Smart and SeXy

Smart and SeXy: The Evolutionary origins and biological underpinnings of cognitive differences between the sexes

The soft cover edition is available here. If you are on a budget you can also download the E-book. You can read the amerika.org review here and the counter-currents review here.

This is probably the most heretical work I have ever or will ever put to writing personally, and probably one of the most heretical things from the perspective of progressives, feminists and any other member of the cathedral available anywhere. If you want a no-nonsense (i.e., no feminism) description of sex differences, then you will probably enjoy the information contained within. If you have questions about what exactly the gender differences in intelligence are, by what fairly exact biological mechanisms they come about, and what potential evolutionary narratives explain what we observe, then this is the book for you. After reading this book you will not only know the current patterns of sex differences in intelligence as shown by psychometric tests, but why and how the underlying biology explains the patterns we observe. At the heart of the differences is both genetic and hormonal elements which work in concert to generate what we see on an every day basis. It has taken years of work (since 2011) and hundreds of hours invested in reading hundreds of dry academic papers to compile the more than 300 sources included, but I did so you can have the evidence all in one place and explained in lay terms. And perhaps most importantly, to have the evidence for gender differences in intelligence without muddying the waters with the foul taint of feminism.

At the heart of The Red Pill and the Dark Enlightenment, when thinking about women, is a kernal which grows to support everything else; all the theory on game, marriage, etc. All higher level knowledge is dependent on it. The fundamental concept, or more accurately the anti-concept, is the rejection of Equality. Egalitarianism just isn’t so. Men and women aren’t equal and they aren’t the same. Knowing they are not equal allows correct understanding of the world and relationships from successful one night stands to successful marriages. The entirety of the manosphere and red pill are dependent on this insight. The Dark Enlightenment is also dependent on this insight, but they expand it to include not only sex differences but ethnic differences as well.

Having that level of dependence on that initial small kernal can present a problem when it isn’t sufficiently supported by evidence. Though there is this and that study which suggests in a minor way that gender equality is false, it is my view that such information as bolsters the rejection of egalitarianism when it comes to men and women is lacking sufficient centralization within the manosphere and neoreactionary community. There may be thousands of individual blog posts on the topic, but mostly each one only addresses a small part of the big picture and getting the entirety of the picture from these diffused writings can be more difficult than it needs to be. The known facts are sufficiently dispersed, unorganized, and lacking in coherence that it makes the kernal a source of vulnerability to criticism from the outside. It is, as it were, a chink in our armor that needs to be addressed.

You might think “there is plenty of evidence.” Sure, there is. But, in all honesty, do we (the community more than geneticists) REALLY understand the mechanism? How exactly, at the molecular level, does inequality between men and women come about? It is an important question, and until it is answered so rigorously and thoroughly that it can’t be denied this will always be a vulnerability in our position. This is why I wrote this book. It is meant to be the titanium plate to cover our chink in the armor. This book coheres the currently available data into a single place and a single narrative that is relatively easy to access and difficult to refute. Moreover, and unlike most feminist theories, it presents a testable hypothesis. The genetic explanation for sex differences in intelligence I propose is something that biologists and geneticists can design experiments to test in order to prove or disprove. By making this hypothesis known to the mainstream it forces scientists to directly test the hypothesis. At least that is my hope. Prior evidence suggests what the result of such testing will be.

Another point of this book is to attempt to put to rest once and for all the idea that disparities in achievement between men and women have a chiefly cultural origin; they don’t. The differences between men and women are almost exclusively due to biology. Once society accepts that women aren’t going to ever achieve at the same rate as men, we can stop wasting time and resources promoting women, via affirmative action, into positions and occupations they are not suited for; thus saving a lot of effort and wealth that is currently getting wasted. We might also be able to get the birthrate back up to a more stable level and thus avoid demographic problems.

Lastly, to a certain extent it is meant to be a handbook for those who might be faced with deliberation on the topic and who need to quickly reference one type of study or another to demonstrate biological reality. I have made herculean efforts to make this as readable as possible and I believe I have done a good job with this, but I have placed greater emphasis on including as much relevant information with proper citations to credible journals as possible. I wanted to give people knowledge of which studies they need to cite for their particular argument or discussion in one convenient and accessible place.

Who to thank?

I owe some twisted gratitude to progressive academics who through their push to shun and silence me in the name of political correctness gave me the motivation I needed to write this book contrary to their culturally Marxist fantasies. On multiple occasions I have been personally screwed over by people holding that ideology because I was so audacious as to merely mention I had read The Bell Curve and found the points within to be worth consideration. I didn’t even claim to agree with it, just that it is a hypothesis which needs to be taken seriously. That is, I was trying to be an objective biologist which is what scientists are supposed to do. What we are trained to do in fact. There were also several situations (probably more actually) where similar points, but about gender instead of race, met with pretty much the same result. Though it didn’t end up mattering very much, I was rejected from one graduate school because the chairman of the department found out I had a conversation with another professor about the bell curve (that professor actually brought the topic up!). That chairman then projected onto me an argument he had with his daughter’s teacher where apparently the teacher said or believed something sexist. The bell curve only briefly talks about gender differences (a couple pages out of 849)…  What the teacher actually did was never very clearly explained. This guy was mad, and it had absolutely nothing to do with anything I said to him, and I got a nice rejection because of it. So ya, I got really pissed, and not for the first or last time. A string of situations just like this created a great resentment within me, which I am sure is quite true of many other people given the swelling of the red pill, the dark enlightenment and other internet phenomena. These prig prog “scientists” were being complete a**%^$!s about hypotheses which cover perfectly valid scientific questions, and which as I show in the book have a great deal of empirical support. If it hadn’t been for my naive faith in actual objectivity in science, and the subsequent confrontation with the progressive faith that actually exists in science that resulted, I almost certainly never would have cared enough to do any of this work. I may never have cared enough to find neoreaction. Yet those things did happen, and now neoreaction, the alt-right and the red pill have something available that they can use against left-wing creationists, should they desire to use it.

Confrontations like these have made me, and many others, heavily motivated to discredit feminism because their beliefs don’t match the facts and they witch hunt anyone and everyone who points that out. The best way to do that is with hard data and if I didn’t do it, I feared nothing else so comprehensive would have come out for years. Or if it did, it would be hidden in esoteric academic texts in obscure journals and even then it would be dressed in evasive and overly-qualified language. In fact, I would argue that there has been more than enough data available to discredit feminism for a very long time but paywalls for publicly funded research (don’t get me started on that) and a wide dispersion of everything relevant with substantial credibility has made it difficult to pull everything together. There are many, many papers which touch on the subject but none that I have been able to locate that brings it all together. And they definitely don’t come close to calling out progressives. Most try to appease the leftist mobs. To do this right takes an outsider, and it takes someone with an audience. I have a marginal audience, but the biggest help with spreading the information lies with my ties to the other neoreactionaries who have a much larger following. Likely, it will spread to the manosphere blogs due to the porous nature of the divide between neoreaction and that community. Or not, only time will tell.

Blog vs. book

There are a number of bloggers who write for years then decide after the fact to convert their posts into a book. In my case, I actually went the other direction. I had already had this book in progress for several years prior to starting this blog in 2014. A number of posts on this blog (not all) were either direct offshoots from work on this project or were indirectly inspired by my work on the book and later integrated as they were highly relevant to points I was making. Some changed little, while others changed significantly in the move. For the most part, my posts are shortened versions of what appears in the book and have less evidence, citations, and topics as a result of needing to make them stand alone away from the rest of the text. However, the most important part of the book, in my mind, is the large numbers of studies collected together from a wide variety of fields and which constitute the evidence for the biological origins of sexual dimorphism in intelligence. This includes both IQ test studies and the impact of the genetics and hormones on the brain and intelligence. This evidence is exclusive to the book. If you would like a taste of the content of the book before deciding whether or not you want it, I recommend you take a look at the following posts:

Career women are dysgenic

How standardized testing undervalues men

stereotype threat and pseudo-scientists.

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Kami, The HIV Muppet

I was recently browsing a subreddit I just discovered called /r/bertstrips. It seems that the focus is to have screen shots of sesame street and to caption them with racist, inappropriate, malicious, or otherwise mean intentions of the characters. Some of them are pretty funny. Well, I found one posted featuring Kami, the HIV muppet:

R1sEOLKNow, many of the characters are given perverse or otherwise degenerate attitudes, beliefs, and preferences in the comics which are not present in the show. I expected this to be just another example of artistic license on the part of comic makers. Imagine my surprise when I found out that Kami, the HIV Muppet is a real character that is really depicted on the show as having HIV and debuted way back in 2002. Not only that, but prominent celebrities and political leaders have made appearances with the HIV muppet including former president Bill Clinton, Laura Bush (ok, not a political leader but close enough), Whoopi Goldberg, and Oprah Winfrey. See previous link. Apparently Kami is a “bipartisan” supported character in that both cuckservatives and liberals are in favor and supportive of it and have made appearances with it. You can see a video clip of Bill Clinton with the HIV muppet below:

I found the concept of the HIV Muppet to be absolutely astounding. HIV is a serious disease and should never be taken lightly. While it is true that merely touching a HIV+ person will not result in a transfer of the disease, you would be at quite a high risk should they get injured and start bleeding. High enough that you need to take substantial precautions against becoming infected yourself. Young children (3-7) who would watch sesame street could not really be expected to suddenly recognize the extreme risk should a HIV positive person start bleeding and the risk of transmission experience a large spike. Normalizing and downplaying HIV to children is so irresponsible I can’t even fathom it. If you go back to that reddit comment thread, you will see that most of the commenters there had exactly the same reaction I did. First, complete surprise the character exists at all, then disgust and abhorrence at the sadistic irresponsibility of its creation and promotion. It takes a lot to disgust the kind of community which enjoys bertstrips; leave it to leftists.

Moreover, this character was originally and/or mainly intended for a South African audience where around 1 in 9 people is infected with the disease. I try to avoid conspiracies, but if my main concern was population control in Africa, Kami is exactly the kind of character I would create. Normalize and trivialize HIV to African children so that you can boost infection rates and subsequently lower the population. Of course, it could just be a typical example of the leftist tendency for feelz before realz. To them, the most important thing is people’s emotions. Legitimate and medically necessary precautions are, to them, invalidated if it happens to make someone feel bad.

Intentional or not, if I were a black South African (the target group with the highest HIV rate) I would be hopping mad that this propaganda is going on. Instead of advocating sensible precautions, that population (and very specifically children!) is being encouraged to increase contact with HIV infected persons as much as possible. If blacks still think that the liberal elite is their ally, the creation, use, and promotion by prominent personalities of this character should cure them of that delusion. It won’t, but it should.

Of course, this is not the first nor will it be the last time cultural Marxists attempt to normalize HIV to save the feelings of the few at the cost of increasing the risk to the many. Recently there was the controversy about allowing gay men to donate blood. In the west, gay men are the main carriers of the disease and have substantially greater infection rates than the rest of the population. Banning them from giving blood is a simple and straightforward precaution. Yet, that may hurt gay men’s feelings so leftists rally against it. Unsurprisingly, much of this nonsense protesting takes place at universities. (I didn’t make a big deal about Kami being female because the main audience is South Africa, where infection patterns are more gender balanced, mainly as a result of the African inclination for heterosexual anal sex. However, having her be female in the West makes little sense because it is very much a disease that mostly affects gay men.)

In addition, most states in the US have, in my opinion, a completely lax attitude to HIV+ health workers. Were I running things no one with HIV would be allowed to work in the health care field at all, and probably others as well. Health care workers and patients are both commonly exposed to sharp objects such as needles and scaples that can and do create wounds to facilitate transmission of the disease. In reality testing workers is on a voluntary basis and even knowing a worker is HIV positive is not grounds for dismissal. According to the CDC, there have been 58 confirmed and 150 possible cases of transmission of HIV from an infected health worker to a patient. It says in the last link that there has been only one confirmed case since 1999. Nice try, but reporting cases of HIV transmission from a healthcare worker to a patient is voluntary. Translation: Progs are almost certainly obfuscating the issue by not reporting it when they discover it has happened because they care more about the feelings of gays than they do about the general health of the population. The feds are encouraging them in this by intentionally keeping reporting voluntary. I would be willing to bet a million dollars that there have been quite a few more cases than 1 since 1999, but of course no sensible person would bet against me because that would just be stupid.

 

 

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Wikipedia in Action on Race

I like to refer to Lewontin’s fallacy frequently when debating people who deny the biological basis of race. Wikipedia, while clearly not perfect, did have a reasonable article (at least for quick referral of lay-people) on the paper written by W.F. Edwards which coined “Lewontin’s fallacy.”(1) A brief overview is that in the 1970’s an academic social justice advocate published a paper(2) in which he claimed that there is more variation within individuals from one race than there is variation between different racial populations. So much that you can regularly find people of different races who are more similar to each other than they are to members of their own race. However, the first paper linked to above shows that the problem mainly stems from the fact that very few loci were studied by Lewontin. Allele frequencies differ between populations and with enough loci studied, the ability to distinguish between racial groups based purely on genetic information is quite high. Virtually 100%.

As is typical for pretty much all articles on Wikipedia, anything that isn’t politically correct can be expected to drift over time such that claims that are not PC are deleted, diluted, and placed next to a larger number of criticisms than is warranted such that it implies that the non-PC claims seem unsupported or only supported by very few outliers. Sometimes, like in this article, a paper which can be seen to support one conclusion actually supports the opposite on more careful inspection. All of this is the wikipedia version of death by 1000 cuts. I once tried editing the page on gender differences in intelligence and was basically run out and banned by marxist feminists. I assume this happens to anyone who objectively tries to include factual and balanced information into potentially politically incorrect articles. These same people got that article deleted or subsumed into gender differences in psychology for awhile, but it looks like it has been resurrected now. Honestly, the constant battle over these sorts of articles is just beyond all reason and I will never bother editing wikipedia again. Chances are your work is just going to get deleted and there are other platforms where that won’t happen.

Subjectively, it seems like this sort of thing has been happening to the Lewontin’s fallacy article, but I will let you be the judge:

Here is an old archived version of this article.

Here is an archived version of the current article.

Here is a direct link to the article. (It shouldn’t look different than the above link at the time of this post, but who knows what future changes will be made. In a year or two it could be interesting to compare these three versions)

The thing that is most obvious in my mind is that a paper discussed in an earlier version of the article which supported the concept of Lewontin’s fallacy has had any reference to it completely deleted. Here is the now deleted content:

Studies of human genetic clustering have shown that people can be accurately classified into racial groups using correlations between alleles from multiple loci. For instance, a 2001 paper by Wilson et al. reported that an analysis of 39 microsatellite loci divided their sample of 354 individuals into four natural clusters, which broadly correspond to four geographical areas (Western Eurasia, Sub-Saharan Africa, China, and New Guinea)

In addition, a paper which purports to undermine the concept that Lewontin’s thinking is fallacious is present at the end in both versions, but is quoted more (and very selectively) in the most recent version. In my opinion, the findings in both wikipedia versions are misrepresented.

In the old article this:

The paper claims that this masks a great deal of genetic similarity between individuals belonging to different clusters. Or in other words, two individuals from different clusters can be more similar to each other than to a member of their own cluster, while still both being more similar to the typical genotype of their own cluster than to the typical genotype of a different cluster. When differences between individual pairs of people are tested, Witherspoon et al. found that the answer to the question “How often is a pair of individuals from one population genetically more dissimilar than two individuals chosen from two different populations?” is not adequately addressed by multi locus clustering analyses. They found that even for just three population groups separated by large geographic ranges (European, African and East Asian) the inclusion of many thousands of loci is required before the answer can become “never”

On the other hand, the accurate classification of the global population must include more closely related and admixed populations, which will increase this above zero, so they state “In a similar vein, Romualdi et al. (2002) and Serre and Paabo (2004) have suggested that highly accurate classification of individuals from continuously sampled (and therefore closely related) populations may be impossible”. Witherspoon et al. conclude “The fact that, given enough genetic data, individuals can be correctly assigned to their populations of origin is compatible with the observation that most human genetic variation is found within populations, not between them. It is also compatible with our finding that, even when the most distinct populations are considered and hundreds of loci are used, individuals are frequently more similar to members of other populations than to members of their own population”

expanded into this:

In the 2007 paper “Genetic Similarities Within and Between Human Populations”,[20] Witherspoon et al. attempt to answer the question, “How often is a pair of individuals from one population genetically more dissimilar than two individuals chosen from two different populations?”. The answer depends on the number of polymorphisms used to define that dissimilarity, and the populations being compared. When they analysed three geographically distinct populations (European, African and East Asian) and measured genetic similarity over many thousands of loci, the answer to their question was “never”. However, measuring similarity using smaller numbers of loci yielded substantial overlap between these populations. Rates of between-population similarity also increased when geographically intermediate and admixed populations were included in the analysis

Witherspoon et al. conclude that, “Since an individual’s geographic ancestry can often be inferred from his or her genetic makeup, knowledge of one’s population of origin should allow some inferences about individual genotypes. To the extent that phenotypically important genetic variation resembles the variation studied here, we may extrapolate from genotypic to phenotypic patterns. […] However, the typical frequencies of alleles responsible for common complex diseases remain unknown. The fact that, given enough genetic data, individuals can be correctly assigned to their populations of origin is compatible with the observation that most human genetic variation is found within populations, not between them. It is also compatible with our finding that, even when the most distinct populations are considered and hundreds of loci are used, individuals are frequently more similar to members of other populations than to members of their own population. Thus, caution should be used when using geographic or genetic ancestry to make inferences about individual phenotypes”,[20] and warn that, “A final complication arises when racial classifications are used as proxies for geographic ancestry. Although many concepts of race are correlated with geographic ancestry, the two are not interchangeable, and relying on racial classifications will reduce predictive power still further.”

This paper… It had decent data and methodology actually. But as is almost always the case with these sorts of things, interpretations and framing of the results are key. It is clear that the people who wrote this are deliberately softballing their wording either to cover their ass (my guess) or to promote a more progressive narrative.

ω in the following quotes is defined as given a certain number of loci considered, the probability of individuals originating from two distinct geographical areas will be more similar to each other than to someone originating closer to them. I.E., the probability that two randomly selected individuals from different races will be more similar to each other than each is similar to a randomly selected member of their own race. Keep in mind that ω is not the same as determining what race a person is based on genetic data. Even with small numbers of loci and a high ω, there is very low probability of misclassifying the race of an individual person. From the very same paper used to undermine the Edwards’ paper:

[A relatively large ω is found with low numbers of loci] It breaks down, however, with data sets comprising thousands of loci genotyped in geographically distinct populations: In such cases, ω becomes zero.

With the large and diverse data sets now available, we have been able to evaluate these contrasts quantitatively. Even the pairwise relatedness measure, ω, can show clear distinctions between populations if enough polymorphic loci are used. Observations of high ω and low classification errors are the norm with intermediate numbers of loci (up to several hundred)

Thus the answer to the question “How often is a pair of individuals from one population genetically more dissimilar than two individuals chosen from two different populations?” depends on the number of polymorphisms used to define that dissimilarity and the populations being compared. The answer, ω, can be read from Figure 2. Given 10 loci, three distinct populations, and the full spectrum of polymorphisms (Figure 2E), the answer is ω ≅ 0.3, or nearly one-third of the time. With 100 loci, the answer is ∼20% of the time and even using 1000 loci, ω ≅ 10%. However, if genetic similarity is measured over many thousands of loci, the answer becomes “never” when individuals are sampled from geographically separated populations.

Molecular biologists and geneticists use a little bit different definition of polymorphism than some other branches in biology. In this case, they are referring to single nucleotide differences in the genome. This is equivalent to having one letter different in spelling a word. Prog and prig mean almost the same thing, but there is one letter difference which slightly changes the meaning. This is a reasonable analogy to the differences in the genetic code.

What this paper says (and it should be said with less tip-toeing) is that if you only consider a small number of these single nucleotide polymorphisms, there is a high degree of error and you can often erroneously conclude that two people from different races are more similar to each other than they are to individuals of their own race. The key word here is erroneously. This is a statistical problem, not biological fact. If you consider thousands of SNPS at once, then you have virtually no chance of encountering this problem. The authors of this paper found that Edwards was right and Lewontin was wrong. Individuals from two different races are never more similarly related than people from the same race, and the genetics supports this when you consider enough loci. It is pretty unambiguous. The quotes in the Wikipedia article and in the paper don’t really represent what the researchers actually found. The researchers had to dress this language up the way they did because of progressive influence in academia. Chances are they wouldn’t have gotten published if they were straight forward about what they found, and even if they could have published political heresy they may have had their careers ruined by SJWs in academia. See what happens when you don’t toe the line with the progressive narrative by reading what happened to a University of Texas researcher who didn’t find the “right” conclusions with regards to gay couples raising children. Though there is a huge problem with how Wikipedia articles are written and “maintained,” they wouldn’t have been able to misconstrue these results so badly if it weren’t from the same sorts of SJWs in academia malevolently influencing researchers. Though it shouldn’t be understated that the wikipedia editors did in fact selectively quote from this already bludgeoned paper. Two layers of SJW influence changed the findings of this paper to mean the exact opposite of what it actually found. Unbelievable. It is truly amazing that this sort of shenanigans is allowed to go on.

You might object that “thousands” is a huge number and that this demonstration of statistical problems convincingly shows that races don’t differ if it takes that many to reduce error to zero. However, the human genome is about 3 billion base pairs long. If you were to use 3000 base pair SNPs, which is consistent with the minimum in the paper, then you need to utilize only .0001% of the whole genome to reduce this error to zero. Or, if you want to consider SNPs only, there are about 10 million SNPs in the human genome. A sample of 3000 SNPs is only .003% of the total number of SNPs that could be used. This is a conservative estimate because their figure 2 indicates it only takes about 1000 SNPS to minimize this error. In other words, it only takes a vanishingly small fraction of the genome to relieve you of this statistical error that can find that humans from two different races are more similar to each other than either is to their own race.

Yet this paper, which so conclusively shows that human races are different from each other on the genetic level, is used to debunk the original Edwards’ paper. The author’s of the paper attempt to debunk themselves or at least pretend like they found the opposite of what they actually did. This paper is absolutely one of the worst instances of doublethink I have ever come across. It literally blows my mind. As a society, we seem to have a real hatred for truth when it comes to biological realities and the uninformed are clearly being purposefully told lies.

Sidenote: I know there was another article on cathedral entryism on Wikipedia in the alt-right in the last year or so, but for the life of me I can’t find it. If anyone can provide a link I would appreciate it. Edit: Found it.

(1) Bioessays. 2003 Aug;25(8):798-801. Human genetic diversity: Lewontin’s fallacy. Edwards

(2) The Apportionment of Human Diversity. R. C. Lewontin. 1972

(3) Genetics. 2007 May; 176(1): 351–359. doi:  10.1534/genetics.106.067355 PMCID: PMC1893020 Genetic Similarities Within and Between Human Populations J. Witherspoon, S. Wooding, A. R. Rogers, E. E. Marchani, W. S. Watkins, M. A. Batzer, and L. B. Jorde

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