Jump to content

Nations and IQ: Difference between revisions

From Wikipedia, the free encyclopedia
Browse history interactively
← Previous editNext edit →
Content deleted Content added
VisualWikitext
→‎International student assessment studies: in first half of subsection, removed sentences that were unclear or of unclear relevance, reducing the WP:UNDUE attention to Rindermann, per talk page discussion
Line 27: Line 27:


=== International student assessment studies ===
=== International student assessment studies ===
⚫
Rindermann (2007) states that the correlations between international student assessment studies and measures of national IQ are very high. His analysis found many of the same groupings and correlations found by Lynn and Vanhanen, with the lowest scores in sub-Saharan Africa, and a correlation of .60 between cognitive skill and GDP per capita. According to Hunt, Rindermann's analysis was more reliable than those by Lynn and Vanhanen.<ref>Hunt, Earl. ''Human Intelligence''. Cambridge University Press, 2011. pp. 440–43.</ref>
Rindermann (2007) states that the correlations between international student assessment studies and measures of national IQ are very high. Using the same statistical method used to measure the [[general intelligence factor]] (''g'') he finds evidence for that the "student achievement assessments and intelligence tests primarily measure a common cognitive ability". The international student assessment studies have the advantages of standardized testing over a short time period. A disadvantage is that unlike IQ-data collections, it does not include older people or more developing nations.<ref name="Rindermann"/> An advantage of using international student assessments instead of educational assessment is that "across countries and time, educational degrees are difficult to compare".<ref name=":0">{{Cite book|title=Cognitive capitalism: Human Capital and the Wellbeing of Nations|last=Rindermann|first=Heiner|publisher=University Printing House|year=2018|isbn=9781107279339|location=Cambridge UK|pages=64}}</ref> Compared to international student assessments, "literacy as the ability to read and write texts is a much too basic competence" and as a result "these three educational measures [literacy rate, years spent attending school, and highest achieved degree] usually show lower correlations compared to more complex ability measures".<ref name=":0" />

The international student assessment studies, the [[Trends in International Mathematics and Science Study|TIMSS]], [[Progress in International Reading Literacy Study|PIRLS]], and [[Programme for International Student Assessment|PISA]], are highly correlated with each other: "between TIMSS and PIRLS: r = .94 (N = 54), between TIMSS and PISA: r = .89 (N = 58), between PIRLS and PISA: r = .82 (N = 49)".<ref>{{Cite book|title=Cognitive Capitalism|last=Rindermann|first=Heiner|publisher=Cambridge University Press|year=2018|isbn=9781107279339|location=Cambridge|pages=114}}</ref>

⚫
Rindermann's analysis found many of the same groupings and correlations found by Lynn and Vanhanen, with the lowest scores in sub-Saharan Africa, and a correlation of .60 between cognitive skill and GDP per capita. According to Hunt, due to there being far more data available, Rindermann's analysis was more reliable than those by Lynn and Vanhanen. By measuring the relationship between educational data and social well-being over time, this study also performed a causal analysis, finding that a nation's investment in education leads to increased well-being later on.<ref>Hunt, Earl. ''Human Intelligence''. Cambridge University Press, 2011. pp. 440–43.</ref>


Rindermann (2007) writes that the mixture of many different tests and the not always clear representativeness of the samples seem to be the most serious problems. Furthermore, the measurement years vary, which is problematic because of the [[Flynn effect]]. Using the same adjustment for all nations is likely sometimes incorrect because since the 1970s developing nations have seen higher increases than the developed world. The method of averaging neighboring countries for an estimation for the many nations that did not have measured IQs, while having a high correlation (0.92) with the measured results in the case of the 32 nations that changed from the estimated to the measured categories between the two books, is likely problematic because some research indicates that absence of IQ tests indicates conditions such as poverty or war that may affect IQs. "In addition, some errors in the data have been observed".<ref name="Rindermann" />
Rindermann (2007) writes that the mixture of many different tests and the not always clear representativeness of the samples seem to be the most serious problems. Furthermore, the measurement years vary, which is problematic because of the [[Flynn effect]]. Using the same adjustment for all nations is likely sometimes incorrect because since the 1970s developing nations have seen higher increases than the developed world. The method of averaging neighboring countries for an estimation for the many nations that did not have measured IQs, while having a high correlation (0.92) with the measured results in the case of the 32 nations that changed from the estimated to the measured categories between the two books, is likely problematic because some research indicates that absence of IQ tests indicates conditions such as poverty or war that may affect IQs. "In addition, some errors in the data have been observed".<ref name="Rindermann" />

Revision as of 14:21, 6 December 2020

The relationship between nations and intelligence quotient is a controversial area of study concerning differences between nations in average intelligence test scores, their possible causes, and their correlation with measures of social well-being and economic prosperity.

Richard Lynn and Tatu Vanhanen constructed IQ estimates for many countries using literature reviews, student assessment studies and other methodologies to create estimates, which have been widely criticized on theoretical and methodological grounds.

Subsequent research by psychologists such as Earl B. Hunt, Jelte Wicherts and Heiner Rindermann has focused on identifying potential national differences in IQ, investigating possible causal factors, and determining the nature of the relationship of IQ to variables such as GDP, life expectancy, and governance.

Background

Earl B. Hunt writes that economists traditionally view differences in wealth between nations in terms of human capital, which is a general term for the abilities of the workforce. According to Hunt, international studies of IQ are important because they measure the cognitive skills necessary to excel in a post-industrial world.[1] Richard Lynn and Tatu Vanhanen published the books IQ and the Wealth of Nations and IQ and Global Inequality, which led to further investigations by other researchers, some of them highly critical of Lynn and Vanhanen's methods and conclusions.[2]

National comparisons of IQ

"Average IQ values in various European countries"

The 1981 article "Average IQ values in various European countries" by Vinko Buj is the only international IQ study that over a short time period has compared IQs using the same IQ test. Rindermann (2007) states that it is of dubious quality with scant information regarding how it was done.[3][4]

Lynn and Vanhanen

In the books IQ and the Wealth of Nations (2002) and IQ and Global Inequality (2006), Richard Lynn and Tatu Vanhanen created estimates of average IQs for 113 nations. They estimated IQs of 79 other nations based on neighboring nations or by other methods. They also created an estimate of "quality of human conditions" for each nation based on gross national product per capita, adult literacy rate, fraction of the population to enroll in secondary education, life expectancy, and rate of democratization. Lynn and Vanhanen found a substantial correlation between the national IQ scores they created and these various socioeconomic factors. They conclude that national IQ influences these measures of well-being, and that national differences in IQ are heavily influenced by genetics, although they also allow for some environmental contributions to it. They regard nutrition as the most important environmental factor, and education a secondary factor.[5]

Many negative reviews of these books have been published in the scholarly literature. In particular, the claim that the IQ tests employed are culturally neutral and unbiased has been criticized,[6][7][8] as have the methods used to compile the data.[9][10][11][12]

Susan Barnett and Wendy Williams characterized IQ and the Wealth of Nations as "an edifice built on layer upon layer of arbitrary assumptions and selective data manipulation. The data on which the entire book is based are of questionable validity and are used in ways that cannot be justified." They also wrote that cross-country comparisons are "virtually meaningless".[9]

On July 27, 2020, the European Human Behavior and Evolution Association issued a formal statement opposing the utilization of Lynn's national IQ dataset, citing various methodological concerns. They concluded "Any conclusions drawn from analyses which use these data are therefore unsound, and no reliable evolutionary work should be using these data."[10]

Wicherts, Dolan and van der Maas' analysis

In 2009 Jelte M. Wicherts, Conor V. Dolan, and Han L.J. van der Maas conducted a new analysis of IQ in sub-Saharan Africa, which was critical of many of Lynn and Vanhanen's methods.[12] Wicherts et al. concluded that Lynn and Vanhanen had relied on unsystematic methodology by failing to publish their criteria for including or excluding studies. They found that Lynn and Vanhanen's exclusion of studies had depressed their IQ estimate for sub-Saharan Africa, and that including studies excluded in "IQ and Global Inequality" resulted in average IQ of 82 for sub-Saharan Africa, lower than the average in Western countries, but higher than Lynn and Vanhanen's estimate of 67. Wicherts at al. conclude that this difference is likely due to sub-Saharan Africa having limited access to modern advances in education, nutrition and health care.[11]

International student assessment studies

Rindermann (2007) states that the correlations between international student assessment studies and measures of national IQ are very high. His analysis found many of the same groupings and correlations found by Lynn and Vanhanen, with the lowest scores in sub-Saharan Africa, and a correlation of .60 between cognitive skill and GDP per capita. According to Hunt, Rindermann's analysis was more reliable than those by Lynn and Vanhanen.[13]

Rindermann (2007) writes that the mixture of many different tests and the not always clear representativeness of the samples seem to be the most serious problems. Furthermore, the measurement years vary, which is problematic because of the Flynn effect. Using the same adjustment for all nations is likely sometimes incorrect because since the 1970s developing nations have seen higher increases than the developed world. The method of averaging neighboring countries for an estimation for the many nations that did not have measured IQs, while having a high correlation (0.92) with the measured results in the case of the 32 nations that changed from the estimated to the measured categories between the two books, is likely problematic because some research indicates that absence of IQ tests indicates conditions such as poverty or war that may affect IQs. "In addition, some errors in the data have been observed".[3]

In 2013, Rindermann compared the results of three culture-reduced IQ tests collected in Tanzania in 1999 and 2000 (APM, MRT, LPS), WISC-IV working memory and verbal comprehension scale tests of blind, visually handicapped and non-blind multiethnic students aged 10 to 16 years in South Africa, and student assessment studies conducted in 14 African countries between 1964 and 2009 (primarily TIMSS, PIRLS and SACMEQ) with his own regression analysis, which used the Human Development Index and skin brightness as, respectively, potential nurture-based and nature-based predictors of cognitive ability. After adjusting for the Flynn effect and using 2010 estimates as the baseline, his predicted IQ for the African majority nation samples varied between 68 and 78, with an average IQ of around 75. This was similar to Rindermann and Te Nijenhuis (2012)'s average IQ estimate for Bali in Southeast Asia and other developing regions. According to Rindermann, the resulting IQ estimates are predicated on a number of contributing factors, including properly administered tests, the degree to which testing instructions are understood, sample bias, school enrollment rates, mean annual IQ grow at school and per age year, a higher Flynn effect among African samples, age correction, and greater or lesser familiarity with testing norms.[14]

Correlations with national IQ

Hunt argues that substantial correlations between intelligence test scores and measures of well-being also exist when the analysis is limited to developed countries, where the IQ results are more likely to be accurate.[2] Hunt and Wittman (2008) state that although the correlation between national IQ and economic well-being is clear, any possible causality between them is more difficult to determine.[15]

Causes of national differences

See also: Flynn effect § Proposed explanations, and Impact of health on intelligence

Since the 20th century, there have been worldwide continual increases in measured IQ. This rise has been correlated with degrees of rising education levels, and as such may provide a partial explanation for observed differences in average IQ scores between nations. Wicherts et al. have suggested that national differences in IQ could be because African countries have not yet experienced the improvements that cause the Flynn effect in the developed world, such as improvements in nutrition and health, and educational attainment.[11] Wicherts, Borsboom, and Dolan (2010) criticized evolutionary studies for problems such as ignoring or assuming that the Flynn effect is equal worldwide and assuming that there have been no migrations and changes in climate over the course of evolution. They argue that "national IQs are strongly confounded with the current developmental status of countries. National IQs correlate with all the variables that have been suggested to have caused the Flynn Effect in the developed world."[16]

Eppig, Fincher, and Thornhill (2010) states that the most importantly factor in predicting national IQ by a large margin is the prevalence of infectious disease. The authors argue that "From an energetics standpoint, a developing human will have difficulty building a brain and fighting off infectious diseases at the same time, as both are very metabolically costly tasks" and that "the Flynn effect may be caused in part by the decrease in the intensity of infectious diseases as nations develop."[17]

David Marks (2010) argues that differences in average IQ scores between national groups and across time periods can be fully accounted for by differences in literacy levels, and that "IQ distributions will converge if opportunities are equalized for different population groups to achieve the same high level of literacy skills."[18]

See also

Wikimedia Commons has media related to Intelligence quotient maps.

References

  1. ^ Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. pp. 443–45.
  2. ^ a b Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. pp. 436–37.
  3. ^ a b Rindermann, H. (2007). The g-factor of international cognitive ability comparisons: The homogeneity of results in PISA, TIMSS, PIRLS and IQ-tests across nations. European Journal of Personality, 21, 6 67−706 http://onlinelibrary.wiley.com/doi/10.1002/per.634/abstract
  4. ^ Buj, V. (1981). Average IQ values in various European countries. Personality and Individual Differences, 2, 168–169
  5. ^ Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. pp. 437–39.
  6. ^ Case for Non-Biased Intelligence Testing Against Black Africans Has Not Been Made: A Comment on Rushton, Skuy, and Bons (2004) 1*, Leah K. Hamilton1, Betty R. Onyura1 and Andrew S. Winston International Journal of Selection and Assessment Volume 14 Issue 3 Page 278 - September 2006
  7. ^ Culture-Fair Cognitive Ability Assessment Steven P. Verney Assessment, Vol. 12, No. 3, 303-319 (2005)
  8. ^ The attack of the psychometricians Archived 2007-06-08 at the Wayback Machine. DENNY BORSBOOM. PSYCHOMETRIKA VOL 71, NO 3, 425–440. SEPTEMBER 2006.
  9. ^ a b Barnett, Susan M. and Williams, Wendy (August 2004). "National Intelligence and the Emperor's New Clothes". Contemporary Psychology: APA Review of Books. 49 (4): 389–396. doi:10.1037/004367. Archived from the original on 2012-07-17.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  10. ^ a b "EHBEA Statement on National IQ Datasets, European Human Behaviour and Evolution Association" (PDF). 27 July 2020.{{cite web}}: CS1 maint: url-status (link)
  11. ^ a b c Jelte M. Wicherts, Conor V. Dolana, and Han L.J. van der Maas, A systematic literature review of the average IQ of sub-Saharan Africans, Intelligence, Volume 38, Issue 1, January–February 2010, pp. 1–20, https://dx.doi.org/10.1016/j.intell.2009.05.002
  12. ^ a b Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. pp. 439–40.
  13. ^ Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. pp. 440–43.
  14. ^ Rindermann, Heiner (July 2013). "African cognitive ability: Research, results, divergences and recommendations". Personality and Individual Differences. 55 (3): 229–233. doi:10.1016/j.paid.2012.06.022.
  15. ^ Hunt, Earl and Wittman, Werner. "National Intelligence and national prosperity." Intelligence 36:1, 2008.
  16. ^ Why national IQs do not support evolutionary theories of intelligence, Jelte M. Wicherts, Denny Borsboom and Conor V. Dolan, Personality and Individual Differences, Volume 48, Issue 2, January 2010, pp. 91–96, https://dx.doi.org/10.1016/j.paid.2009.05.028
  17. ^ Christopher Eppig, Corey L. Fincher, and Randy Thornhill Parasite prevalence and the worldwide distribution of cognitive ability Proc R Soc B 2010: rspb.2010.0973v1-rspb20100973. http://rspb.royalsocietypublishing.org/content/early/2010/06/29/rspb.2010.0973.abstract
  18. ^ Marks, David (2010). "IQ Variations across Time, Race, and Nationality: An Artifact of Differences in Literacy Skills". Psychological Reports. 106:3: 643–664.

External links

Retrieved from "https://en.wikipedia.org/w/index.php?title=Nations_and_IQ&oldid=992672331"