Author: Meng Hu (Page 1 of 5)

How IQ became less important than personality: A critical examination of Borghans et al. (2016)

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).

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Wealth, Poverty and Politics: A must read for understanding group differences

Thomas Sowell’s book, Wealth, Poverty and Politics, provides a thorough explanation as to why nations and groups of peoples developed at different rates, how and why they rise or fall as a group or empire. There are only a few sections which I do not find convincing, such as his arguments on group differences in IQ and his complete rejection of the genetic hypothesis.

To summarize the ideas of the book, Sowell shows that 1) population differences emerged because geography has never been egalitarian, 2) cultural and geographical isolations are great impediments to development, 3) equal opportunity will not create equal outcomes between groups, 4) education is not human capital and has sometimes caused negative outcomes, 5) exploitation of the poor through either slavery or imperialism does not explain prosperity status, 6) poverty and inequality are so ill-defined to the point that comparisons are meaningless, 7) the government has a duty to please the masses through dubious tactics at the expense of economic performance.

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The Structure of Well Designed Online IQ Tests

There are convenient ways researchers can collect IQ scores and correlate the observed scores with measures of self-reported health, socio-economic attainment, personality or political views. In platforms such as Prolific or MTurk, participants make money in their spare time by completing tasks. Designing a test that displays both a high loading on the general factor of intelligence, while avoiding measurement bias and bad quality data from online participants, is quite a challenging task.


  1. Introduction page content
  2. Item’s pass rate and g-loading
  3. Lazy and dishonest test takers
  4. Short versus long test
  5. Scrolling dilemma
  6. Item type “write-in”
  7. Instruction and rules
  8. Cultural content and cultural bias
  9. Computerized Ability Test

The issues related to online testing are illustrated based on the numerous IQ tests Jurij Fedorov devised, with my assistance, using Alchemer’s professional software.

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Gender wage gap: Why the discrimination theory (likely) fails

Probably the most rehearsed explanation of the gender pay gap is discrimination. After accounting for traditional labor market factors, a large residual gap remains. This residual gap is also called the unexplained gap. Researchers often commit the fallacy of equating unexplained effect to discrimination effect instead of omitted variable bias. In fact, most wage decomposition models are probably contaminated by bias. This article will explain that much of the residual gap is likely due to other causes. In particular, time flexibility. The evidence for the discrimination effect is often ambiguous.

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Affirmative action failed: An extensive and complicated literature review

Despite the US Supreme Court recently overturning affirmative action (AA), many scholars believe that AA bans in higher education hurt minorities’ opportunities because affirmative action actually delivered on its promises. Although the findings lack consistency, the impact of AA on the outcomes of under-represented minorities (URM) is generally either ambiguous or slightly negative. The bans exert a less negative effect on more competitive fields such as STEM. The picture is even worse when one considers that AA comes at the cost of lowering the chance of other, more capable minorities, such as Asians, and does not greatly impact the intended targets, i.e., the impoverished families among URMs.

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Canadian Race/Ethnic Differences on the LSAT (2019-2023)

This article reports racial gaps in the LSAT scores for Canada (2019-2023). By using the threshold method designed by La Griffe du Lion (2007), the standardized effect sizes are computed from the proportions of members of each groups who attain specific score ranges. Results are compared with U.S. gaps in the Law School Admission Test (LSAT) and Medical College Admission Test (MCAT) scores. Details of the analysis is available here.

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Spearman’s g Explains Black-White but not Sex Differences in Cognitive Abilities in the Project Talent

In this analysis of the Project Talent data, the g factor model as represented by the Spearman’s Hypothesis (SH) was confirmed for the black-white cognitive difference but not for the sex difference. Results from MGCFA and MCV corroborate each other. MGCFA detected small-modest bias with respect to race but strong bias with respect to sex cognitive difference. Full result is available at OSF.

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A remarkable similarity between IQ and SAT scores across ethnic groups

Chuck recently published the IQ estimates for almost 30 ethnic groups/subgroups in the ABCD of the 10-year old US children. The post was an astounding hit. However, a few commenters complained that the sample sizes of some subgroups were small. I responded that if one could replicate the values and the rank order, one would have more confidence in these estimates. And this is exactly what we did here (full result available).
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Math abilities of transracial adoptees in the HSLS: Parent education does not moderate group differences

Transracial adoption studies, especially ones which examine the performance of adopted blacks, are lacking since the prominent Minnesota Transracial Study of Black adoptees (Weinberg et al., 1992, Table 2). To fill this gap I analyzed the HSLS data, and found that the math abilities of transracial adoptees do not depend on the adoptive parents’ race. Continue reading

The Untold Group Interaction in the Black-White IQ Gap

When observable measures such as socio-economic and health factors are adjusted, the IQ gap is substantially reduced yet a non-trivial difference remains. And while it is known that environmental factors are influenced by genetic factors and therefore should be not treated as pure environmental effects, an outcome that is typically ignored is that the education-matched blacks fall further behind in the IQ scores when education level increases.

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