{"id":3328,"date":"2012-10-18T14:38:22","date_gmt":"2012-10-18T13:38:22","guid":{"rendered":"http:\/\/emilkirkegaard.dk\/en\/?p=3328"},"modified":"2012-10-19T00:47:05","modified_gmt":"2012-10-18T23:47:05","slug":"review-and-thoughts-intelligence-a-unifying-construct-for-the-social-sciences-richard-lynn-and-tatu-vanhanen-2012","status":"publish","type":"post","link":"https:\/\/emilkirkegaard.dk\/en\/2012\/10\/review-and-thoughts-intelligence-a-unifying-construct-for-the-social-sciences-richard-lynn-and-tatu-vanhanen-2012\/","title":{"rendered":"Review and thoughts: Intelligence: A Unifying Construct for the Social Sciences (Richard Lynn and Tatu Vanhanen, 2012)"},"content":{"rendered":"<p>Richard Lynn was so kind to send me a signed copy of his latest book. i immediately paused the reading of another book to read this one. some comments and quotes are below. quotes are from the ebook version of the book which i found on the internet.<\/p>\n<p><a href=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/intelligence-a-unifying-construct-for-the-social-sciences-richard-lynn-and-tatu-vanhanen.pdf\">Richard Lynn, Tatu Vanhanan &#8211; Intelligence, a A Unifying Construct for the Social Sciences, 2012<\/a><\/p>\n<h3>Review<\/h3>\n<p>Some general conclusions about the book. All in all this is a typical Richard Lynn book. It has a very dry style, and is somewhat repetitive. On the other hand, it is not overly long at 400 pages. Many of these are long lists of tables, so are not normally read except if one wants to look up specific countries. It would perhaps have been a good idea to just publish them on the internet for the curious and other researchers. The book contains a wealth of citations revealing a very impressive scholarship. The areas investigated on a global level are many, and the results interesting. The people who think that national IQs are &#8220;meaningless&#8221; and that human races do not exist or are social constructions (whatever that means, if anything) have the difficult job of explaining why, if these numbers are meaningless, do they fare so well in predicting things on a global level? In other words, why do they have so high validity for a multitude of things? One cannot just regard IQ as &#8220;academic intelligence&#8221; or some such thing if one can effectively use national IQs to predict things like the lack of proper sanitation. Most often national IQs are found to be better predictors than various non-IQ variables. Although one some occasions I would have liked the authors to use some more variables to see whether they made an impact. I think the authors are sometimes a bit too pessimistic about the possibilities of changing the situation for the low-IQ countries, but I agree with them that one should not expect many of these correlations to change drastically in the near future.<\/p>\n<p>&nbsp;<\/p>\n<h3>Thoughts and comments to various things<\/h3>\n<p>The introduction of the book neatly and shortly explains what the book is about:<\/p>\n<p><span style=\"color: #800000;\">The physical sciences are unified by a few common theoretical<\/span><br \/>\n<span style=\"color: #800000;\">constructs, such as mass, energy, pressure, atoms, molecules and<\/span><br \/>\n<span style=\"color: #800000;\">momentum, that are defined and measured in the same ways and<\/span><br \/>\n<span style=\"color: #800000;\">explain a wide range of phenomena in physics, astrophysics,<\/span><br \/>\n<span style=\"color: #800000;\">chemistry and biochemistry. This has been beneficial for the<\/span><br \/>\n<span style=\"color: #800000;\">development of the physical sciences, because it has allowed the<\/span><br \/>\n<span style=\"color: #800000;\">transfer of concepts from one field to others. It has allowed<\/span><br \/>\n<span style=\"color: #800000;\">interface subjects like chemical physics and biochemistry to<\/span><br \/>\n<span style=\"color: #800000;\">develop their own insights and concepts on the basis of those<\/span><br \/>\n<span style=\"color: #800000;\">already developed in their parent fields. Physics is the most basic<\/span><br \/>\n<span style=\"color: #800000;\">of the natural sciences, because the phenomena of the others can<\/span><br \/>\n<span style=\"color: #800000;\">be explained by the laws of physics. For this reason, physics has<\/span><br \/>\n<span style=\"color: #800000;\">been called the queen of the physical sciences.<\/span><\/p>\n<p><span style=\"color: #800000;\">Hitherto, the social sciences have lacked common unifying<\/span><br \/>\n<span style=\"color: #800000;\">constructs of this kind. The disciplines of the social sciences,<\/span><br \/>\n<span style=\"color: #800000;\">comprising psychology, economics, political science,<\/span><br \/>\n<span style=\"color: #800000;\">demography, sociology, criminology, anthropology and<\/span><br \/>\n<span style=\"color: #800000;\">epidemiology are largely isolated from one another, each with<\/span><br \/>\n<span style=\"color: #800000;\">their own vocabulary and theoretical constructs.<\/span><br \/>\n<span style=\"color: #800000;\">Psychology can be considered the most basic of the social<\/span><br \/>\n<span style=\"color: #800000;\">sciences because it is concerned with differences between<\/span><br \/>\n<span style=\"color: #800000;\">individuals, while the other social sciences are principally<\/span><br \/>\n<span style=\"color: #800000;\">concerned with differences between groups such as socio-<\/span><br \/>\n<span style=\"color: #800000;\">economic classes, ethnic and racial populations, regions within<\/span><br \/>\n<span style=\"color: #800000;\">countries, and nations. These groups are aggregates of<\/span><br \/>\n<span style=\"color: #800000;\">individuals, so the laws that have been established in psychology<\/span><br \/>\n<span style=\"color: #800000;\">should be applicable to the group phenomena that are the concern<\/span><br \/>\n<span style=\"color: #800000;\">of the other social sciences.<\/span><br \/>\n<span style=\"color: #800000;\">Our objective in this book is to develop the case that the<\/span><br \/>\n<span style=\"color: #800000;\">psychological construct of intelligence can be a unifying<\/span><br \/>\n<span style=\"color: #800000;\">explanatory construct for the social sciences. Intelligence is<\/span><br \/>\n<span style=\"color: #800000;\">measured by the intelligence test that was constructed by Alfred<\/span><br \/>\n<span style=\"color: #800000;\">Binet in 1905. During the succeeding century it has been shown<\/span><br \/>\n<span style=\"color: #800000;\">that intelligence, measured as the IQ (the intelligence quotient),<\/span><br \/>\n<span style=\"color: #800000;\">is a determinant of many important social phenomena,<\/span><br \/>\n<span style=\"color: #800000;\">including educational attainment, earnings, socio-economic<\/span><br \/>\n<span style=\"color: #800000;\">status, crime and health. Our theme is that the explanatory value<\/span><br \/>\n<span style=\"color: #800000;\">of intelligence that has been established for individuals can be<\/span><br \/>\n<span style=\"color: #800000;\">extended to the explanation of the differences between groups,<\/span><br \/>\n<span style=\"color: #800000;\">that have been found in the other social sciences, and in<\/span><br \/>\n<span style=\"color: #800000;\">particular to the explanation of the differences between nations.<\/span><br \/>\n<span style=\"color: #800000;\">Thus, we propose that psychology is potentially the queen of<\/span><br \/>\n<span style=\"color: #800000;\">the social sciences, analogous to the position of physics as the<\/span><br \/>\n<span style=\"color: #800000;\">queen of the physical sciences. <span style=\"color: #000000;\">(p. 1-2)<\/span><br \/>\n<\/span><\/p>\n<p>It is difficult to disagree with this.<\/p>\n<p>&#8211;<\/p>\n<p>one of the things that bother me with the Health chapter is that it doesnt try to compare with and adjoin with the data from <a href=\"http:\/\/en.wikipedia.org\/wiki\/The_Spirit_Level:_Why_More_Equal_Societies_Almost_Always_Do_Better\"><em>The Spirit Level<\/em><\/a>. The authors of SPL contend that many of the things that Lynn&amp;Vanhanan (LV) thinks is due to intelligence, is really due to economic (in)equality. unfortunately, LV does not try to control for this. it wud be interesting to see if the effects of high econ. equality goes away if one controls for intelligence. in other words, that the effects of econ. equality is really just intelligence working thru it.<\/p>\n<p>For a video introduction to the SPL, see this:<\/p>\n<p><iframe loading=\"lazy\" src=\"http:\/\/embed.ted.com\/talks\/richard_wilkinson.html\" frameborder=\"0\" scrolling=\"no\" width=\"560\" height=\"315\"><\/iframe><\/p>\n<p>&#8211;<\/p>\n<p>one annoying thing about this book, is that it is full of data tables, and the data from these cannot easily be copied into something useful. at least, i have failed to do it in any easy way. it requires a lot of fiddling to get the formatting right in calc\/excel. hopefully, LV will make data tables available on their websites where they can easily be downloaded so that others can test out other hypotheses.<\/p>\n<p>many of the tables span two pages but are not that big and cud easily fit into a single table on one page. unfortunately, having to use the image now requires that one either zooms out a lot to fit it all into one screen before taking a screenshot and hence makes the text small, or take two screenshots and edit them together in an image editor. it wud be very nice if they were made available on the website for free use.<\/p>\n<p>&#8211;<\/p>\n<p>a recurrent thing about the book is that the editor did quite a poor job. there are a lot of easily visible typografical mistakes that are a bit annoying. they dont distract too much from the reading of the book, except in the rare cases where a missing word makes interpretation necessary. for instance, on p. 83-84 table 4.5, the 10th line is missing the prefix &#8220;in&#8221; which makes it appear as if the data presented varies wildly from a positive 0.61 correlation to three other strong negative correlations between -.52 and -0.60.<\/p>\n<p>there was also another place where a &#8220;not&#8221; was missing and this left me confused for a few seconds.<\/p>\n<p>as for formatting, look at table 7.1, line 1, the word &#8220;All&#8221; is strangely located in a line below the other information. look also to lines 10-11 and notice how the two &#8220;F&#8221; are floating to the left.<\/p>\n<p>these mistakes shud be fixed and a new online edition released. this cant be too difficult to do.<\/p>\n<p>&#8211;<\/p>\n<p><a href=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/ScreenHunter_04-Oct.-18-01.22.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-thumbnail wp-image-3330\" title=\"ScreenHunter_04 Oct. 18 01.22\" src=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/ScreenHunter_04-Oct.-18-01.22-150x150.png\" alt=\"\" width=\"150\" height=\"150\" \/><\/a><\/p>\n<p>notice how low the dysgenic effects are. i was under the impression that they were stronger. also keep in mind that the lines 14-17 are those with the best data. the reason for that is that:<\/p>\n<p><span style=\"color: #800000;\">Rows 2, 3 and 4 give negative correlations between<\/span><br \/>\n<span style=\"color: #800000;\">intelligence and fertility based on a nationally representative<\/span><br \/>\n<span style=\"color: #800000;\">American sample showing that the negative correlation is higher<\/span><br \/>\n<span style=\"color: #800000;\">for white women than for white men, and higher for white<\/span><br \/>\n<span style=\"color: #800000;\">women than for black women. This study is not wholly<\/span><br \/>\n<span style=\"color: #800000;\">satisfactory because the age of the sample was 25 to 34 years and<\/span><br \/>\n<span style=\"color: #800000;\">many of them would not have completed their fertility.<\/span><\/p>\n<p><span style=\"color: #800000;\">To overcome this problem, Vining (1995) published data on<\/span><br \/>\n<span style=\"color: #800000;\">the fertility of his female sample of the ages between 35 and 44,<\/span><br \/>\n<span style=\"color: #800000;\">which can be regarded as close to completed fertility. The results<\/span><br \/>\n<span style=\"color: #800000;\">are given in rows 4 and 5 for white and black women and show<\/span><br \/>\n<span style=\"color: #800000;\">that the correlations between intelligence and fertility are still<\/span><br \/>\n<span style=\"color: #800000;\">significantly negative and are higher for black women (-0.226)<\/span><br \/>\n<span style=\"color: #800000;\">than for white women (-0.062). These correlations are probably<\/span><br \/>\n<span style=\"color: #800000;\">underestimates because the samples excluded high-school<\/span><br \/>\n<span style=\"color: #800000;\">dropouts, who were about 14 per cent of whites and 26 per cent<\/span><br \/>\n<span style=\"color: #800000;\">of blacks at this time, and who likely had low IQs and high<\/span><br \/>\n<span style=\"color: #800000;\">average fertility. <span style=\"color: #000000;\">(p. 201-2)<\/span><br \/>\n<\/span><\/p>\n<p>which is to say that if one gathers the data before women are done having children, one will miss out some older women who get children late. since such women are especially likely to be well-educated (and hence, smart), this is an important bias.<\/p>\n<p>still given that there <em>are<\/em> some consistent negative correlations, then there is a dysgenic effect &#8211; its just smaller than i had imagined. at least on a within population basis.<\/p>\n<p>&#8211;<\/p>\n<p><span style=\"color: #800000;\">It would be interesting to explore to what extent differences<\/span><br \/>\n<span style=\"color: #800000;\">in geographical circumstances and water resources affect the<\/span><br \/>\n<span style=\"color: #800000;\">access to clean water, but unfortunately it is difficult to find<\/span><br \/>\n<span style=\"color: #800000;\">appropriate indicators of geographical factors. However, there is<\/span><br \/>\n<span style=\"color: #800000;\">one indicator for this purpose.WDI-09 (Table 3.5) includes data<\/span><br \/>\n<span style=\"color: #800000;\">on renewable internal freshwater resources per capita in cubic<\/span><br \/>\n<span style=\"color: #800000;\">metres in 2007 (Freshwater). It measures internal renewable<\/span><br \/>\n<span style=\"color: #800000;\">resources (internal river flows and groundwater from rainfall) in<\/span><br \/>\n<span style=\"color: #800000;\">the country. It is noted that these &#8220;estimates are based on different<\/span><br \/>\n<span style=\"color: #800000;\">sources and refer to different years, so cross-country<\/span><br \/>\n<span style=\"color: #800000;\">comparisons should be made with caution&#8221; (WDI-09, p. 153). It<\/span><br \/>\n<span style=\"color: #800000;\">could be assumed that freshwater resources per capita are<\/span><br \/>\n<span style=\"color: #800000;\">negatively correlated with Water-08, but in fact there is no<\/span><br \/>\n<span style=\"color: #800000;\">correlation between these variables (0.050, N=139). The<\/span><br \/>\n<span style=\"color: #800000;\">correlation between national IQ and Freshwater is also in zero<\/span><br \/>\n<span style=\"color: #800000;\">(0.014, N=147). Access to clean water seems to be completely<\/span><br \/>\n<span style=\"color: #800000;\">independent from freshwater resources, whereas it is<\/span><br \/>\n<span style=\"color: #800000;\">significantly dependent on national IQ (39%) and several<\/span><br \/>\n<span style=\"color: #800000;\">environmental variables. Therefore, it is interesting to see how<\/span><br \/>\n<span style=\"color: #800000;\">well national IQ explains the variation in Water-08 at the level of<\/span><br \/>\n<span style=\"color: #800000;\">single countries and what kinds of countries deviate most from<\/span><br \/>\n<span style=\"color: #800000;\">the regression line. Figure 8.1 summarizes the results of the<\/span><br \/>\n<span style=\"color: #800000;\">regression analysis of Water-08 on national IQ in the group of<\/span><br \/>\n<span style=\"color: #800000;\">166 countries. Detailed results for single countries are reported in<\/span><br \/>\n<span style=\"color: #800000;\">Table 8.3. <span style=\"color: #000000;\">(p. 246)<\/span><br \/>\n<\/span><\/p>\n<p>Very interesting! Is this a direct disproof of <a href=\"https:\/\/en.wikipedia.org\/wiki\/Guns,_Germs,_and_Steel\">Jared Diamond (1997)<\/a>&#8216;s environment theory regarding access to water?<\/p>\n<p><span style=\"color: #800000;\">Figure 8.1 shows that the relationship between national IQ<\/span><br \/>\n<span style=\"color: #800000;\">and Water-08 is linear as hypothesized, but many highly<\/span><br \/>\n<span style=\"color: #800000;\">deviating countries weaken the relationship. In the countries<\/span><br \/>\n<span style=\"color: #800000;\">above the regression line, the percentage of people without<\/span><br \/>\n<span style=\"color: #800000;\">access to improved water services is higher than expected on the<\/span><br \/>\n<span style=\"color: #800000;\">basis of the regression equation, and in the countries below the<\/span><br \/>\n<span style=\"color: #800000;\">regression line it is lower than expected. In all countries above<\/span><br \/>\n<span style=\"color: #800000;\">the national IQ level of 90, the percentage of the population<\/span><br \/>\n<span style=\"color: #800000;\">without access to clean water is zero or near zero, except in<\/span><br \/>\n<span style=\"color: #800000;\">Cambodia, China and Mongolia, whereas this percentage varies<\/span><br \/>\n<span style=\"color: #800000;\">greatly in the countries below the national IQ level of 85.<\/span><br \/>\n<span style=\"color: #800000;\">National IQ is not able to explain the great variation in Water-08<\/span><br \/>\n<span style=\"color: #800000;\">in the group of countries with low national IQs. Most of that<\/span><br \/>\n<span style=\"color: #800000;\">variation seems to be due to some environmental and local<\/span><br \/>\n<span style=\"color: #800000;\">factors, perhaps also to measurement errors. <span style=\"color: #000000;\">( p. 247-8)<\/span><br \/>\n<\/span><\/p>\n<p>in the case of China it seems very unhelpful to category it as one country. it is a HUGE place. it wud be better to split it up into provinces, and calculate these instead. <a href=\"https:\/\/en.wikipedia.org\/wiki\/Provinces_of_the_People%27s_Republic_of_China\">https:\/\/en.wikipedia.org\/wiki\/Provinces_of_the_People%27s_Republic_of_China<\/a> altho this will result in many of them having no data. i doubt that there is IQ data for all the regions of China. perhaps those in the regions away from the ocean are not quite as clever as those near the ocean, and near Japan. but surely there is data about Hong Kong, Macau, and some other city or city-like states.<\/p>\n<p>&#8211;<\/p>\n<p>one thing that bothers me a bit is that when LV discuss outliers to their correlation, they use some seemingly arbitrarily picked number. heres a random example (p. 258):<\/p>\n<p><span style=\"color: #800000;\">Table 8.3 shows the countries which deviate most from the<\/span><br \/>\n<span style=\"color: #800000;\">regression line and for which positive or negative residuals are<\/span><br \/>\n<span style=\"color: #800000;\">large. An interesting question is whether some systematic<\/span><br \/>\n<span style=\"color: #800000;\">differences between large positive and negative outliers could<\/span><br \/>\n<span style=\"color: #800000;\">help to explain their deviations from the regression line. Let us<\/span><br \/>\n<span style=\"color: #800000;\">regard as large outliers countries whose residuals are \u00b115 or<\/span><br \/>\n<span style=\"color: #800000;\">higher (one standard deviation is 13).<\/span><\/p>\n<p>they note that the sd is 13, but instead opt to use 15 without an explanation. this is the same every time they adopt such an analysis, which do they every chapter. normally, they choose some number slightly larger than 1sd. in p. 155 sd = 1.7, and they use 2. in p. 146 they use 11 while sd = 10.1. in p. 103 they use 12 while the sd is 12.017. the general rule seems to be: choose an arbitrary but nicely looking number just a bit larger than the sd. i dont think this skews the analysis much, but i wud have prefered just if they used 1sd as the border for counting as an outlier.<\/p>\n<p>&#8211;<\/p>\n<p>one odd thing is that when LV finds that a relationship between national IQs and some other variable is curvilinear, they still go on to use the linear model in their explanation. they do this time and time again. it results in some bad points of analysis, for instance:<\/p>\n<p><span style=\"color: #800000;\">It is remarkable that this group does not include any<\/span><br \/>\n<span style=\"color: #800000;\">economically highly developed countries, Caribbean tourist<\/span><br \/>\n<span style=\"color: #800000;\">countries, Latin American countries, or oil exporting countries.<\/span><br \/>\n<span style=\"color: #800000;\">Most of them are poor sub-Saharan African countries (17). <strong>China<\/strong><\/span><br \/>\n<strong><span style=\"color: #800000;\">is not really a large positive outlier for the reason that its<\/span><\/strong><br \/>\n<span style=\"color: #800000;\"><strong>predicted value of Water-08 is negative -6.<\/strong> The other eight<\/span><br \/>\n<span style=\"color: #800000;\">positive outliers are poor Asian and Oceanian countries. Most of<\/span><br \/>\n<span style=\"color: #800000;\">them (especially Afghanistan, Cambodia, Myanmar and Timor-<\/span><br \/>\n<span style=\"color: #800000;\">Leste) have suffered from serious civil wars, which have<\/span><br \/>\n<span style=\"color: #800000;\">hampered socio-economic development. <span style=\"color: #000000;\">(p.259)<\/span><\/span><\/p>\n<p>if they had made a proper model, one where negative values are impossible, then they wud have avoided such details. its not that LV doesnt know this, as they discuss on page. 79:<\/p>\n<p><span style=\"color: #800000;\">Rows 13 through 18 give six correlations between national<\/span><br \/>\n<span style=\"color: #800000;\">IQs and various measures of per capita income reported. The<\/span><br \/>\n<span style=\"color: #800000;\">author analyzed further the relationship by fitting linear, quadratic<\/span><br \/>\n<span style=\"color: #800000;\">and exponential curves to the data for 81 and 185 nations and<\/span><br \/>\n<span style=\"color: #800000;\">found that fitting exponential curves gave the best results. His<\/span><br \/>\n<span style=\"color: #800000;\">interpretation was that &#8220;a given increment in IQ, anywhere along<\/span><br \/>\n<span style=\"color: #800000;\">the IQ scale, results in a given percentage in GDP, rather than a<\/span><br \/>\n<span style=\"color: #800000;\">given dollar increase as linear fitting would predict&#8221; (Dickerson,<\/span><br \/>\n<span style=\"color: #800000;\">2006, p. 291). He suggests that<\/span><\/p>\n<p style=\"padding-left: 30px;\"><span style=\"color: #800000;\">exponential fitting of GDP to IQ is logically<\/span><br \/>\n<span style=\"color: #800000;\">meaningful as well as mathematically valid. It is<\/span><br \/>\n<span style=\"color: #800000;\">inherently reasonable that a given increment of IQ<\/span><br \/>\n<span style=\"color: #800000;\">should improve GDP by the same proportional ratio,<\/span><br \/>\n<span style=\"color: #800000;\">not the same number of dollars. An increase of GDP<\/span><br \/>\n<span style=\"color: #800000;\">from $500 to $600 is a much more significant change<\/span><br \/>\n<span style=\"color: #800000;\">than is a linear increase from $20,000 to $20,100. The<\/span><br \/>\n<span style=\"color: #800000;\">same proportional change would increase $20,000 to<\/span><br \/>\n<span style=\"color: #800000;\">$24,000. These data tell us that the influence of<\/span><br \/>\n<span style=\"color: #800000;\">increasing IQ is a proportional effect, not an absolute<\/span><br \/>\n<span style=\"color: #800000;\">one <span style=\"color: #000000;\">(p. 294).<\/span><\/span><\/p>\n<p>heres as example of a plot where LV acknowledges that it is curvilinear:<\/p>\n<p><a href=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/ScreenHunter_06-Oct.-18-15.40.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-thumbnail wp-image-3333\" title=\"ScreenHunter_06 Oct. 18 15.40\" src=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/ScreenHunter_06-Oct.-18-15.40-150x150.png\" alt=\"\" width=\"150\" height=\"150\" \/><\/a><\/p>\n<p>i wud replicate this plot myself and fit an exponential function to it, and then look for outliers, but i wud need the raw data for that in a useable form. see the previous point about how it is difficult to extract the data from the PDF and the need to publish it in some other format, preferably excel\/calc.<\/p>\n<p>&#8211;<\/p>\n<p><span style=\"color: #800000;\">Some systematic differences in the characteristics of large<\/span><br \/>\n<span style=\"color: #800000;\">positive and negative outliers provide partial explanations for<\/span><br \/>\n<span style=\"color: #800000;\">their large residuals. Most countries with large negative residuals<\/span><br \/>\n<span style=\"color: #800000;\">have benefitted from investments, technologies, and<\/span><br \/>\n<span style=\"color: #800000;\">management from countries of higher national IQs, whereas<\/span><br \/>\n<span style=\"color: #800000;\">most countries with large positive residuals have received much<\/span><br \/>\n<span style=\"color: #800000;\">less such foreign help.<\/span> (p.260)<\/p>\n<p>tourism is not the only way to receive money from the rich countries. it wud be interesting to look at the effects of foreign aid to poor countries. is there any discernible effect of it? perhaps it has had effects on water supply, for instance.<\/p>\n<p>&#8211;<\/p>\n<p><span style=\"color: #800000;\">Table 8.4 shows that the indicators of sanitation are a little<\/span><br \/>\n<span style=\"color: #800000;\">more strongly correlated with national IQ than the indicators of<\/span><br \/>\n<span style=\"color: #800000;\">water (cf. Table 8.2). The explained part of variation varies from<\/span><br \/>\n<span style=\"color: #800000;\">41 to 60 percent. Differences between the three groups of<\/span><br \/>\n<span style=\"color: #800000;\">countries are relatively small, although the correlations are<\/span><br \/>\n<span style=\"color: #800000;\">strongest in the group of countries with more than one million<\/span><br \/>\n<span style=\"color: #800000;\">inhabitants. It should be noted that the correlations between<\/span><br \/>\n<span style=\"color: #800000;\">national IQ and Sanitation-08 are negative because Sanitation-08<\/span><br \/>\n<span style=\"color: #800000;\">concerns the percentage of the population without access to<\/span><br \/>\n<span style=\"color: #800000;\">improved sanitation services (see section 2).<\/span> (p. 261)<\/p>\n<p>i understand their wish to stay true to the sources numbers, but i wud have prefered if they had multiplied the numbers by -1 to make them fit with the direction of the other numbers.<\/p>\n<p>&#8211;<\/p>\n<p><span style=\"color: #800000;\">Row 7 gives a low but statistically significant positive<\/span><br \/>\n<span style=\"color: #800000;\">correlation of 0.18 between national IQ and son preference. This<\/span><br \/>\n<span style=\"color: #800000;\">may be a surprising result, because it might be expected that<\/span><br \/>\n<span style=\"color: #800000;\">liberal and more modern populations would not have such a<\/span><br \/>\n<span style=\"color: #800000;\">strong preference for sons as more traditional peoples.<\/span> (p. 273)<\/p>\n<p>surprising indeed.<\/p>\n<p>&#8211;<\/p>\n<p><span style=\"color: #800000;\">Consistent with Frazer&#8217;s analysis, it has been found in a<\/span><br \/>\n<span style=\"color: #800000;\">number of studies of individuals within nations that there is a<\/span><br \/>\n<span style=\"color: #800000;\">negative relationship between intelligence and religious belief.<\/span><br \/>\n<span style=\"color: #800000;\">This negative relationship was first reported in the United States<\/span><br \/>\n<span style=\"color: #800000;\">in the 1920s by Howells (1928) and Sinclair (1928), who both<\/span><br \/>\n<span style=\"color: #800000;\">reported studies showing negative correlations between<\/span><br \/>\n<span style=\"color: #800000;\">intelligence and religious belief among college students of -0.27<\/span><br \/>\n<span style=\"color: #800000;\">to -0.36 (using different measures of religious belief). A number<\/span><br \/>\n<span style=\"color: #800000;\">of subsequent studies confirmed these early results, and a review<\/span><br \/>\n<span style=\"color: #800000;\">of 43 of these studies by Bell (2002) found that all but four found<\/span><br \/>\n<span style=\"color: #800000;\">a negative correlation. To these can be added a study in the<\/span><br \/>\n<span style=\"color: #800000;\">Netherlands of a nationally representative sample (total N=1,538)<\/span><br \/>\n<span style=\"color: #800000;\">that reported that agnostics scored 4 IQs higher than believers<\/span><br \/>\n<span style=\"color: #800000;\">(Verhage, 1964). In a more recent study Kanazawa (2010) has<\/span><br \/>\n<span style=\"color: #800000;\">analyzed the data of the American National Longitudinal Study of<\/span><br \/>\n<span style=\"color: #800000;\">Adolescent Health, a national sample initially tested for<\/span><br \/>\n<span style=\"color: #800000;\">intelligence with the PPVT (Peabody Picture Vocabulary Test) as<\/span><br \/>\n<span style=\"color: #800000;\">adolescents and interviewed as young adults in 2001-2<\/span><br \/>\n<span style=\"color: #800000;\">(N=14,277). At this interview they were asked: &#8220;To what extent<\/span><br \/>\n<span style=\"color: #800000;\">are you a religious person?&#8221; The responses were coded &#8220;not<\/span><br \/>\n<span style=\"color: #800000;\">religious at all&#8221;, &#8220;slightly religious&#8221;, &#8220;moderately religious&#8221;, and<\/span><br \/>\n<span style=\"color: #800000;\">&#8220;very religious&#8221;. The results showed that the &#8220;not religious at all&#8221;<\/span><br \/>\n<span style=\"color: #800000;\">group had the highest IQ (103.09), followed in descending order<\/span><br \/>\n<span style=\"color: #800000;\">by the other three groups (IQs = 99.34, 98.28, 97.14). The<\/span><br \/>\n<span style=\"color: #800000;\">negative relationship between IQ and religious belief is highly<\/span><br \/>\n<span style=\"color: #800000;\">statistically significant.<\/span> (p. 278)<\/p>\n<p>the Bell article sounds interesting, but after spending some time trying to locate it, i failed. it seems that <a href=\"http:\/\/www.theflatearthsociety.org\/forum\/index.php?topic=10570.0#top\">im not the only one having such problems<\/a>.<\/p>\n<p>regardless of that, there was a similar article: &#8220;The Effect of Intelligence on Religious Faith,&#8221; <a href=\"http:\/\/www.secularhumanism.org\/fi\/\"><em>Free Inquiry<\/em><\/a>, Spring 1986: (1). There is an online parafrase of it <a href=\"http:\/\/kspark.kaist.ac.kr\/jesus\/intelligence%20&amp;%20religion.htm\">here<\/a>.<\/p>\n<p>&#8211;<\/p>\n<p><a href=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/ScreenHunter_07-Oct.-18-19.01.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-thumbnail wp-image-3335\" title=\"ScreenHunter_07 Oct. 18 19.01\" src=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/ScreenHunter_07-Oct.-18-19.01-150x150.png\" alt=\"\" width=\"150\" height=\"150\" \/><\/a><\/p>\n<p>one of the interesting datasets that id love to see a nonlinear function fitted to. i want to know how much we need to boost intelligence to almost remove religiousness. perhaps one can discover this from using high-IQ samples. at which IQ are there &lt;5% religious people?<\/p>\n<p>&#8211;<\/p>\n<p><a href=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/ScreenHunter_08-Oct.-18-22.56.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-thumbnail wp-image-3336\" title=\"ScreenHunter_08 Oct. 18 22.56\" src=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/ScreenHunter_08-Oct.-18-22.56-150x150.png\" alt=\"\" width=\"150\" height=\"150\" \/><\/a><\/p>\n<p>another of those tables that have problems with the direction. Legatum and Newsweek shud be positive with each other, right? since they are measuring in the same direction, that is, the one opposite of HDI and IHC (which correlate positively).<\/p>\n<p>&#8211;<\/p>\n<p>LV mention the 2008 study by Kanazawa: <a href=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/Temperature-and-evolutionary-novelty-as-forces-behind-the-evolution-of-general-intelligence.pdf\">Temperature and evolutionary novelty as forces behind the evolution of general intelligence<\/a>. The interesting thing about this study is that it sort of tests my idea that <a href=\"http:\/\/emilkirkegaard.dk\/en\/?p=3317\">i wrote about earlier<\/a>. Kanazawa goes on with his novelty hypothesis using distance from Africa to predict national IQs. However, compared with Ashraf and Galor (2012) paper, he just uses bird distance instead of actual travel distance (humans are not birds, after all!, nor did they just sail straight from Africa to populate America). So im not really sure what his computed r&#8217;s are useful for. It wud be interesting to add together the data from the Ashraf and Galor (2012) paper about distances, and genetic diversity to the climate model. LV does mention at one point that lack of genetic diversity make evolution slower:<\/p>\n<p><span style=\"color: #800000;\">A further<\/span><br \/>\n<span style=\"color: #800000;\">anomaly is that the Australian Aborigines inhabit a relatively<\/span><br \/>\n<span style=\"color: #800000;\">warm region but have small brain sizes and low IQs. The<\/span><br \/>\n<span style=\"color: #800000;\">explanation for this anomaly is that these were a small isolated<\/span><br \/>\n<span style=\"color: #800000;\">population numbering only around 300,000 at the time of<\/span><br \/>\n<span style=\"color: #800000;\">European colonization, so the mutant alleles for higher IQs did<\/span><br \/>\n<span style=\"color: #800000;\">not appear in them.<\/span> (p. 381)<\/p>\n<p>consider also the criticism of Kanazawa&#8217;s paper in <em><a href=\"http:\/\/emilkirkegaard.dk\/en\/wp-content\/uploads\/Why-national-IQs-do-not-support-evolutionary-theories-of-intelligence.pdf\">Why national IQs do not support evolutionary theories of intelligence<\/a><\/em>, Wicherts et al (2009):<\/p>\n<p><span style=\"color: #800000;\"><strong>5. Migration and geographic distance<\/strong><\/span><br \/>\n<span style=\"color: #800000;\">Kanazawa (2008) was concerned with the relation between lev-<\/span><br \/>\n<span style=\"color: #800000;\">els of general intelligence, as they were distributed geographically<\/span><br \/>\n<span style=\"color: #800000;\">thousands of years ago, and the degree of \u2018\u2018evolutionary novelty\u201d of<\/span><br \/>\n<span style=\"color: #800000;\">the relevant geographic locations. Lacking data regarding evolu-<\/span><br \/>\n<span style=\"color: #800000;\">tionary novelty, Kanazawa proposed, as a measure of evolutionary<\/span><br \/>\n<span style=\"color: #800000;\">novelty, the geographic distance to the EEA, i.e., a large region of<\/span><br \/>\n<span style=\"color: #800000;\">sub-Saharan Africa. The idea is that the greater the distance from<\/span><br \/>\n<span style=\"color: #800000;\">the EEA, the more evolutionarily novel the corresponding environ-<\/span><br \/>\n<span style=\"color: #800000;\">ment. There are several problems with this operationalization.<\/span><br \/>\n<span style=\"color: #800000;\">First, Kanazawa operationalized geographic distance using<\/span><br \/>\n<span style=\"color: #800000;\">Pythagoras\u2019 \ufb01rst theorem (a<sup>2<\/sup>+ b<sup>2<\/sup>= c<sup>2<\/sup>). However, Pythagoras\u2019 theo-<\/span><br \/>\n<span style=\"color: #800000;\">rem applies to Euclidian space, not to the surface of a sphere. Sec-<\/span><br \/>\n<span style=\"color: #800000;\">ond, even if these calculations were accurate, distances as traveled<\/span><br \/>\n<span style=\"color: #800000;\">on foot do not in general correspond to distances \u2018\u2018as the crow \ufb02ies\u201d<\/span><br \/>\n<span style=\"color: #800000;\">(Kanazawa 2008, p. 102). According to most theories, ancestors of<\/span><br \/>\n<span style=\"color: #800000;\">the indigenous people in Australia (i.e., the Aborigines) moved out<\/span><br \/>\n<span style=\"color: #800000;\">of Africa on foot. They probably crossed the Red Sea from Africa to<\/span><br \/>\n<span style=\"color: #800000;\">present day Saudi Arabia, went on to India, and then through Indo-<\/span><br \/>\n<span style=\"color: #800000;\">nesia to Australia. Thus the distance covered on foot must have<\/span><br \/>\n<span style=\"color: #800000;\">been much larger than the distances computed by Kanazawa. This<\/span><br \/>\n<span style=\"color: #800000;\">suggests that the real distances covered by humans to reach a gi-<\/span><br \/>\n<span style=\"color: #800000;\">ven location, i.e., data of central interest to Kanazawa, are likely<\/span><br \/>\n<span style=\"color: #800000;\">to differ appreciably from the distances as the crow \ufb02ies. One<\/span><br \/>\n<span style=\"color: #800000;\">can avoid this problem by using maps that exist of the probable<\/span><br \/>\n<span style=\"color: #800000;\">routes that humans followed in their exodus from Africa, and esti-<\/span><br \/>\n<span style=\"color: #800000;\">mating the distances between the cradle of humankind and various<\/span><br \/>\n<span style=\"color: #800000;\">other locations accordingly (Relethford, 2004).<\/span><br \/>\n<span style=\"color: #800000;\">Third, it is not obvious that locations farther removed from the<\/span><br \/>\n<span style=\"color: #800000;\">African Savannah are geographically and ecologically more dissim-<\/span><br \/>\n<span style=\"color: #800000;\">ilar than locations closer to the African Savannah. For instance, the<\/span><br \/>\n<span style=\"color: #800000;\">rainforests of central Africa or the mountain ranges of Morocco are<\/span><br \/>\n<span style=\"color: #800000;\">relatively close to the Savannah, but arguably are more dissimilar<\/span><br \/>\n<span style=\"color: #800000;\">to it than the great plains of North America or the steppes of Mon-<\/span><br \/>\n<span style=\"color: #800000;\">golia. In addition, some parts of the world were quite similar to the<\/span><br \/>\n<span style=\"color: #800000;\">African savannas during the relevant period of evolution (e.g., Ray<\/span><br \/>\n<span style=\"color: #800000;\">&amp; Adams, 2001). Clearly, there is no strict correspondence between<\/span><br \/>\n<span style=\"color: #800000;\">evolutionary novelty and geographic distance. This leaves the use<\/span><br \/>\n<span style=\"color: #800000;\">of distances in need of theoretical justi\ufb01cation. It is also notewor-<\/span><br \/>\n<span style=\"color: #800000;\">thy that given the time span of evolutionary theories, it is hardly<\/span><br \/>\n<span style=\"color: #800000;\">useful to speak of environmental effects as if these were \ufb01xed at<\/span><br \/>\n<span style=\"color: #800000;\">a certain geographical location.<\/span><br \/>\n<span style=\"color: #800000;\">People migrate, and have done so extensively in the time since<\/span><br \/>\n<span style=\"color: #800000;\">the evolutionarily period relevant to the evolutionary theories by<\/span><br \/>\n<span style=\"color: #800000;\">Kanazawa and others. A simple, yet imperfect, solution to this<\/span><br \/>\n<span style=\"color: #800000;\">problem is to use data solely from countries that have predomi-<\/span><br \/>\n<span style=\"color: #800000;\">nantly indigenous inhabitants (Templer, 2008; Templer &amp; Arika-<\/span><br \/>\n<span style=\"color: #800000;\">wa, 2006). However, Kanazawa used national IQs of all<\/span><br \/>\n<span style=\"color: #800000;\">countries in Lynn and Vanhanen\u2019s survey, including Australia<\/span><br \/>\n<span style=\"color: #800000;\">and the United States. This casts further doubt on the relevance<\/span><br \/>\n<span style=\"color: #800000;\">of Kanazawa\u2019s data vis-\u00e0-vis the evolutionary theories that he<\/span><br \/>\n<span style=\"color: #800000;\">set out to test. Given persistent migration, it is likely that many<\/span><br \/>\n<span style=\"color: #800000;\">of the people, whose test scores Lynn and Vanhanen used to cal-<\/span><br \/>\n<span style=\"color: #800000;\">culate national IQs, are genetically unrelated to the original<\/span><br \/>\n<span style=\"color: #800000;\">inhabitants of their respective countries. In at least 50 of the<\/span><br \/>\n<span style=\"color: #800000;\">192 countries in Kanazawa\u2019s (2008) study, the indigenous people<\/span><br \/>\n<span style=\"color: #800000;\">represent the ethnic minority.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Richard Lynn was so kind to send me a signed copy of his latest book. i immediately paused the reading of another book to read this one. some comments and quotes are below. quotes are from the ebook version of the book which i found on the internet. Richard Lynn, Tatu Vanhanan &#8211; Intelligence, a [&hellip;]<\/p>\n","protected":false},"author":17,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1839,1898,1746,1624,1690,1921],"tags":[298,1711,1712],"class_list":["post-3328","post","type-post","status-publish","format-standard","hentry","category-psychometics","category-economics","category-evolutionary-biology","category-evolutionary-psychology","category-genetics","category-sociology","tag-download","tag-ebook","tag-free","entry"],"_links":{"self":[{"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/posts\/3328","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/users\/17"}],"replies":[{"embeddable":true,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/comments?post=3328"}],"version-history":[{"count":7,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/posts\/3328\/revisions"}],"predecessor-version":[{"id":3339,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/posts\/3328\/revisions\/3339"}],"wp:attachment":[{"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/media?parent=3328"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/categories?post=3328"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/tags?post=3328"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}