Education: Black Caribbean children held back by institutional racism [Of course! It couldn’t be because they have low I.Q.’s and behavioral problems! Just like Negroes everywhere… It’s always the White man’s fault when little stupid and violent darky can’t hack it!]

Ready for homework?

The solution? Return them to their native countries… No white racism there, because no white people…and we all know how well Negro/Caribbean children perform in their natural habitat!

When will we finally see a truthful study that plainly states that Negroes have low I.Q.’s, cannot delay gratification or control their impulses, and show sociopathic character traits?

Continue reading Education: Black Caribbean children held back by institutional racism [Of course! It couldn’t be because they have low I.Q.’s and behavioral problems! Just like Negroes everywhere… It’s always the White man’s fault when little stupid and violent darky can’t hack it!]…

Big-brained people are smarter: A meta-analysis of the relationship [Michael A. McDaniel]

The relationship between brain volume and intelligence has been a topic of a scientific debate since at least the 1830s. To address the debate, a meta-analysis of the relationship between in vivo brain volume and intelligence was conducted. Based on 37 samples across 1530 people, the population correlation was estimated at 0.33. The correlation is higher for females than males. It is also higher for adults than children. For all age and sex groups, it is clear that brain volume is positively correlated with intelligence.

Read the article here:

brain-size-mcdaniel.pdf

See also for a basic understanding of the issue regarding brain size and intelligence/ behavioral complexity (and other very interesting subjects) serendip.

I don’t find anything presented there that contradicts anything regarding brain size, which is measured in various ways, but most accurately linked to intelligence or behavioral complexity via EQ. Most interestingly, the site appears to consider “intelligence” and “behavioral complexity” synonymous (caveat: I haven’t completed an entire search of the site).

How important is the role of intelligence in the rise of civilization?

by Maria T. Phelps, University of Western Ontario

Abstract : Looks at the importance of intelligence in the rise of civilization. Racial differences in test scores as a reflection in the rise of civilization; Agriculture as a necessary precursor of civilization; Technological and social innovations as a result of a multiple causative network; Conceptualization of civilization as an event.

Lynn (1991b) contends that racial differences in intelligence test scores are also reflected in the rise of civilization. During the Neolithic period, only Mongoloids and Caucasoids exhibited all the defining characteristics of civilization such as agriculture, writing and number systems. In contrast to Negroid populations, Mongoloid and Caucasoid populations were exposed to the extreme cold of the main Wurm glaciation, resulting in a process of selection in favor of higher intelligence in the populations occupying the Eurasiatic land mass. Lynn (1991ab) suggests that this increase in intelligence was the causative agent responsible for the rise of civilization. The author argues, however, that although intelligence might be a necessary condition for the rise of civilization, it is not by itself a sufficient reason. She argues, that agriculture, a necessary precursor of civilization, developed when hunting and gathering were no longer ecologically viable. The technological and social innovations that followed were the result of a multiple causative network and cannot be attributed solely to increased intelligence. Finally, the problems of conceptualizing civilization as an event instead of a process are discussed.

An analysis of global intelligence test scores conducted by Lynn (1991b) revealed that Mongoloids living in North America and Asia obtain higher mcan IQ scores (101-108) than North American or European Caucasoids (100), and Caucasoids obtain higher mean IQ scores than American-Negroid (85) or African-Negroid (70) populations. Because intelligence is highly heritable (e.g., Bouchard, Lykken, McGec, Segal & Tellegen, 1990), Lynn (1991ab) argued that these differences in intelligence are genetically based. Rushton (1988) has expanded the list of heritable factors that serve to differentiate the three races to include physiological, reproductive and personality variables. Further, a number of studies examining the relationship between reaction time and intelligence also indicate a similar ordering of the three races, with Mongoloids exhibiting faster reaction times than Caucasoids and Negroids, respectively.

This latter finding is particularly noteworthy in two respects. One, reaction time is a measure that is unaffected by experience. Two, other studies, not concerned with the ranking of the races by intelligence, have demonstrated that reaction time is positively associated with intelligence (Vernon, 1993). The universality of racial differences in IQ test scores and reaction time measures supports Lynn’s (1991ab) claim that the explanation for these differences cannot be solely accounted for by environmental factors such as social and economic conditions.

Lynn (1991b) then makes the claim that racial differences in intelligence are reflected both in the level and complexity of civilization attained by the three races. He reasons that if scientific, intellectual and technological innovations are made by a few highly intelligent individuals then there will be more of these in a population where average intelligence is high. Consequently, Lynn argues (1991a) that Mongoloid and to a lesser extent Caucasoid populations, in contrast to Negroid populations, exhibited all the defining characteristics of civilization such as agriculture, mathematics, legal, ethical and religious systems. According to Lynn (1991ab) the level of intelligence necessary to create civilization, however, was not to be attained until the Neolithic period, approximately 9,000 years ago. The problems of survival during periods of extreme cold caused by the main Wurm glaciation (24,000-10,000 years ago) was the selective force that produced further increases in intelligence in Caucasoid and Mongoloid populations and this increase in intelligence laid the foundation upon which civilization is built (Lynn, 1991ab). Because Negroid population were not exposed to the main Warm glaciation, they did not undergo a transformation in intelligence that was a necessary precondition for the rise of civilization (Lynn, 1991ab).

It is only the latter point, that civilization is an intellectual achievement, that this author takes issue with. Most anthropologists feel that agriculture is the necessary first step toward urbanization and complex social and political systems that characterize civilization (Childe, 1967; Fiedel, 1992; Flannery, 1969; Hardesty, 1977; Henry, 1989; Layton, Foley & Williams, 1991; Redding, 1988; McCorriston & Hole, 1991; Perkins & Daly, 1974; Stigler, 1974). The adoption of agriculture as a subsistence mode occurred because hunting and gathering were no longer ecologically or economically feasible (Fiedel, 1992; Henry, 1988; Layton et al., 1991; Redding, 1988; McCorriston & Hole, 1991; Perkins & Daly, 1974). The explosion of cultural innovations that followed, for example, writing, number systems, standardization of measurement, and astronomy, were attempts to adapt to the changes brought about by the new agricultural economy by creating new tools (Childe, 1967; Fiedel, 1992; Flannery, 1969; Hardesty, 1977; Henry, 1989; Redding, 1988; Perkins & Daly, 1974; Stigler, 1974). It will be argued that the technological, organizational and ideological changes associated with the rise of civilization are the products of a multiple causative network and can not be attributed to a single causative agent, such as intelligence.

Agriculture: The Best of a Bad Job Strategy

Lynn (1991a) postulates that his theory solves a problem that has long perplexed anthropologists, namely why didn’t civilization and its precursor, agriculture, occur prior to the Neolithic revolution? Lynn (1991a) suggests that the reason is because prior to 10,000 years ago Homo sapiens had not attained a level of intelligence high enough to invent civilization. I argue that the reason why agriculture and civilization did not occur between 200,000-10,000 years ago is more likely due to the fact that the precultigens (i.e., ancestral populations of the major cereal grains, maize etc.) were absent because of the prevailing climatic conditions of the Pleistocene (Fiedel, 1992; Henry, 1989; Layton et al., 1991). To put it more simply, it is difficult to have agriculture as a subsistence mode when the plant resource base has not come into existence. The precultigens were selected by the early farmers because their short reproductive cycles and self-fertilization were easily manipulated, thus making them ideal candidates for domestication (McCorriston & Hole, 1991).

What has perplexed anthropologists, however, are two anomalies in the archaeological record of early farming communities in both the New and Old World. One, the archaeological record of early farming communities show that agriculture did not arise in lush environments but rather in marginal, arid semi-desertic ecological zones (Fiedel, 1992; Henry, 1989). The second anomaly concerns the apparent ill-health of the early farming populations, relative to both ancient and modern hunter-gatherers (Fiedel, 1992; Henry, 1989; Layton et al., 1991). For example, skeletal remains of early farmers exhibit numerous instances of nutritionally based and infectious diseases. The question that anthropologists ask is why did humans abandon the previously successful subsistence mode of hunting and gathering and switch to agriculture? One answer is that these early farmers had no choice. The changes in the prevailing climatic and environmental conditions in combination with increasing population size forced these people to abandon hunting and gathering and adopt an alternative subsistence mode, agriculture, in order to survive (Fiedel, 1991; Henry, 1989; Layton et al., 1991; McCorriston & Hole, 1991; Redding, 1989). Further, the mass extinction of the megafauna due to increasing aridity of the climate also necessitated the broadening of the resource base to include the harvesting of vegetal material.

In order to maximize their rate of return from the new resource base, nomadic hunters and gatherers became sedentary, devoting more time and energy to the efficient cultivation and harvesting of the cultigens. One of the peculiar side effects to adopting a sedentary lifestyle is the consequences it has on female fertility and fecundity. Because fertility in females is dependent upon the body fat to body weight ratio, decreasing the time spent in the search for and pursuit of mobile food items acts to increase females’ reproductive output (Henry, 1989). In addition the switch from a high-protein, meat-based diet to a high carbohydrate, low-protein, cereal-based diet also contributed to higher body fat to body weight ratios (Henry, 1989). Once a group becomes sedentary and adopts a plant-based diet, it sets into motion a vicious cycle of increased offspring production, which in turn requires increased food production, forcing groups to develop more effective means of resource extraction. In other words, necessity is the mother of invention. It is at this point in human history that intelligent individuals can make a difference by ensuring group survival through technological or intellectual innovation. In the absence of these ecological pressures, however, I argue that there is no need to invent more effective farm tools when survival is largely dependent on a mobile meat-based resource.

Agriculture and Civilization

Agriculture propelled population growth, and as a function of a positive feedback loop, the increased population size could only be supported by the adoption of more intensive farming methods, such as irrigation, and terracing (Fiedel, 1992; Perkins & Daly, 1974; Stigler, 1974). Coincidentally, intensive agricultural practices also produced a resource surplus that enabled farmers to remain sedentary during periods of resource fluctuations (Fiedel, 1992; Henry, 1989). In contrast, hunters and gatherers typically respond to scarcity by dispersing and migrating in search of new food sources (Fiedel, 1992). In addition, the increase in intensity of land use activated the processes culminating in complex social and political institutions such as the state (Fiedel, 1992; Flannery, 1969; Hardesty, 1977; Henry, 1989; Perkins & Daly, 1974; Stigler, 1974). As land was used more intensely, there was not only an increasingly large gap between the most valuable land and the least valuable land but also a progressively smaller amount of valuable land (Fiedel, 1992; Flannery, 1969; Hardesty, 1977). For example, nearly 35% of the total land of western Iran is optimal for the hunting of ungulates (Flannery, 1969; Hardesty, 1977). However, the shift to dry farming decreased the percentage of optimal land to 10% and the shift to irrigation farming to only 1% (Flannery, 1969; Hardesty, 1977). Consequently, specialized social groups evolved for the purpose of holding and maintaining these scarce resources (Fiedel, 1992; Flannery, 1969; Hardesty, 1977; Perkins & Daly, 1974; Stigler, 1974). These specialized social groups led to new patterns of political and religious authority, class stratification, the appearance of new economic classes not directly engaged in producing their own food, and mechanisms for apportioning wealth (Fiedel, 1992; Stigler, 1974). Agricultural surpluses made this possible by feeding construction workers, religious authorities and town-dwellers (Fiedel, 1992; Perkins & Daly, 1974; Stigler, 1974). Thus, agriculture is the foundation upon which civilization is built. Agriculture necessitated social and political change that evolved to manage the scarce resource of arable land and also provided the surplus to feed those not directly involved in resource extraction. If human groups had not been forced to adopt this new subsistence mode, the infrastructure necessary to attain and sustain large groups of even highly intelligent people would be absent.

The Tools of Civilization

Contrary to popular opinion, most hunting and gathering societies possess religious, ethical and legal systems in which certain behaviors are either proscribed or prescribed by the group (Fiedel, 1992; Greenwood & Stini, 1977). What hunters and gatherers do not evidence are the stereotypical tools of civilization, writing, mathematics and astronomy, that most anthropologists typically associate with civilization. The issue that I wish to address is why these traits co-occur with urbanization and agriculture. I argue that the differing demands of civilization compared to hunting and gathering necessitated the development of these new tools. That is, the appearance of these additions to the human tool kit at this point in human history can not entirely be accounted for by an increase in the level of intelligence.

One of the most complete examples of the evolutionary history of writing is provided by the Sumerians of southern Mesopotamia. In the civic and religious buildings of these ancient peoples, the earliest clay tablets are found that record the evolution of pictographic form writing into an ideographic-cum-phonetic system, the standard cuneiform of later Mesopotamia (Stigler, 1974). The functional raison d’e tre of the writing system is readily apparent in these fossils. They are account ledgers, records of livestock and harvest yields, receipts, expenditures and wage lists (Childes, 1967; Stigler, 1974). In other words, these clay tablets document the administration of an agricultural surplus that supports specialists who do not produce food directly but rather build temples, pottery and agricultural terraces (Childes, 1967: Stigler, 1974).

The economy of mobile hunters and gatherers dictates a different pattern of adaptation because for this lifestyle the costs associated with maintaining a resource surplus can exceed the benefits (Layton et al., 1991; McCorriston & Hole, 1991; Redding, 1988). When the energetic and nutritive demands of each individual in the group are met, as is characteristic of hunter-gatherers, time and energy spent in the maintenance and defense of a resource surplus is unnecessary (Fiedel, 1992; Henry, 1989). Further, the mobility required by the hunter-gatherer resource base also prevents the maintenance and defense of the surplus from other groups (Layton et al., 1991). The assignment of individuals to activities not directly involved in food production would detract from the rate of energetic gain for the entire group (Layton et al., 1991). And, in the absence of a surplus, there is no need to document its use by those not directly involved in resource extraction.

A number system would be as necessary a tool as a writing system in order to adapt to the new economy. For hunters and gatherers, notches on a tally stick for each bison slain by a hunter would suffice (Childe, 1967; Fiedel, 1992; Stigler, 1974). For enumerating the vast herds of a religious temple or the contents of a city granary, however, such a system would be inadequate (Childe, 1967). The new economic conditions also required the creation of arithmetic and geometry in order to ascertain and predict the number of bricks to be used for the building of a new temple wall or the number of men needed to build a new terracing system (Childe, 1967; Fiedel, 1992; Stigler, 1974). Thus, the genesis for this new tool is evident in its function. It was not created to satisfy an interest in the properties of numbers as such, or in the measurement of an abstract empty space (Childe, 1967).

Similarly, astronomy was developed in order to foretell the precise time to begin agricultural operations (Childe, 1967: Fiedel, 1992; Stigler, 1974). It is not an accident that many temple structures are aligned with some star or constellation that facilitates the determination of the precise time of the spring and autumnal equinox (Childe, 1967: Fiedel, 1992). Ascertaining the length of the growing season is an important consideration for farmers because it aids in the decision of when to plant and when to harvest. A sudden frost can spell disaster for a group dependent on a plant-based resource (Layton et al., 1991). For hunter gatherers dependent on a mobile meat-based resource, a sudden change in weather is handled by dispersing early or later in the year (Fiedel, 1992). This, however, is not an option for a group of sedentary farmers who provide for their own needs as well as the needs of non-food providers.

The standardization of measurement also arose in response to the demands created by the new subsistence mode (Childe, 1967; Fiedel, 1992; Stigler, 1974). In order to construct a hand-axe the needs of a hunter and gatherer are supplied by nature — the length of a finger, or forearm would suffice (Childe, 1967). In contrast, the construction of a large temple or terracing system would be seriously hampered by the use of such measurement because not every arm is of the same length. To put it more simply, such an inaccuracy could result in some beams failing to span the temple while others would project beyond its walls (Childe, 1967).

Thus, the addition of new tools to the human tool kit occurred because of the new demands created by agriculture. What intelligence did was to ensure that these new demands or challenges were met successfully. For hunter-gatherers the use of these new tools would not be necessary and in some case would be cost-prohibitive. In other words, the intellectual capability to invent these new tools existed in Caucasoid and Mongoloid hunter-gatherer populations but it did not manifest itself in the form of writing and numerical systems until it was needed. The impetus for each new innovation and the innovations themselves are parts of an interlocking system that can not be explained by an appeal to a single causative agent, such as intelligence.

The Concept of Civilization as an Event

There may also be problems with Lynn’s (1991ab) conceptualization of civilization as an event instead of a process. Obviously, there was not a time when a group of Mongoloid or Caucasoid hunter-gatherers, huddled around the camp fire, spontaneously decided to invent civilization; yet, this scenario is implied in Lynn’s analysis. Rather than following a unilineal developmental sequence, the economic and social changes in the Old and New World are best understood in the context of consequences of an interaction of population growth and climatic environmental changes that were the catalysts for civilization (Fiedel, 1992; Henry, 1989; Layton et al., 1991; McCorriston & Hole, 1991; Redding, 1989). An ecological approach to understanding the evolution of civilization is more compatible with the evidence than an event-based hypothesis. Anthropologists long ago abandoned the view of civilization as the end product of a unilinear trend due to the existence of a phenomenon known as reversion. Reversion occurs when a previously agricultural or urban group reverts back to a hunting and gathering lifestyle because of the collapse of the agricultural infrastructure due to variety of reasons, such as over cultivation or decreasing rainfall. Contrary to an event-based model of human cultural evolution, human groups may return to a ‘primitive’ hunting and gathering subsistence mode due to changes in ecological conditions rather than a drop in intelligence. This illustrates the danger of perceiving the transition between hunting and gathering as a one-way process that in some sense constitutes a step up the evolutionary ladder.

As stated previously, the catalysts for civilization include the pressure of population growth and the scarcity of basic resources produced by the adoption of agriculture as a subsistence mode (McCorriston & Hole, 1991; Redding, 1989). In such circumstances, societies had to reorganize in order to survive. The shift to a centrally organized, stratified society may not have been the only possible solution, but it is one that has occurred independently in many parts of the world. In that sense environmental and population stress may be conceived as an event. But, the occurrence of that event is heavily predicated on the occurrence of a population and environmental stress interaction. If these two factors do not co-occur, I argue that there is no reason to adopt an alternative lifestyle.

Finally the conceptualization of civilization as an event is a double-edged sword that can also be used to impale Lynn’s (1991ab) argument. In contrast to the pattern observed in Europe, the archaeological record in China shows a 3,000 year interval between the development of agriculture and the rise of civilization. For over two centuries, Japan failed to capitalize on superior military technology (guns) despite their introduction by Westerners in the 1700’s. From an event-based perspective, these examples could be interpreted as evidence disputing north east Asians as intellectually superior to Caucasoids. By viewing civilization as an alternative subsistence mode or process, however, I suggest that Mongoloid hunter-gatherers would still obtain higher IQ scores than urban Caucasoid and Negroid populations. Based on Lynn’s (1991ab) global survey of IQ scores and reaction time measures, such an argument is not incompatible with the evidence.

Source : Mankind Quarterly, Summer94, Vol. 34 Issue 4, p287, 10p

References:

Bouchard, T. L, Lykken, D. T., McGue, M., Segal, M. L, & Tellegen, A.

1990 Sources of human psychological differences: The Minnesota study of twins reared apart. Science 250: 223-228.

Childe, G. V.

1967 The advent of civilization. In N. F. Cantor and M. S. Werthman (eds). Ancient Civilization: 4000 B.C.- 400 A.D. New York: Thomas Y. Crowell Company. Pp. 4-63.

Fiedel, S. J.

1992 Prehistory of the Americas. Cambridge: Cambridge University Press.

Flannery, K.V.

1969 Effects of early domestication in Iran and the Near East. In P. J. Ucko and G. W. Dimbleby (eds). The Domestication and Exploitation of . . . and Animals. Chicago: Aldine Press. Pp. 73-100.

Greenwood, D. J. & Stini, W. A.

1977 Nature, Climate and Human History. New York: Harper & Row Publishers.

Hardesty, D. L

1977 Ecological Anthropology. Wiley & Sons.

Henry, D.O.

1989 From Foraging to Agriculture. Philadelphia: University of Philadelphia Press.

Layton, R., Foley, R., & Williams, E.

1991 The transition between hunting and gathering and specialized husbandry to resources. Current Anthropology 32: 225-273.

Lynn, R.

1991a The evolution of racial differences in intelligence. Mankind Quarterly 32: 99-121.

1991b Race differences in intelligence: A global perspective. Mankind Quarterly 32: 225-296.

McCorriston, J., & Hole, F.

1991 The ecology of seasonal stress and the origins of agriculture in the Near East. American Anthropologist 93: 46-68.

Perkins, Jr., D., & Daly, P.

1974 The beginning of food production in the Near East. In R. Stigler (ed.). The Old World: Early Man to the Development of Agriculture. New York: St. Martin’s Press. Pp. 71-97.

Redding, R. W.

1988 A general explanation of subsistence change: From hunting and gathering to food production. Journal of Anthropological Archaeology 7: 56-97.

Rushton, J.P.

1988 Race differences in behavior: A review and evolutionary analysis. Personality & Individual Differences 9: 1009-24.

Stigler, R.

1974 The later Neolithic in the Near East and the rise of civilization. In In R. Stigler (ed.). The Old World: Early Man to the Development of Agriculture New York: St. Martin’s Press. Pp. 98-126.

Vernon, P. A.

1993 Biological Approaches to the Study of Human Intelligence. Norwood, NJ: Ablex Publishing.

Intelligence and the Wealth and Poverty of Nations

by Richard Lynn, University of Ulster, Coleraine, Northern Ireland

and Tatu Vanhanen, University of Helsinki, Finland

Summary : National IQs assessed by the Progressive Matrices were calculated for 60 nations and examined in relation to per capita incomes in the late 1990s and to post World War Two rates of economic growth. It was found that national IQs are correlated at 0.757 with real GDP (Gross Domestic Product) per capita 1998 and 0.706 with per capita GNP (Gross National Product) 1998; and at 0.605 with the growth of per capita GDP 1950-90 and 0.643 with growth of per capita GNP 1976-98. The results are interpreted in terms of a causal model in which population IQs are the major determinant of the wealth and poverty of nations in the contemporary world.

INTRODUCTION

The causes of the inequalities in income and wealth between nations have been discussed for some two and a half centuries. In 1748 Montesquieu published De l’Esprit des Lois in which he proposed that temperate climates were more favorable to economic development than tropical climates. In 1776 this problem was discussed by Adam Smith in his Wealth of Nations, in which he proposed that the skills of the population are the principal factor responsible for national differences in incomes and wealth.

Since these early attempts to analyse this problem, numerous other theories have been advanced. These theories fall into four principal categories. First, climatic theories are still proposed. Their leading exponent in recent times is Kamarck (1976) who argues that tropical climates are unfavorable for economic development because the heat and humidity reduce the efficiency of working capacities, impair the productivity of the land and provide a favorable environment for debilitating diseases. This explains the difference between what is sometimes called “the rich north” with its temperate climate and “the poor south” with its predominantly tropical climate.

Diamond (1998) presents similar arguments on the crucial significance of climatic and geographical factors.

The second major contemporary explanation is “dependency theory”. This proposes that the economically developed capitalist nations are responsible for the poverty of the underdeveloped nations because they dominate the world economy, force the rest of the world into economic dependency, and pay low prices for Third World agricultural products and natural resources. Some of the leading exponents of this theory are Frank (1969, 1996), dos Santos (1993, 1996), Wallerstein (1998) and Valenzuela and Valenzuela (1998); see also Seligson and PassŽ-Smith (1998).

Third, there is the neoliberal theory. This proposes that the major factor responsible for national differences in economic development consists of the presence of free markets as opposed to command, socialist and communist economies. Bates (1993) and Weede (1993) are leading recent exponents of this theory.

Fourth, there are a variety of psychological theories which argue for the importance of differences in attitudes, values and motivations. The first major theory of this kind was Weber’s (1904) theory that the Protestant work ethic explained the more rapid economic development of northern Europe as compared with the Catholic south from the sixteenth century onwards. Later theorists in this tradition include McClelland (1976) who advanced the similar concept of achievement motivation. Several economists, while not endorsing the theories of Weber or McClelland, are sympathetic to this kind of explanation and propose what are generally termed “cultural” factors as major contributors to national differences in economic development. Landes writes of the importance of culture “in the sense of inner values and attitudes that guide a population” (1998, p. 516). Many economists have taken eclectic positions in which they argue that several of these factors contribute to national differences in incomes and wealth.

We believe it has never been suggested that national differences in intelligence might play some role in national differences in economic development. It is widely assumed that the peoples of all nations have the same average level of intelligence. For instance, Kofi Annan, the United Nations Secretary General, asserted in April 2000 that intelligence “is one commodity equally distributed among the world’s people” (Hoyos and Littlejohns, 2000). It is known in psychology that this is incorrect and that there are large differences in average levels of intelligence between different nations. Reviews of the literature have shown that in relation to average IQs of 100 in Britain and the United States, the peoples of north east Asia have average IQs of around 105 and the peoples of sub-Saharan Africa have average IQs of around 70 (Lynn, 1991).

In view of these differences, it seems a reasonable hypothesis that national differences in intelligence may be a factor contributing to national differences in wealth. This is a promising hypothesis for two reasons. First, it is well established that intelligence is a determinant of earnings among individuals; and second, several studies have shown that the intelligence of groups is related to their average earnings. The earlier American research literature, up to 1970, on the relationship of intelligence to earnings among individuals was summarized by Jencks (1972) who concluded that the best estimate was expressed by a correlation of .35. Later studies have confirmed this conclusion. Brown and Reynolds (1995) examined the relation between IQ measured in early adulthood and earnings approximately 12 years later for samples of 24,819 whites and 4,008 blacks and reported correlations of .327 and .126, respectively. Hunter and Hunter (1984) report correlations between .25 and .60 for different types of occupations. Murray (1998) has examined the National Longitudinal Study of Youth sample for the relation between IQ measured in adolescence and income in the late twenties to mid-thirties and found a correlation of .37. Most students of this question have concluded that IQ is a cause of income because IQs are established quite early in childhood and predict incomes achieved in adulthood (Duncan, Featherman and Duncan, 1972; Jensen, 1998). It is estimated by Li (1975) that childhood IQ is correlated .83 with adult IQ. The relation between childhood IQ and adult income is present when parental socio-economic status is controlled (Duncan, Featherman and Duncan, 1972; Jencks, 1979).

The positive association between IQ and income among individuals led to the expectation that there would be positive associations between the average IQs of groups and their average earnings. We believe that the existence of such an association was first reported by Davenport and Remmers (1950) in a study in which the population units were the states of the United States. They obtained IQ scores from tests administered in 1943 to more than 300,000 young men in high schools and colleges as part of selection for placement in training programs for the armed services. The test was composed of verbal, mathematical and scientific items and was described as “a combination of a group intelligence test and a general educational achievement test” (p. 110). They calculated the average score for each state, examined this in relation to the state’s per capita income and found a correlation of .81.

The positive relationship between the average IQs of groups and their average incomes has also been found in studies carried out in Europe. A study of the British Isles examined the relation between average IQs in thirteen regions obtained in the 1940s and 1950s and per capita incomes in 1965. The average IQs fell within the relatively narrow range between 102.1 in London and 96.0 in Ireland. The correlation between average IQs and incomes was .73 (Lynn, 1979). A similar study for France examined the relation between average IQs in 90 “departments” (regions) obtained from testing approximately 257,000 young men conscripted into the armed services in the mid-1950s and per capita incomes in 1974. The correlation between IQs and earnings was .61 (Lynn, 1980). The same relationship has been found in Spain in a study in which average IQs for 48 regions were calculated from approximately 130,000 military conscripts for the mid-1960s. The correlation between these and average regional incomes was .65 (Lynn, 1981). In view of these relationships it seems a promising hypothesis that a positive relationship would be present between the average IQs of the populations of nations and their average earnings. It is this hypothesis that we are now about to investigate.

METHOD

This study presents data for 60 countries for national IQs, per capita incomes in 1998, and economic growth 1950-1998 and examines their relationships by the statistical techniques of correlation and regression analyses.
National IQs

National IQs have been calculated from normative data obtained in 60 countries for the Colored and Standard Progressive Matrices. The reasons for using these data are that the Progressive Matrices is the most widely used test in cross-cultural research, is non-verbal and hence is likely to yield more valid cross cultural data than verbal tests which require translation, is among the best measures of g, and the rate of secular increase is well established. The data have been obtained from the bibliographies of Progressive Matrices studies compiled by Court (1980) and Court and Raven (1995), from the data given by Raven in a series of manuals and research supplements for the Progressive Matrices, and from the Raven archive.

The Standard Progressive Matrices was constructed in Britain in the 1930s and was first published in 1938 with norms for 6-15 year olds and adults. This was followed by the publication in 1947 of the Colored Progressive Matrices, a simpler test suitable for 5-11 year olds. The Standard Progressive Matrices was renormed for 6 to 15 year olds in Britain 1979. A norm table is provided by Raven (1981) giving percentile equivalents of raw scores for half year age groups. The procedure for calculating the IQ of a country in which norms have been obtained for the Standard Progressive Matrices is to read off the raw scores of the 50th percentile from the norm table and obtain the British 1979 percentile. This is then converted to the British IQ equivalent using a conversion table. The raw score of the 50th percentile is the median IQ rather than the mean. Several studies have provided mean raw scores in addition to the medians and these show that means and medians are virtually identical. In most countries in which Progressive Matrices data have been collected norms have been given for a number of age groups. IQs are calculated for each of these and averaged to give a single national IQ. This IQ is then adjusted for the secular rise of the IQ which has been 2 IQ points per decade for the Standard Progressive Matrices in Britain over the period 1938-1979 (Lynn and Hampson, 1986). All national IQs are therefore expressed in relation to a British IQ of 100.

Norms for the Standard Progressive were collected for adults for Britain in 1992 and for the United States for 1993. The norm table for the United States provided by Raven, Court and Raven (1996) gives the most detailed information consisting of the percentile equivalents of raw scores. Less information is provided for the British standardization which gives only the raw score equivalents of the 5th, 10th, 25th, 50th, 75th, 90th and 95th percentiles. The British medians have been converted to American IQs by the use of the American norm table. The result of this calculation is that the British IQ is 102 on the American norms. Data for adults from other countries are converted to American IQs and then adjusted to British IQs by the subtraction of 2 IQ points.

There are no norms giving detailed percentiles for the Colored Progressive Matrices for Britain, the United States or elsewhere. To deal with data for the Colored Progressive Matrices, raw scores are converted to those of the Standard Progressive Matrices using the conversion table provided by Raven, Court and Raven (1995) and the IQs calculated in the way set out above.

In a few instances median raw scores fall below the 1st percentile of the British and American norm tables. The 1st percentile is equivalent to an IQ of 65. In these cases the countries are assigned an IQ of 64. For a number of countries Progressive Matrices data have been collected for two or more samples. These have been averaged to provide a single mean given to the nearest whole number.

The IQ for South Africa has been calculated as follows. The study by Owen (1992) gives the following IQs for the four racial groups. Whites: 94; blacks: 66; coloureds: 82; Indians: 83. The percentages of the four groups in the population are whites: 14%; blacks: 75%; coloreds: 9%; Indians: 2% (Ramsay, 1999, p. 158). Weighting the IQs of the four groups by their percentages in the population gives an IQ for South Africa of 72. The IQ of Singapore has been calculated in the same way by weighting the IQs of the ethnic groups (Malays, Chinese and Indians in Singapore) by their numbers in the population. The data on national IQs are shown in Appendix 1 which gives the IQ, the sample size, the test used (Colored or Standard Progressive Matrices) and the reference. For some countries there are two or more studies of the national IQ. These have been averaged to give mean IQs for these countries.

Because the concept of national IQ is new, it will be useful to examine its reliability and validity. To examine its reliability we have taken the sixteen countries for which there are two or more measures of IQ and calculated the correlation between the two measures. For the countries for which there are more than two measures (Brazil, Hong Kong, India and Mexico) we have used the two extreme values. The correlation between the two measures of national IQ is 0.937. This establishes that the measure of national IQ has high reliability.

To examine the validity of the national IQs we have examined their relation with national measures of educational attainment. This follows the long established methodology of the validation of intelligence tests among individuals by showing that they are positively correlated with test of educational attainment. The measures of education attainment are taken from the second and third international studies of educational achievement in mathematics and science. These data are shown in Table 1 for the countries for which we have IQ measures. The correlations between educational attainment and IQ are shown in the bottom two rows of the table. Five of the six correlations are statistically significant and establish the validity of the measures of national IQ.

National Wealth and Rates of Economic Growth

National wealth is measured by per capita national income. Strictly speaking, national wealth and national per capita income are different concepts because national wealth consists of the value of capital stock, whereas income is income, so we use the term national wealth in the general sense in which people speak of rich countries and poor countries. We use two alternative measures of national income: per capita GNP in US dollars and real GDP per capita in US dollars. The second measure is calculated on the basis of the purchasing power parity of the country’s currency. It is intended “to make more accurate international comparisons of GDP and its components than those based on official exchange rates, which can be subject to considerable fluctuation” (Human Development Report, 1997, p. 239). For some countries data on per capita GNP and real GDP per capita can differ considerably from each other. The basic difference between GNP and GDP is that GDP comprises the total output of goods and services for final use produced by an economy by both residents and non-residents within the geographical boundaries of a nation, whereas GNP comprises GDP plus income from abroad, which is the income residents receive from abroad, less similar payments made to non-residents who contribute to the domestic economy. The difference between GNP and GDP is relatively small for most countries - much smaller than difference between GNP and real GDP - but in some cases it can be quite substantial (see Gardner, 1998, pp. 22-23; Human Development Report 1999, p. 254; World Development Report 1999/2000, p. 274).

Most data on per capita GNP are taken from the World Bank’s World Development Report 1999/2000 and all data on real GDP per capita from the United Nations Development Program’s (UNDP) Human Development Report 2000. Sources of supplementary data are given at the foot of Appendix 2. Data for per capita GNP and real GDP per capita used in this paper are for the year 1998. These are the latest data available to us at the time of writing. These data for per capita incomes are shown in Appendix 2 for the same countries as in Appendix 1. However, in Appendix 2 the United Kingdom replaces Britain in Appendix 1.

Economic growth rates are measured as percentage increases in per capita GNP and per capita GDP. Consistent national differences in economic growth rates over many decades are responsible for contemporary national differences in GNP and GDP. Our hypothesis that national differences in IQ are a cause of contemporary national differences in GNP and GDP entails the prediction that national IQs should be positively correlated with long term rates of economic growth. We present two tests of this prediction. First, we examine the correlation between national IQs and economic growth rates of per capita GDP over the period 1950-1990 using the per capita GDP data given by Maddison (1995) for 54 of the countries in our sample. Second, we examine the correlation between national IQs and economic growth rates of per capita GNP over the period 1976-1998 using per capita GNP data given in the World Bank’s World Development Reports. From these data we have calculated the percentage changes of per capita GDP over the period 1950-90 and per capita GNP over the period 1976-98.

RESULTS

We examine first the correlations between national IQs and the two measures of national per capita income. These are presented in Table 2. It shows that the two measures of per capita national income are highly intercorrelated (.945). It also shows that the correlations between national IQs and the two measures of per capita national income are strongly positive as hypothesized. The national IQs are correlated .706 with per capita GNP and .757 with per capita real GDP. Both correlations are statistically significant at p<.001. We examine next the relation between national IQs and rates of economic growth. The correlation between national IQs and economic growth rates of GDP per capita over the period 1950-1990 is .605 (N=54, p<.001). The correlation between national IQs and economic growth rates of per capita GNP over the period 1976-1998 is .643 (N=56, p<.001).

It has been suggested by a referee that the mean IQs of sub-Saharan African countries are so low that they cannot be valid and that they spuriously inflate the correlations between the national IQs and the measures of per capita income and economic growth. We believe that we have to some degree met this point by showing in Table 1 that attainment in mathematics in Nigeria and South Africa is well below that in the rest of the world and that this goes some way to establishing the validity of the IQs for the countries of sub-Saharan Africa. Nevertheless to meet this point more fully we have excluded the 15 African countries and rerun the calculations. The results are that the correlation of IQ and per capita GNP 1998 falls from .706 to .625; the correlation of IQ and real GDP per capita falls from .757 to .586; the correlation of IQ and economic growth per capita GDP 1950-90 falls from .605 to .600; and the correlation of IQ and economic growth per capita GNP 1976-98 falls from .643 to .513. Thus the exclusion of the 15 African countries reduces the correlations to some degree, as would be expected with the reduction of variance in the reduced sample, but all four correlations remain substantial and statistically significant at p<.001. We are forced to conclude that the exclusion of the 15 countries of sub-Saharan Africa makes no significant difference to the associations between national IQs and economic growth.

It has been pointed out that correlation analysis does not establish causality because of the fact that correlations merely measure covariation. Let us conseder what causality presupposes. Manheim and Rich (1986: 21-22) say that it is justified to postulate causal relationships only when four conditions are simultaneously met: First, the postulated cause and effect must change together, or covary. Second, the cause must precede the effect. Third, we must be able to identify a causal linkage between the supposed cause and effect. Fourth, the covariance of the cause and effect phenomena must not be due to their simultaneous relationship to some other third factor. We think that the relationship between national IQ and the measures of per capita income and economic growth meets these requirements quite well. First, correlations indicate that the postulated cause and effect change together. Second, because differences in national IQs are partly genetic, they have certainly preceded contemporary differences in economic conditions. Third, the causal linkage between the hypothesized cause and effect will be discussed and explained in the next section. Fourth, it is highly improbable that the observed covariance between cause and effect could be due to any third factor. This last requirement will be discussed in greater detail in the next section. Consequently, we are quite confident that the relationship is causal.

Although the correlations between national IQs and the measures of per capita income are high, there are some countries which have much higher per capita incomes than would be expected from their national IQs and other countries whose national per capita incomes are much lower than expected. To examine these anomalies a regression analysis has been carried out to disclose which countries deviate most from the regression line. This analysis is limited to the regression of real GDP per capita 1998 on IQ. Real GDP per capita 1998 was selected for this analysis because real GDP per capita (purchasing power parity) can be regarded as a more valid measure of living standards than per capita GNP and because the correlation between national IQs and real GDP per capita is stronger than the correlation between national IQs and per capita GNP (see Table 2). The results of regression analysis are given in Table 3.

Table 3 shows how much individual countries deviate from the regression line, which represents the average relationship between national IQs and real GDP per capita in 1998. “Fitted GDP” indicates the predicted value of real GDP per capita in 1998. If the correlation between IQs and Real GDP per capita were perfect, all countries would be at the regression line and all residuals would be zero. Because the correlation (0.757) is not perfect, all countries deviate to some extent from the regression line. The residuals indicate the size and direction of the deviations. Positive residuals indicate that nations have higher real GDP per capita than is predicted on the basis of the average relationship between IQs and real GDP per capita, while negative residuals indicate that their per capita incomes are lower than expected. The sum of “Residual GDP” and “Fitted GDP” is always the same as the actual value of real GDP per capita given in Table 3. There is no natural distinction between countries with large and small deviations. Because one standard error of estimate is 5,583 real GDP per capita dollars in this regression analysis, it is reasonable to regard as highly deviating cases all countries for which positive or negative residuals are larger than 6,000. Positive residuals are large for eight countries: Belgium, Canada, Denmark, Ireland, Qatar, South Africa, Switzerland and the United States. Negative residuals are large for nine countries: China, Iraq, South Korea, the Philippines, Romania, Russia, Slovakia, Thailand and Uruguay. We consider the explanations for these anomalies in the discussion.

DISCUSSION

The hypotheses examined in this study have been that national per capita incomes and rates of economic growth would be positively correlated with national IQs. These hypotheses have been confirmed by strong correlations that are at a high level of statistical significance for both GNP and GDP. If we adopt a one way causal model that national IQs are a determinant of national per capita incomes and rates of economic growth, the results show that national IQ explains 57 percent of the variance of real GDP per capita 1998 and 50 percent of the variance of GNP per capita 1998. National IQ also explains 37 percent of the variance in economic growth of per capita GDP 1950-90 and 41 percent of the variance in economic growth of per capita GNP 1976-98.

There are two reasons why we consider that a causal effect of national IQ on per capita incomes and rates of economic growth is the most reasonable theory to explain the correlations. First, this theory is a corollary of an already established body of theory and data showing that IQ is a determinant of income among individuals, the evidence for which has been reviewed in the introduction. IQs measured in childhood are strong predictors of IQs in adolescence and these are predictors of earnings in adulthood. The most reasonable interpretation of these associations is that IQ is a determinant of earnings. From this it follows that groups with high IQs would have higher average incomes than groups with low IQs because groups are aggregates of individuals. This prediction has already been confirmed in the studies of the positive relationship between IQs and per capita incomes among the American states and among the regions of the British Isles, France and Spain, as noted in the introduction. The positive relation between IQ and income is so well established that it can be designated a law, of which the finding that national IQs are positively related to national per capita incomes is a further instance.

Second, there is a straightforward explanation for the positive association between IQ and incomes at both the individual and population level. The major reason for this association is that people with high IQs can acquire complex skills that command high earnings and that cannot be acquired by those with low IQs. Nations whose populations have high IQs tend to have efficient economies at all levels from top and middle management through skilled and semi-skilled workers. These nations are able to produce competitively goods and services for which there is a strong international demand and for which there is therefore a high value, and that cannot be produced by nations whose populations have low IQs. In addition, nations whose populations have high IQs will have intelligent and efficient personnel in services and public sector employment that contributes indirectly to the strength of the economy such as teachers, doctors, scientists and a variety of public servants responsible for the running of telephones, railroads, electricity supplies and other public utilities. Finally, nations whose populations have high IQs are likely to have intelligent political leaders who manage their economies effectively. Skilled economic management is required to produce the right conditions for economic growth, such as keeping interest rates at the optimum level to produce full employment with minimum inflation, maintaining competition, preventing the growth of monopolies, controlling crime and corruption, and promoting education, literacy and numeracy and vocational training.

While we consider that a causal effect of national intelligence on per capita income and rates of economic growth is the most reasonable model for an explanation of the data, there are two other possible explanations that deserve consideration. The first of these is that there is no direct causal relation between national IQs and per capita incomes and growth rates and the correlation between them is due to some third factor affecting all three. Although this is a theoretical possibility and needs to be mentioned, we do not think it is possible to formulate a plausible theory of this kind.

Second, it might be argued that national per capita incomes are a cause of national differences in IQs. This argument would state that rich nations provide advantageous environments to nurture the intelligence of their children in so far as they are able to provide their children with better nutrition, health care, education and whatever other environmental factors have an impact on intelligence, the nature of which is discussed in Neisser (1998). Intelligence has increased considerably in many nations during the twentieth century and there is little doubt that these increases have been brought about by environmental improvements, which have themselves occurred largely as a result of increases in per capita incomes that have enabled people to give their children better nutrition, health care, education and the like. Such a theory has some plausibility but it cannot explain the totality of the data. Countries like Japan, South Korea, Taiwan and Singapore had high IQs in the 1960s when they had quite low per capita incomes and the same is true of China today. Nevertheless, the model of national differences in IQ as a major determinant of economic growth and per capita incomes should probably be supplemented by the postulation of a small positive feedback in which national per capita income has some impact on the population’s IQ.

Our results are based on a sample of 60 nations out of approximately 185 nations of significant size in the world. We believe that the sample can be regarded as relatively well representative of the totality of nations because all categories of nations are well represented including the economically developed “First World” market economies of North America, Western Europe, Australia and New Zealand; the “Second World” former communist nations of Russia and Eastern Europe; the “Third World” economically developing but impoverished nations of South Asia, sub-Saharan Africa and the Caribbean; and the residual categories of Latin America and East Asia. If the representativeness of our sample is accepted, our results indicate that slightly over half the variance in national per capita income in the contemporary world is attributable to national differences in IQ. However, it should be noted that correlations are somewhat lower in the total group of 185 countries (see Lynn and Vanhanen, 2002). The difference in correlations implies that this sample of 60 nations is probably slightly biased.

The regression analysis suggests that a major additional factor is the economic form of organisation consisting of whether countries have market or socialist economies. The countries that have the largest positive residuals and therefore have higher per capita income than would be predicted from their IQs are Australia, Belgium, Canada, Denmark, France, Ireland, Israel, Qatar, Singapore, South Africa, Switzerland and the United States. With the exception of Qatar and South Africa, all of these are technologically highly developed market economy countries and their higher than predicted per capita incomes can be attributed principally to this form of economic organisation. Qatar’s exceptionally high level of per capita national income is principally due to its oil production industries. South Africa’s much higher than expected level of per capita income should probably be attributed principally to the cognitive skills of its European minority who comprise 14 per cent of the population.

The countries that have the largest negative residuals are China, Iraq, South Korea, the Philippines, Romania, Russia, Slovakia, Thailand and Uruguay. Four of these countries (China, Romania, Russia and Slovakia) are present or former socialist countries whose economic development has been hampered by their socialist economic and political systems. After the collapse of the Soviet communist systems in 1991 and the introduction of market economies in these countries and in China, the prospects for rapid economic development for these countries are good, although it takes time to establish effective market economies. Of the remaining five countries with large negative residuals, Iraq’s low level of per capita national income is due principally to the destruction inflicted in 1990 war and the UN sanctions imposed in 1990. South Korea’s Real GDP per capita is also considerably lower than expected on the basis of the country’s exceptionally high level of national IQ (106). The principal explanation for this is probably that South Korea had a very low per capita income at the end of World War Two as a result of military defeat and occupation by the Japanese and that it has not yet had sufficient time to achieve the predicted level of per capita income, although economic growth in South Korea since 1950 has been extremely high (see Appendix 2). The Asian economic crisis in 1998 may have increased the negative residuals of the Philippines and Thailand temporarily. Economic growth in Uruguay has been strong since the 1970s, although the country has not yet achieved the per capita income level expected on the basis of its relatively high national IQ.

Thus our general conclusion is that national differences in the wealth and poverty of nations in the contemporary world can be explained first in terms of the intelligence levels of the populations; secondly, to some extent, in terms of whether they operate market or socialist economies; and thirdly by unique circumstances such as the possession of valuable natural resources like oil in the case of Qatar and trade sanctions imposed on Iraq.
Estimation of Missing National IQs

We want to extend the analysis to the further 104 countries with populations of more than 50,000 for which we have not been able to find IQ data. For these 104 countries we have estimated the IQs. Two principles have been adopted for making the estimates of national IQs for those countries for which data are lacking. First, it is assumed that national IQs which are unknown will be closely similar to those in neighboring countries whose IQs are known. It can be seen from the results set out in Table 6.1 that neighboring countries normally have closely similar IQs. Thus, for instance, the IQ in both Germany and the Netherlands is 102; the IQ in Japan is 105 and the IQ in South Korea is 106; the IQ in Argentina and in Uruguay is 96; the IQ in Uganda is 73 and in Kenya 72; and so forth. It is therefore assumed that where national IQs are unknown, they will be closely similar to those in neighboring countries. We have therefore taken the most appropriate neighboring countries and used their IQs to assign IQs to countries whose IQs are unknown. Where there are two or more appropriate neighboring countries, the IQs of these are averaged to obtain an estimated IQ for the country whose IQ is unknown. Thus, for example, to estimate an IQ for Afghanistan, we have averaged the IQs of neighboring India (81) and Iran (84) to give an IQ of 83. Averages with decimal points have been rounded towards 100.

A second principle for the estimation of national IQs has been used for several countries which are racially mixed and for which there is no similar neighboring country. In these cases we have assigned IQs to the racial groups on the basis of the known IQs of these groups in neighboring countries. For example, Cape Verde, the archipelago off the coast of Senegal, has a population which is 1 percent white, 28 percent black and 71 percent mixed black-white (Philip’s, 1996). On the basis of the IQs of these groups in South Africa, it is assumed that the whites have an IQ of 94, the blacks of 66 and the mixed of 82, the IQ of South African coloreds (see Appendix 1). Weighting these figures by the percentages in the population gives an IQ of 78.

The racially mixed population of the Comoros consists of African (black), Arab and Malagasy elements. It is not any longer possible to separate clearly different racial groups. Because the racial composition of the population is comparable with Madagascar’s population, we estimate its national IQ to be 79, the same as in Madagascar. The Malayo-Polynesians and Negroids constitute the principal elements in the racially mixed population of Madagascar. The contribution of each of them may be approximately equal. Therefore, it is reasonable to estimate the national IQ for Madagascar on the basis of the Philippines (86) and Tanzania (72), which gives an IQ of 79 for Madagascar. For Mauritius, the population consists of 68 percent Indians, 27 percent Creole (black-white hybrids), 3 percent Chinese and 1 percent whites. It is assumed that the IQs are 81 for the Indians (as in India), 82 for the Creoles (as for South African coloreds), 100 for the Chinese (as in China) and 94 for the whites (as for the whites in South Africa). Weighting these figures by the percentages in the population gives an IQ of 81.

Table 4 shows these estimated IQs and the comparison countries on which they are based, together with measured IQs. We should emphasize that these data on national IQs are estimates and that they certainly contain errors, but we assume that the margin of error is relatively small in nearly all cases.

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Source : Richard Lynn’s website

Leftist magazine acknowledges racial differences in intelligence!

Race, Genes and Intelligence in Slate Magazine
http://www.slate.com/id/2178122/entry/2178123/

Other evidence on the topic:

James Watson Tells the Inconvenient Truth: Faces the Consequences

[The link to Gene Expression blog has been deleted because the Subcontinental “cognitive elitists” (or rather the filthy Bangladeshi, Razib Khan) changed links to a disgusting interracial porn site. Very classy. Our newest contributor, Ahnenerbe, wasn’t aware of Razib Khan’s obscene character. We sincerely apologize. ]

Interracial porn-loving Bangladeshi, NEWAMUL K. KHAN (also known as Razib Khan).

J. Rushton & A. Jensen - 30 years of research on race differences in cognitive ability
http://psychology.uwo.ca/faculty/rushtonpdfs/PPPL1.pdf

The evolution of racial differences in intelligence.

by Richard Lynn, University of Ulster, Coleraine, Northern Ireland
Abstract : Discusses a general theory of the processes through which the racial differences in intelligence quotients (IQ) have evolved. Cognitive demands for survival; Racial differences in the building of civilization; Tropical and subtropical hominids as plant eaters; Cold climates as a selection pressure for increased intelligence; Mean IQs of Mongoloids, Negroids and Caucasoids in different regions; Effect of nutrition on IQ.

Hominids first evolved in tropical and subtropical latitudes, most probably reaching sapiens status in the highlands of East Africa. From this ancestral population some groups migrated north into Eurasia and evolved there into the Caucasoids and Mongoloids. Colonizing temperate and cold environments, they encountered the cognitively demanding problems of survival in cold winters. These problems consisted principally of securing a food supply by hunting large animals and of keeping warm in winter by making fires, clothing and shelters. Survival in these difficult conditions acted as a selection pressure favoring enhanced intelligence and explains why the Caucasoids and the Mongoloids are the races which have evolved the highest intelligence.
Continue reading The evolution of racial differences in intelligence….

High IQ kids have distinct pattern of brain development

LONDON (Reuters) - Intelligence may have more to do with how the brain develops during adolescence than its overall size, researchers said on Wednesday.

Barack Hussein Obama’s ‘lost’ brother found in Kenya, lives on less than a dollar a day

Life in a low I.Q. country. Barack promises to do to America what his people have done to Africa.

“Huruma is a tough place, last January during the elections there was rioting and six people were hacked to death. The police don’t even arrest you they just shoot you.

“I have seen two of my friends killed. I have scars from defending myself with my fists. I am good with my fists.”

See also Obama campaign claims suspect “birth certificate” as genuine item.

The truth will get you lynched

By DENIS CAMPBELL
The Observer Sunday, November 5, 2006

LONDON - The London School of Economics is embroiled in a row over academic freedom after one of its lecturers published a paper alleging that African states were poor and suffered chronic ill-health because their populations were less intelligent than people in richer countries.
Continue reading The truth will get you lynched…

Sleep on It: How Snoozing Makes You Smarter

During slumber, our brain engages in data analysis, from strengthening memories to solving problems.

High-Aptitude Minds: The Neurological Roots of Genius

Scientific American Mind - September 4, 2008

High-Aptitude Minds: The Neurological Roots of Genius Researchers are finding clues to the basis of brilliance in the brain
By Christian Hoppe and Jelena Stojanovic
Continue reading High-Aptitude Minds: The Neurological Roots of Genius…

A portrait of life in black America

Niggers doing what they they do best: looting.

Ohio’s African-American teens die at twice the rate of white teens

Parenting practices affect child development

July 26th, 2008 | by Graham Scharf
Continue reading Parenting practices affect child development…

Life on a low I.Q. continent: The New Tragic Measure of True Happiness in Africa

Africans purchase 36 billion bottles of Coke a year, at a price of 20-30 American cents per bottle. Since the price is so low, and because Coca-Cola analyzes sales so closely, the Coke bottle has actually become a reliable tracker of stability and prosperity in Africa.
Continue reading Life on a low I.Q. continent: The New Tragic Measure of True Happiness in Africa…