At Our Wits' End, page 16
Country
Europeans
Non-Europeans
France
1.9
2.8
Netherlands
1.7
2.5
Sweden
1.5
2.3
It can be seen that the fertility rate of non-European mothers is almost double that of European mothers. Though the Danish statistics indicate that, while this difference is decreasing, the difference nevertheless still exists. Lynn presents data showing that this same process is occurring in Australia, New Zealand, Canada, the USA, and in other European countries; in other words, across the Western world. Based on these data, he calculates the European percentage of different Western countries by certain years. By 2050, the UK, which was about 86% European in 2006, will be 56% European. The USA, which was 71% European in the year 2000, will be 45% European.[68]
So, all of these developments have led to a ‘perfect storm’ of factors which ensure that there is a negative relationship between intelligence and fertility and a negative relationship between education level and fertility. We would expect this negative relationship to have been present in England at least since around 1800. Based on these data, Lynn has calculated that by the year 2106 the average IQ in Britain should be about 87, 13 points lower than it is now. This will obviously have huge implications for living standards, democracy, political stability, civic society, crime rates, and all of the other issues that are connected to IQ. The only Western country where Lynn predicts no significant intelligence decline over the next 20 years is Canada, because its immigrant population is primarily Northeast Asian in origin. Similarly, Danish psychologist Helmuth Nyborg has calculated that by 2072 Denmark will be 60% Danish and IQ will have gone down by 5 points, partly due to immigration and partly due to less intelligent Danes having the highest fertility.[69]
Indeed, research by Richard Lynn and the Finnish political scientist Tatu Vanhanen (1929–2015) has shown that there are average IQ differences between countries. These strongly correlate with other measures of cognitive differences between countries, such as differences on international scholastic tests like PISA, so they are likely to be broadly correct even if some samples are problematic. Lynn and Vanhanen have shown that the average IQ of a country strongly predicts how highly it will score on pretty much every measure of civilisation that you can think of: educational attainment, average earnings, democracy, lack of corruption, nutrition, life expectancy, low infant mortality rate, access to clean water and sanitary conditions, low levels of crime, liberal attitudes, rational attitudes, and even happiness.[70]
However, if intelligence is declining, and if intelligence is strongly heritable, we would expect it to be clearly measurable. There should be clear evidence that intelligence has been decreasing for the last century or so. We will see that there is indeed such evidence. However, the most obvious place to look for evidence is IQ tests and here things start to become complicated, at least at first...
1 Baines, E. (2015) History of Cotton Manufacture in Great Britain, Cambridge: Cambridge University Press, p. 155.
2 For a readable introduction to the direct and indirect achievements of the Industrial Revolution, see: Weightman, G. (2003) What the Industrial Revolution Did For Us, London: BBC Books.
3 Richard Lynn originally presented detailed biographies of the key characters in his book, Dysgenics. In the following section, we draw upon these.
4 Morel, B.A. (1857) Traité des dégenérescenses physiques, intellectuelles et morales de 1’espèce humaine, Paris: Larousse.
5 Galton, F. (1865) Hereditary talent and character, MacMillan’s Magazine, p. 325.
6 Galton, F. (1869) Hereditary Genius, London: Macmillan, p. 414. See also: Bulmer, M. (2004) Francis Galton: Pioneer of Heredity and Biometry, Baltimore, MD: Johns Hopkins University Press.
7 Darwin, C. (1871) The Descent of Man, London: John Murray, p. 501.
8 Wallace, A.R. (1890) Human selection, Popular Science Monthly, 38, pp. 90–102.
9 Pearson, K. (1901) National Life from the Standpoint of Science, London: Methuen, p. 101.
10 Pearson, K. (1912) The Groundwork of Eugenics, Cambridge: Eugenics Laboratory, p. 32. On Karl Pearson’s life, see: Porter, T. (2010) Karl Pearson: The Scientific Life in a Statistical Age, Princeton, NJ: Princeton University Press.
11 Fisher, R.A. (1929) The Genetical Theory of Natural Selection, Oxford: Clarendon Press.
12 Heron, D. (1906) On the Relation of Fertility in Man to Social Status, London: Dulan.
13 For a more detailed discussion of Fisher’s life, see: Fisher Box, J. (1978) R.A. Fisher: The Life of a Scientist, Hoboken, NJ: John Wiley & Sons.
14 Cattell, R.B. (1937) The Fight for our National Intelligence, London: P.S. King & Son Ltd.
15 Cattell, R.B. (1937) The Fight for our National Intelligence, London: P.S. King & Son Ltd.
16 Cattell, R.B. (1951) The fate of national intelligence: Test of a thirteen year prediction, Eugenics Review, 17, pp. 136–148.
17 On Cattell’s life, see: Horn, J. & Cattell, H. (2015) A Short Biography: Raymond Bernard Cattell, [Online], http://www.cattell.net/devon/rbcbio.htm.
18 Meisenberg, G. (2010) The reproduction of intelligence, Intelligence, 38, pp. 220–230.
19 Reeve, C., Lyerly, J. & Peach, H. (2013) Adolescent intelligence and socio-economic wealth independently predict adult marital and reproductive behaviour, Intelligence, 41, pp. 358–365.
20 Von Stumm, S., Batty, G.D. & Deary, I.J. (2011) Marital status and reproduction: Associations with childhood intelligence and adult social class in the Aberdeen children of the 1950s study, Intelligence, 39, pp. 161–167.
21 Kanazawa, S. (2014) Intelligence and childlessness, Social Science Research, 48, pp. 157–170.
22 Woodley of Menie, M.A. (2015) How fragile is our intellect? Estimating losses in general intelligence due to both selection and mutation accumulation, Personality & Individual Differences, 75, pp. 80–84.
23 Chmykhova, E., Davydov, D. & Lynn, R. (2016) Dysgenic fertility in the Russian Federation, Mankind Quarterly, 57, pp. 269–278.
24 Chen, H.-Y., Chen, Y.-H., Liao, Y.-K., Chen, H.-P. (2012) Relationship of fertility with intelligence and education in Taiwan, Journal of Biosocial Science, 45, pp. 567–572.
25 Chen, H.-Y., Chen, Y.-H., Cheng, H. & Lynn, R. (2017) Dysgenic fertility for intelligence and education in Taiwan, Intelligence, DOI: 10.1016.
26 Wang, M., Fuerst, J. & Ren, J. (2016) Evidence of dysgenic fertility in China, Intelligence, 57, pp. 15–24.
27 Abdel-Khalek, A. & Lynn, R. (2008) Intelligence, family size and birth order: Some data from Kuwait, Personality and Individual Differences, 44, pp. 1032–1038.
28 Al-Kandari, Y. (2007) Fertility and its relationship with sociocultural factors in Kuwaiti society, Eastern Mediterranean Health Journal, 13, pp. 1364–1371.
29 Abdin, T. (22nd May 2014) Sudan: The case of the missing professor, All Africa, [Online], http://allafrica.com/stories/201405301164.html.
30 Khaleefa, O. (2010) Intelligence in Sudan and IQ gain between 1964 and 2008, Arab Psynet E-Journal, 25–26, pp. 157–167.
31 Al Shahomee, A., Lynn, R. & Abdalla, S. (2012) Dysgenic fertility, intelligence and family size in Libya, Intelligence, 41, pp. 67–69. In addition a very weak correlation (–0.08) has been found between completed fertility and IQ on the Caribbean island of Dominica. See: Meisenberg, G., Lawless, E., Lambert, E. & Newton, N. (2005) The Flynn Effect in the Caribbean: Generational change of cognitive test performance in Dominica, Mankind Quarterly, 46, pp. 29–69.
32 Hawe, E. (2008) Compendium of Health Statistics, 2009, Manchester: Radcliffe Medical.
33 Čvorović, J., Rushton, J. & Tenjevic, L. (2008) Maternal IQ and child mortality in 222 Serbian Roma (Gypsy) women, Personality & Individual Differences, 44, pp. 1604–1609.
34 Okbay, A., Beauchamp, J.P., Fontana, M.A., Lee, J.J., Pers, T.H., Rietveld, C.A. & Benjamin, D.J. (2016) Genomewide association study identifies 74 loci associated with educational attainment, Nature, 533, pp. 539–542.
35 Beauchamp, J.P. (2016) Genetic evidence for natural selection in humans in the contemporary United States, Proceedings of the National Academy of Sciences USA, 113, pp. 7774–7779.
36 Meisenberg, G. (2008) How universal is the negative correlation between education and fertility? Journal of Social, Political & Economic Studies, 33, pp. 205–227.
37 Beauchamp, J.P. (2016) Genetic evidence for natural selection in humans in the contemporary United States, Proceedings of the National Academy of Sciences USA, 113, pp. 7774–7779. See also: Conley, D., Laidley, T., Belsky, D.W., Fletcher, J.M., Boardman, J.D. & Domingue, B.W. (2016) Assortative mating and differential fertility by phenotype and genotype across the 20th century, Proceedings of the National Academy of Sciences USA, 113, pp. 6647–6652.
38 Woodley of Menie, M.A., Schwartz, J.A. & Beaver, K.M. (2016) How cognitive genetic factors influence fertility outcomes: A meditational SEM analysis, Twins Research & Human Genetics, 19, pp. 628–637.
39 It has been observed in studies with very large sample sizes that these genetic variants for educational attainment and IQ negatively predict fertility even when educational attainment is fully controlled for. This may be because persistent selection for lower g has created negative genetic correlations between genes for g and genes for fertility. Selection requires genetic variance upon which to operate. As such, it creates correlations among traits, thus fuelling itself by pooling formerly distinct sources of genetic variance and acting upon them.
40 The following section summarises his presentation of this argument in his book 2011 book Dysgenics.
41 Kost, K. & Forrest, J. (1995) Intention status of U.S. births in 1988: Differences by mothers’ socio economic and demographic characteristics, Family Planning Perspectives, 27, pp. 11–17.
42 Forrest, J. & Singh, S. (1990) The sexual and reproductive behavior of American women, 1982–1988, Family Planning Perspectives, 22, pp. 206–214.
43 Kanazawa, S. (2014) Intelligence and childlessness, Social Science Research, 48, pp. 157–170.
44 Murray, C. (1984) Losing Ground: American Social Policy, 1950–1980, New York: Basic Books.
45 Herrnstein, R. & Murray, C. (1994) The Bell Curve, New York: Free Press.
46 Swinford, S. (10th July 2013) Most children will be born out of wedlock by 2016, The Telegraph, [Online], http://www.telegraph.co.uk/news/politics/10172627 /Most-children-will-be-born-out-of-wedlock-by-2016.html.
47 Murray, C. (1994) Underclass: The Crisis Deepens, London: IEA Health and Welfare Unit.
48 Perkins, A. (2016) The Welfare Trait: How State Benefits Affect Personality, London: Palgrave: Macmillan.
49 Young, T. (16th January 2016) Tell the truth about benefit claimants and the left shuts you down, The Spectator.
50 Perkins, A. (2016) The Welfare Trait: How State Benefits Affect Personality, London: Palgrave Macmillan, p. 2, citing: Brewer, M., Ratcliffe, A. & Smith, S. (2012) Does welfare reform affect fertility? Evidence from the UK, Journal of Population Economics, 25, pp. 245–266.
51 Perkins, A. (2016) The Welfare Trait: How State Benefits Affect Personality, London: Palgrave Macmillan, pp. 158–159.
52 Perkins, A. (2016) The Welfare Trait: How State Benefits Affect Personality, London: Palgrave Macmillan, p. 176.
53 Perkins, A. (2016) The Welfare Trait: How State Benefits Affect Personality, London: Palgrave Macmillan, p. 77. Citing: Tonge, W.L., Lunn, J.E., Greathead, M. & McLaren, S. (1981) A Follow-Up to the Adult Sons and Daughters of Sheffield Problem and Comparison Families Originally Reported by Tonge, James and Hilliam in 1975, London: Social Science Research Council.
54 Tonge, W.L., Lunn, J.E., Greathead, M. & McLaren, S. (1981) A Follow-Up to the Adult Sons and Daughters of Sheffield Problem and Comparison Families Originally Reported by Tonge, James and Hilliam in 1975, London: Social Science Research Council. Cited in Perkins, p. 24.
55 Perkins, A. (2016) The Welfare Trait: How State Benefits Affect Personality, London: Palgrave Macmillan, p. 25.
56 Quoted in: Perkins, A. (2016) The Welfare Trait: How State Benefits Affect Personality, London: Palgrave Macmillan, p. 48.
57 Woodley of Menie, M.A., Cabeza de Baca, T., Fernandes, H., et al. (2016) Slow and steady wins the race: K positively predicts fertility in the USA and Sweden, Evolutionary Psychological Science, 3, pp. 109–117.
58 Woodley of Menie, M.A. & Madison, G. (2015) The association between g and K in a sample of 4246 Swedish twins: A behavior genetic analysis, Personality and Individual Differences, 75, pp. 80–84.
59 Glass, R., et al. (2006) Glass’ Office Gynecology, Philadelphia, PA: Lipincott, Williams & Wilkins, p. 385.
60 Herrnstein, R.J. & Murray, C. (1994) The Bell Curve, New York: Free Press.
61 This is no exaggeration. For a history of the way in which researchers in this area have been treated up to 2012, see: Dutton, E. (2012) Culture Shock and Multiculturalism, Newcastle: Cambridge Scholars Publishing, pp. 135–137. Reactions to their research have included death threats, assault, disruption of lectures, police investigations, trumped up academic misconduct investigations, condemnation in the media, condemnation by politicians leading to threats to their safety, petitions to be fired from university posts, and actual firings from university posts. We hope readers will agree that it is shocking that researchers can be treated in this way simply for reporting what they genuinely regard as empirically accurate findings. Such critics also deploy less violent though equally illogical tactics, such as finding small errors in the works of such scholars and attempting to claim that the whole work is, therefore, suspect; or attacking the researcher personally rather than his or her arguments. For example, they might accuse the researcher of bias, which, of course, has no bearing at all on whether what they are saying is empirically accurate.
62 We have already looked at the fallacious arguments levelled against the concept of ‘intelligence’. Similar arguments are used against the concept of ‘race’. A ‘race’ is a breeding population that differs, genetically, from other such breeding populations. It differs as a result of geographical isolation, cultural separation, and endogamy. A ‘race’ shows patterns of genotypic frequency for a number of inter-correlated characteristics compared with other breeding populations. The most obvious manifestations of these differences are differences in physical appearance and mental characteristics which correlate together, indicating that it is useful, following the scientific desire to be able to make correct predictions about the world, to divide humans into racial categories in much the same way that we might divide any other particular animal species into different sub-species. The differences between races may be smaller than the differences within races for certain traits, but if these small differences are all in a particular direction—due to adaptation to a particular environment—they will lead to significant overall differences. Genetic clustering data indicate that there are around five to seven distinct races. Anyone who wants to question the ‘morality’ of the ‘race’ category should note that there are significant race differences in the prevalence of genetic diseases, so there are potentially serious consequences to denying the significance of race. For a more detailed explanation of the ‘race’ concept, see: Sarich, V. & Miele, F. (2004) Race: The Reality of Human Differences, Boulder, CO: Westview Press.
63 Te Nijenhuis, J. & van der Flier, H. (2003) Immigrant-majority group differences in cognitive performance: Jensen effects, cultural effects, or both? Intelligence, 31, pp. 443–459.
64 See: Jensen, A.R. (1998) The g Factor: The Science of Mental Ability, Westport, CT: Praeger.
65 Kirkegaard, E. (2013) Predicting immigrant IQ from their countries of origin, and Lynn’s National IQs: A case study from Denmark, Mankind Quarterly, 54, pp. 151–167.
66 Lynn, R. & Vanhanen, T. (2012) Intelligence: A Unifying Construct for the Social Sciences, London: Ulster Institute for Social Research.
67 The Local (15th January 2015) A portrait of modern Denmark in ten stats, [Online], http://www.thelocal.dk/20150115/a-portrait-of-modern-denmark-in-ten-stats.
