of an outlier), such that the relative male advantage increased with increased item difficulty.Results were interpreted to be congruent with Richard Lynn’s developmental theory of sex differences in general intelligence.

IQ differences were examined between Blacks and Whites in a large Vietnam era sample (Vietnam Experience Study; total n ≈ 10,800). Relative to a White IQ of 100 and SD of 15, Blacks obtained a mean IQ of 85 and an SD of 12.An attempt to examine measurement invariance using multi-group confirmatory factor analysis failed with impossible estimates and very poor fits. A simpler approach of examining the correlation matrices by group showed that the White correlations were stronger, sometimes by a lot. Possible reasons for this were discussed.