Category: EGI

Immigration: No Free Lunch

It’s NOT the economy, stupid.

I note, and have noted many times before, that the immigration question among the mainstream is continuously presented (almost solely) in economic terms.  The latest manifestation of this is the claim that immigration is the “closest thing to a free lunch” since population growth fuels economic growth via an increased number of workers and consumers. This Ponzi scheme view of economic growth fails for a number of reasons, including the obvious point that a larger economy divided over a larger population is not increasing the per capita payoff – it may be a larger pie, but not larger pieces for each individual. I note that as immigration has flooded into America over the past several decades, allegedly “fueling economic growth,” real wages for the typical American have stagnated, and the American middle class is in a well-documented and oft-discussed decline.  Is it that all this “growth” is lining the pockets of big business, and also benefiting the immigrants themselves and not natives?  Then we are constantly being told that automation will “make work obsolete,” and so a “basic guaranteed income” will be required in the wake of the mass unemployment thus created – a “citizen’s dividend” based on the productivity generated by automation and artificial intelligence.  If so, why do we import more people who will not only become superfluous as workers, but who will compete with natives for the proceeds of the productivity to be distributed as that guaranteed income?  

And even putting the issue of automation aside, the Ponzi scheme aspect of the immigration-population-economy equation becomes more clear when we ask: if immigrants do the work natives won’t do, then who will do that work in the next generation (assuming no automation) when the immigrants’ children are “Americans” or “Europeans” with American or European expectations and the consequent disdain for manual labor?  Do we import another generation of immigrants to do this unwanted work, repeated ad infinitum, until the entire nation is full of the posterity of those brought in to do cheap manual labor?  Conversely, if we need “high skilled immigrants” as we in America are constantly told, then why can’t we find Americans to do these desirable, highly-paid professional jobs?  Are native Americans stupid as well as lazy?  And, if so, how did they build a nation so attractive that all these immigrants want to come to in the first place?  And, further, if immigrants are required to fund “the retirement of an aging native population” (assuming that young non-Whites would politically support funding the retirement of old Whites who they hate), what happens when the immigrants themselves get old and retire?  Would more immigrants be required to fund those retirements – an endless pyramid scheme of immigration and inter-generational wealth transfer?  Or will the immigrants have enough children to support their retirement, underscoring the race replacement aspect of the immigrant influx?  Speaking of which, we can further ask – even if a declining native population “hinders economic growth” (a popular meme, along with the “who will pay for retirement” ploy, to justify genocidal alien immigration into Europe) – so what?   Eventually it will be a self-correcting process, as automation, increased productive efficiency, altered economic structures and expectations and, very likely, an eventual increase in the native birth rate, balances things out – sans replacement immigration.  I can also point out that bringing in hordes of cheap labor aliens to crowd out, compete with, and displace, natives is not exactly conductive to increasing native birth rates.  Or is that the intention?

Finally, we get to the most important, the most fundamental point.  Even if everything the pro-immigration crowd says about economic benefit is true, it still is not worth it.  A nation is not an abstract economic zone, and a people are not an atomized mass of workers and consumers.  Nations and peoples are historical entities, with particular ethnic, racial, social, and cultural profiles, and a people being demographically and culturally displaced and replaced are not benefiting, even if “the economy grows.” Mass immigration of alien peoples, particularly in the context of declining native populations, is genocide against the natives, and what price economic growth if historical nations and peoples cease to exist, and vanish from the Earth?  Read this post for a more technical analysis of the precedence of genetic continuity and genetic interests over any economic concerns, and if you still insist on putting a “dollars and cents” measure on these issues, then read this.  Existence, not economic growth, is the fundamental concern of any people, and no amount of “economic growth” – most of which the native masses will never themselves enjoy – can never justify criminal genocidal policies targeted against beleaguered European-derived peoples.

This post is also relevant to another pro-immigration argument I’ve seen making the rounds again recently: “if you are against (legal and illegal) low-skilled immigration, then you have no good reason to oppose high-skilled immigration, which is such a net positive for our nation.”  Nonsense.  Read this post again, particularly the last section that emphasizes race and culture, and the genocidal implications of displacing and replacing the native population.  Read the linked posts, especially the one outlining the EGI concept and its importance to immigration.  Of course high-skilled immigration is harmful; indeed, one can make the argument that high-skilled non-White immigration is worse for Whites than low-skilled non-White immigration.  High-skilled immigration brings in more clever and capable enemies, more capable and clever competitors, the importation of an alien ruling class, using ethnic nepotism to displace native White Americans from positions of power and prestige.  High-skilled immigrants, free-riding on the society and infrastructure painstakingly built up by White Americans, will climb to the top of the human energy pyramid, leveraging ethnic cartel networks to squeeze Whites out and reduce White Americans to a subaltern caste within their own nation. Is that a good enough reason for you?  Is that sufficient reason to oppose high-skilled immigration?  They are not us, they are not wanted, we need to develop and nurture our own high-skilled population.  We do not want or need leering aliens lording it over us.


Behold the Female: Expired Shelf Life

Rotting yeast.

My problems with the gamesters is essentially one of prescription, not description.  With respect to sexual matters, the game crowd are correct in their fundamental analysis.

For example, Johnny Redux:

A sexless marriage, in many (if not most) cases, is the result of a man marrying a woman his own age, and after time losing all sexual interest in her as she quickly morphs into an old woman before his eyes, much quicker than he is aging.

As they say: when a man gets older, he looks more and more like Sean Connery, and when a woman gets older she looks more and more like….Sean Connery.

Indeed, one wonders how much of the retroactive outrage pouring out from #MeToo past-their-prime yeastbuckets is due to the bitterness of aging, sagging hags, who have all the charm of rotting meat and all the grace of a wilted flower, looking back with desperate longing to the days when men actually found them attractive – before the inexorable ravages of time worked to make milady into a pathetic and pitiful shell of her former self.  Unlike Dorian Gray, it’s the woman herself, not her portrait, which decays with every passing day, to the dismay of every man who looks, disapprovingly, upon her.

Some good advice for (White) women: gain some humility, marry and have children in your 20s, suppress your urge to hypergamy, and cultivate a pleasant personality so you will be tolerable when your looks fade (which will occur sooner rather than later). You’ll want to have something to fall back upon when you hit the wall, other than the love of a good cat.

The connection between sexual behavior and EGI should be, I hope, obvious to the reader.  We are, after all, a sexually reproducing species.

Genetic Structure and Altruistic Self-Sacrifice

A more precise accounting is required.

We are all aware of Haldane’s oft-quoted assertion that he would lay down his life for two brothers or eight cousins, the genetic payoff of such altruistic self-sacrifice being the equivalence – as measured by ”bean-bag” genetics – of the numbers of gene copies between these sets of relatives.

In general, I am in broad agreement with the sentiment, although as we shall see, it requires modification.  Even more broadly, those on the Far Right invoke this paradigm to support the idea of altruistic self-sacrifice in favor of larger numbers of an ethny, in defense if ethnic genetic interests.  Likewise, I support that as well, with the proper modifications as with the smaller-scale examples of familial relatives.

Even though at first glance, Haldane’s reasoning seems sound, likely most people would be hesitant to follow that advice.  In large part, this is the natural impulse of self-preservation, but there are other reasonable objections that can be made.

One could argue, all else being equal, that judging between two sets of equivalent genetics, it’s better to preserve yourself for reasons of control.  A person concerned enough with genetic continuity that they would consider such altruistic self-sacrifice is someone likely to start a family, care for children, and properly actualize the continuity. Can you be sure your two brothers would do the same?  Why are they in the position that they need your sacrifice to begin with?  Are they stupid?  Reckless? Are you sure they’ll act in support of your (in this case indirect) genetic continuity with the same vigor you would do for yourself?  So, to be safe, maybe you need to raise the bar for self-sacrifice to three brothers or ten cousins?

A more important reason, and one that may be intuitively sensed by most people even though they wouldn’t be able to explain it, or likely even articulate their feeling about it, is that there is more about kinship than mere numbers of gene copies.  Genetic structure is important – what genes are coinherited and, to the layman’s eye, what phenotypic traits (derived from those genes) are inherited together.  Of course, family is going to be more similar here than (co-ethnic) strangers, but similarity is not identity.  Even with siblings (apart from identical twins, which are a special case), recombination and independent assortment will ensure that your brothers will have a distinct genetic stricture from you.  Now, granted, these same processed, even with a co-ethnic mate, will ensure that your children will also have a different genetic structure than you, but, all else being equal, your brothers’ children will be more unlike you, with respect to genetic structure, than your own children, as the “starting point” (you vs. your brothers) is already different. So, when genetic structure is taken into account, two brothers are not really your genetic equivalent.  Apart from an identical twin, you have no genetic equivalent, just degrees of relative similarity and difference, even after numbers of gene copies are accounted for.  Then how many brothers are sufficient for self-sacrifice?  This requires a more rigorous analysis, which will be dependent upon accurate measures of genetic structure, and that’s not something we can expect SJW population geneticists are likely to do. However, while the overall Haldane argument – and its Salterian extension – makes sense the numbers given based on “bean bag” genetics is going to be an underestimation of where you need to draw the line in sacrificing yourself for others.  On the other hand, the reverse is true – if you have to choose between your brothers and strangers, or between co-ethnics and non-ethnics, taking genetic structure into account means that helping your brothers and your co-ethnics is even more important than before, because in comparison to more genetically alien peoples, genetic structure amplifies how much more close you are to your brothers and your co-ethnics.  It’s a double-edged sword: it makes your own preservation a bit more important, but it also makes the preservation of those more similar to you more important than those more distant.

Now, one can argue that after several generations of recombination and independent assortment – even assuming endogamous mating within the ethny – genetic structures derived from your posterity and those of your brothers will be more or less the same, converging on the common pool of ethny-specific genetic structures.  So, while in the first generation, your offspring and that of your brothers may be distinct with respect to genetic structure, that difference would be attenuated over time and, as long as endogamous mating is maintained, your posterity and theirs would reflect similar genetic structures.  But there are problems here.  First, a rigorous analysis is required; perhaps some differences would continue over at least several generations; even if these differences are small, they nevertheless would need to be accounted for.  Second, if it is true that familial genetic strictures would tend, over time, to converge on more generalized ethny-specific structures, then why bother favoring two brothers over two random co-ethnics?  The brothers would share more of your genes, yes, and be more similar as far as genetic structure, but if one invokes “long term intergenerational effects” with respect to questioning the need to account for structure in modifying Haldane’s argument, then one can use the same “intergenerational effect” to directly question Haldane’s original premise.  The answer I believe is that one must do the best they can at a given time in maximizing their genetic payoff, and hope that subsequent generations do the same. In the absence of the required analysis, one can simply argue that looking to the next generation, differences in genetic structure are important and, hence, two brothers are not quite the genetic equivalence of yourself.  Your structure is different from theirs and the genetic payoff of your reproduction is greater for your than both of theirs combined.  So, maybe you need to hold out and sacrifice for three (or more) brothers instead, including for the other reason outlined above. Note that these fine points deal with very close genetic similarity.  When we are talking about racially alien peoples, the genetic distance becomes even more amplified with genetic structure, and in the absence of panmixia, ethny-specific patterns of genetic structure are broadly stable over evolutionary time (we can see that the Iceman is genetically more similar to Europeans than to, say, Asians  of Africans, as one example).

In the absence of the sort of careful quantitative analysis that population geneticists won’t do, from a qualitative standpoint, it would be prudent to require more of a genetic payoff before engaging in Haldane-style altruistic self-sacrifice.  On the other hand, when considering a choice in investing between two genetic entities, picking the group genetically closer to you is even more important when considering genetic structure.  So, when the choice is between self vs. family or family vs. ethny, genetic structure will require a larger genetic payoff before agreeing to sacrifice the interests of the former for the latter. However, when considering a relative choice between ethny one vs. ethny two, genetic structure means that choosing the more similar-to-you ethny is even more important than with “bean-bag” genetics.  

The overall Salterian imperative remains the same as before, once these adjustments are made.

More Genetic Structure and DifferInt Analysis

An important topic.

I have been looking a bit more at the DifferInt program (currently unable to find anything better), testing some model genotypes to better understand the relationship between different levels of integration with respect to the amount of differentiation.  One finding which is clear that it is when genetic differentiation – at the lowest genepool level – between groups is shallow is when the program is scalable at the level of the highest level of integration.

A test model was devised with two populations of eleven individuals each.  Six loci were considered.  Initially, the two populations were constructed to be genetically identical. Four individuals of the second population had alleles at one lock rearranged so that four heterozygotes were made into four homozygotes (two of each type), without changing the total number of each allele type for that locus in that population.  After this change, the genepool differentiation was 0.0303, but the multilocus genotype neglecting elementary genic differences (MGNEGD) was 0.3636 – a twelve-fold increase in differentiation.  In this simple model of shallow genetic difference, a discrete representation of genetic structure (MGNEGD) is seen to exhibit sharply increased (and quantitatively scalable) differentiation with even a small change in allele structuring in genetically similar (model) populations.

However, when differentiation at the genepool level is already fairly high, then MGNEGD rises to complete differentiation quickly, and the ability to evaluate genetic structure becomes non-scalable using this program.  It could be that the SNP database I utilized for my initial human study was enriched in SNPs that sharply differentiate between ethnies and so all levels of differentiation were high in the analysis; perhaps completely random SNPs would be better? On the other hand, we are most concerned about the distinctive genome (with respect to EGI).  

In a more realistic model of human genetic differentiation, two populations were set up, each consisting of ten individuals, each assayed over 100 loci.  90 of these loci were absolutely identical between the two populations and 10 loci differed between the populations with respect to the frequencies of alleles at the loci.  In some cases, it was 100%  of one allele pair compared to 100% of another; in other cases it was more subtle – for example one population having 20% AA, 60% AT, and 20% TT while the other population was 20% AA, 50% AT, and 30% TT for the same locus.  The genepool differentiation between the two populations was 0.0370; the MGNEGD was 1.000 – complete differentiation.  This again shows that with enough loci studied and differentiated populations, analysis of discrete sets of multilocus genotypes (see my definition of genetic structure below) will reach complete differentiation.  The implications for genetic interests should be obvious.

It might be a good idea to review my idea of genetic structure again here.

Genetic structure as per my definition can be viewed as a form of linkage disequilibrium of alleles over all the loci in the genome, or this distinctive genome, of at least whatever number of loci that were assayed.  Each specific permutation of multilocus genotypes is a discrete entity, so that one would expect, of course, district genetic structures between any set of individuals who are not identical twins; there would be differences in genetic structure within families, never mind within ethnies.

However – and this is the key point that separates my idea from the run-of-the mill evaluations of genetic structure – I envision genetic structure to be defined by specific ranges of multilocus genotypes.  Therefore, while there is going to be, naturally, individual variation of discrete multilocus genotypes within families, there will be a family-specific range of multilocus genotypes, a range within which all the individual genotypes, of that family will fall within.  Likewise, there will be ethny-specific ranges of multilocus genotypes, so that members of an ethny will exhibit genotypes that – while they differ on an individual level – will fall within a range, a set, of genotypes characteristic of that ethny.  

It then follows, that while multilocus genotypes will be differentiated from each other, the extent of that differentiation will differ.  Different families will exhibit different ranges, or sets, of possible multilocus genotypes, but families belonging to the same ethny will exhibit ranges that are more similar to each other than that of families of different ethnies (the same goes for individuals of course, across families or across ethnies).  Ethnies belonging to the same continental population group (i.e., intra-racial) will exhibit more similar ranges of possibilities of multilocus genotypes than that of inter-racial comparisons.  One could think of it also as frequency distributions of multilocus genotypes, of all the alleles possibilities at all the relevant loci considered together as a discrete entity, and one can compare how similar the frequency distributions are, with more overlap from those more similar.  

One would also expect a solid correlation, or association, between the differentiation as measured by an allele-by-allele genepool/beanbag approach, single locus genotypes, and multilocus genotypes. The relative extent of differences should correlate in at least a qualitative sense between these levels of “genetic integration.”  Hence, as previously noted at this blog, “complete differentiation” at the multilocus genotype level should differ in extent dependent upon how similar or different the genotypes are from each other.  One should in theory be able to quantitate this in a continuous fashion, rather than just having a binary yes/no undifferentiated/completely differentiated choice.

This is obviously an important topic.  If we are to make decisions based on genetic interests, don’t we need to have a better understanding about what those interests actually are, quantitatively speaking?

It’s true that we know enough right now to justify taking action in defense of genetic interests; even at the lowest levels of genetic integration, and even with estimates of child equivalents based on Fst, we already know that mass migration of alien peoples is genocide.

So, yes, I’m sympathetic to the argument that in general, qualitatively speaking, it is more important to actualize a defense of the interests we already know about than to fine-tune our understanding of these interests. But why not both?  Nothing stops us from both organizing on a political and metapolitical level while at the same time continuing to refine our understanding of this topic.  While most of my work now concerns the political and metapolitical implications of defending EGI and of actualizing a High Culture, surely there is also a place for a better understanding of EGI and for a better understanding of Spenglerian cycles and how to control them foe civilizational benefit.

Preliminary Quantitation of Genetic Structure

Genetic differentiation increases with higher levels of genetic integration.

Ted Sallis


I have finally performed some preliminary analyses of genetic structure – which I (predominantly) define as the association of alleles at different loci, an association that differs between individuals, between families, and between ethnies. The lack of genetic structure calculations is one of the two major genetics-based weaknesses of On Genetic Interests, the other being the reliance on Fst – which is not a real measure of genetic differentiation – rather than on genetic kinship data.  I’m not going to directly get into genetic kinship here (but note that the “genepool” level of analysis of DifferInt does give sort of a measure of genetic kinship, if the numbers are “crunched” appropriately), but since I’ve been discussing genetic structure for so long, here I present a minimal proof-of-principle of genetic structure quantitation with some human SNP data. This is not an optimal study, which needs to be performed by those with the time, expertise, databases, and computational resources do it well and efficiently (the same goes for global genetic kinship assays). Also, the methodology itself is not optimal and doesn’t cover the entirety of the genetic structure concept, but it does at least cover the underlying core principle.  


The DifferInt program dealing with genetic integration (1-3) – based on the work of Gillet and Gregorius on “genetic integration” (2) – was utilized, as well as some lists of human SNPs and publicly available HapMap population SNP frequency data. Thus, HapMap populations were analyzed. Europeans (EURO) included CEU (Utah residents of Northern and Western European ancestry) and TSI Tuscans, East Asians (EASIA) included CHB and CHD Chinese and JPT Japanese as well as a separate set of Chinese samples previously named HCB (instead of CHB), South Asians (SOUTH ASIAN) included GIH Gujarati Indians, Negroes (AFRICA) includes YRI Nigerians and ASW SE USA African ancestry and LKK and MKK Kenyans, and there also was Mex (MEXICAN: Mexican ancestry). I also produced a CEU-YRI hybrid by taking ~ ½ the alleles from CEU and ~ ½ from YRI – obviously, this is NOT how real admixture would take place (there would be mixing of both alleles at single loci as well as multiple loci, as well as other important differences consequent to sexual reproduction) – this is merely a very crude proof-of-principle.

Ideally, DifferInt populations would be ethnic groups and within each population there would be the individuals of that population, each with their distinct genotypes.  Due to the limitations of this study, the design was somewhat different and at a broader level of analysis. Here, the populations are continental population groups (races) and the “individuals’ within the populations are the ethnic groups themselves – actually the consensus genotypes at each locus for that ethnic group.  Therefore, the entire set of consensus genotypes for an ethnic group is what is being called a single “individual” here.  The consensus genotypes are such that for each gene locus, the most frequent genotype at that locus for the ethnic group was chosen.  So, for example, if a locus has AA – 0.2, AG – 0.3, GG – 0.5, then GG was the genotype chosen in this case.  This results in a “model” individual of a consensus ethnic genotype set.  This is sub-optimal for three related reasons: it doesn’t cover the intra-ethnic group variation; it doesn’t cover the frequency distributions of genotype per locus that are, of course, very important; and there are cases where the most frequent genotype is only slightly more frequent than the second most frequent genotype.  SNPs used are those for which I found genotype data for all twelve ethnic groups evaluated; the SNPs were taken from publicly available information sources.  51 SNPs of my initial list fit the requirements.

Whenever there were two genotypes listed as being of equal frequency at a given locus for any group, I chose the genotype that was the same as to the majority of the other groups.  In other words, I was conservative, and when there was a choice, I always chose the option that minimized differences between the greatest number of groups. That serves two purposes: first, to ensure that whatever differences that are observed are definitive, and not merely in part the result of cherry picking of genotypes; second, to obviate claims of a “racist agenda” in attempting to maximize group differences.  

The three levels of analysis are the genepool (i.e., individual allele “bean-bag” genetics), single locus genotypes (association of alleles at one gene locus – i.e., from the two homologous chromosomes), and, most importantly and consistent with my general basic idea about genetic structure, the multilocus genotypes (the association of all the different single locus genotypes together, how genetic variants at multiple loci are associated with each other).  

Each of these levels can be analyzed with “elementary genic differences” or “neglecting elementary genic differences.”  Considering elementary genic differences is an analysis of the number of individual genes that differ in the types of alleles; from the DifferInt manual: “The genic difference between genetic types at the same level of integration is basically determined by the number of their individual genes that differ in allelic type.”

Neglecting elementary genic differences is a discrete differentiation in which 0 is identity of all alleles of all loci and 1.0 being if the types “differ by at least one allele at one locus” – also from the manual: “By replacing the elementary genic difference between genetic types by the discrete difference, the measures…are based only on relative frequencies of the genetic types of the individuals in the population.”  Differentiation is higher when measured with the second, discrete analysis as compared to the first one. Keep in mind that in my crude model the “individuals” are consensus genotypes based on SNP frequency data from ethnic data sets; thus it would make sense that measuring the “discrete difference” would work best for such coarse-grained, “single-point” distinct and discrete pooled samples. Just measuring the numbers of individual genes that differ by allelic type (elementary genic differences) is not measuring (in my opinion) genetic structure (as I define it) per se; measuring the relative frequencies (neglecting elementary genic differences) is somewhat closer to my conception, so I used that for my analysis.

Differentiation is at a scale of 0 (exactly alike, no differentiation) to 1.0 (completely differentiated).

A major flaw in my study is using consensus genotypes, as opposed to actually listing all the individual samples or being able to use allele frequency data (which DifferInt does not do) since, ultimately, we want a range of ethny-specific genotypes characteristic of each group; it would not be a single, fixed consensus genotype.  Using fixed consensus genotypes also makes it even more imperative to look at the discrete DifferInt metrics that neglect the “elementary genic differences.”


(w/o EGD = without [neglecting] elementary genic differences – see above)



Note that the relative differentiation between groups at the genepool level is consistent with what is expected from standard population genetics studies.

Single-locus (w/o EGD):


There is a considerable increase in differentiation considering association of alleles at single loci.  This makes sense, particularly since in many cases differences between ethnies are at the level of whether alleles at the relevant loci are homozygous or heterozygous (which would also have obvious implications for traits affected in a dominant/recessive fashion by the SNP differences, or by gene sequences linked to such differences).

Multiple-locus (w/o EGD):

Was 1.0000 for all comparisons: complete differentiation.

That is not surprising, as combinations of alleles are going to be relatively specific in an ethny-dependent fashion, and the more loci looked at the greater the proneness to distinctiveness.  Of course, with the relatively blunt instrument of combining DifferInt with consensus genotype data, one would expect complete differentiation (with enough loci looked at) at almost any level of genetic difference. The problem here is that while this is informative in a qualitative sense, it doesn’t help gauge relative differences in the degree of “complete differentiation.”  For example, the “complete differentiation” comparing Europeans and South Asians when considering multiple loci is expected to be less than that between, say, Europeans and Africans.  The closer two groups are at the genepool level, the less “complete differentiation” should be expected at the multiple-locus level.  Note that single-locus differences (above) track well with the genepool differences, so the same should be expected at the multiple-locus level if a more scalable metric could be designed.

This lack of scalability at the multiple-locus level may be due to DifferInt itself and/or the type of crude, consensus, discrete SNP data I am using  If it were possible to include allele frequency data – which could be done with this program by actually separately listing each individual with their own genotype rather than a consensus – that would likely help.  Or, if the program itself was changed so that one could just directly include the frequency data for each allelic type rather than having to actually enter each individual as such (although with the proper computational resources and programs I presume listing the individuals would be easy, but I formatted everything by hand, which was tedious).  Alternatively, one could look at relative genetic structure by looking at SNP permutations (not the same type of permutation analysis that DifferInt can do).  One could ask, to what degree are different permutations of allelic types more similar or different? That would be very informative for EGI purposes, if properly designed.

In any case, at least for the data used here, DifferInt was reasonably quantitatively scalable for genepool and single-locus analyses, while multiple-locus analyses were more qualitative.

Also let us look at the CEU/TSI intra-EURO comparison:

Genepool: 0.0392, Single-locus (w/o EGD): 0.0784, Multiple-locus (w/o EGD): 1.0000

Not surprisingly, the intra-European comparison exhibits little differentiation at the genepool level, which is doubled for single-locus integration.  Multiple-locus again shows complete differentiation.  On the one hand, this multiple-locus finding is expected, and makes sense, since the overall genetic structures of CEU and TSI are different.  However, we once again observe the problem of scalability.  EURO/AFRICAN and CEU/TSI both exhibit complete differentiation at the multiple-locus level, but the two are not obviously equivalent. The combinations of alleles at multiple loci for CEU vs TSI are going to be more similar than that for EURO vs. AFRICAN, even if both cases exhibit complete differentiation.  Again, this is a problem with the type of data I used as input, but I suspect as well it is a feature of the program itself. Consider that EURO/AFRICAN differentiation at the genepool level was already at the level of 0.4779 and the maximum possible is 1.0000.  So, it is obvious that the differences are not properly scalable, and likely would not be even with optimal data.  In a properly scalable analytical system, the maximal possible differentiation with multiple-locus analysis should be many-fold greater than that of genepool (and associated with the number of loci examined).  It is at the multiple-locus level that I find this program weakest, which is unfortunate since that is the most important level of analysis.

What the program considers is not perfectly aligned with my conception of genetic structure, but it is not orthogonal either.  There is considerable conceptual overlap; thus utilizing the program at least for a proof-of-principle demonstration is useful.  

The hybrid model (26 loci from CEU, 25 from YRI) is below.  This is, admittedly, highly artificial and not biologically realistic, but makes the general point (real admixture actually would be expected to cause even more differentiation than shown here):


CEU/YRI: 0.5090, CEU/Hybrid: 0.2640, YRI/Hybrid: 0.2450

As CEU would be expected to be a bit more differentiated from YRI (and other Africans) as are TSI, the CEU/YRI genepool differentiation is slightly higher than the more general EURO/AFRICA, although another possibility is that the non-YRI Africans are closer to Europeans than are YRI. Hybrid values are in between CEU and YRI.

Single-locus (w/o EGD): 

CEU/YRI: 0.8341, CEU/Hybrid: 0.4510, YRI/Hybrid: 0.3922

This increases as expected.

Multiple-locus (w/o EGD): 1.0000 for all comparisons.

Complete differentiation, as expected, but again flawed by lack of scale.  The “complete differentiation”: between CEU/YRI would be expected to be larger than that between CEU/Hybrid, bit that cannot be distinguished in this analysis.  Nevertheless, this shows that merely increasing production of hybrid offspring cannot compensate for foregone parental kinship at the multiple-locus level.


The findings (even with the limitations of the analysis) strongly support and extend the EGI concept; ethnies are more genetically differentiated at the level of higher genetic integration than at the mere “beanbag” genepool approach of individual alleles.

However, the gulf between family and ethny is also likely to be increased when genetic structure is taken into account, so one must be prudent in balancing investments.  However, keep in mind two things.  First, the typical ethny is larger than the typical extended family by five to eight orders of magnitude, so the ethny-ethny differences are of greater relative import than the family-ethny differences.  Second, differences will be expected to increase with genetic integration at every level of genetic interest – not only ethny-ethny and family-ethny, but also, for example, between self and family. But the family is needed for the self to have genetic continuity (although one can argue that the larger extended family could be dispensed with as long as the nuclear family is intact, or even that a human male just “spreads his seed” sans family structures), and one can argue that the family needs some sort of ethny, some sort of national culture, for secure familial genetic continuity.  Families mixed beyond wide racial lines are characterized by a deficit of genetic interests for the divergent members of such families, so the fact that those families are less dependent on national ethnies need not concern us, in any reasonable quest to maximize net genetic interests. So, in summary, when all is said and done, the findings here actually INCREASE the validity of ethnic genetic interests (with “ethnic” meaning ethny, which can include race). 

In the future, I may perform some additional analyses with this program and with these (and other) data; but the main point has already been established. Or, better yet, if I can think of other methods of analyzing the data to yield more useful results that would be more optimal.  It would be helpful if others, with more time and computational resources (including better data sets, can generate additional DifferInt data as well as designing better methods for assaying genetic structure (or finding other existing programs; I will search for such as well).

This was a crude analysis, yet very useful I think to “break the ice” on the topic, especially since I can’t help but notice that no one else has been doing it (insofar as I know).  Do you have the time and resources to do better?  Great: Go to it.

Final Conclusions

1. Although the analysis has limitations, it demonstrates that human genetic differentiation increases as genetic structure is considered.

2. A considerable amount of this increase in genetic differentiation is at the single-locus level, which I had not previously considered as being that important.

3. Most importantly, the multiple-locus analysis shows complete differentiation.

4. A problem in this analysis is with the scalability of the multiple-locus determinations, and the program is unable to evaluate the entire genetic structure concept; better methods, analyzed with better data, are required.  In the meantime, it would be useful to even just have more in-depth analyses using DifferInt.

5. When all is said and done, this analysis, even with its limitations, extends the EGI concept.


2. Gillet, E.M., Gregorius, H.-R. (2008) Measuring differentiation among populations at different levels of genetic integration. BMC Genetics 9, 60.

3. Gillet, E.M. (2013) DifferInt: Compositional differentiation among populations at three levels of genetic integration. Molecular Ecology Resources 13, 953-964. 1111/1755-0998.12145

McCain: Genocidal Lunatic

Note to a lunatic.


Note to John McCain: Those who do not care about “blood and soil” will be replaced by those who do.  And those new people could care less about your “ideals.”

From the perspective of European EGI, McCain is a monster.  Optimally, he should be put on trial for crimes against humanity for both his anti-White genocidal politics (e.g., immigration) as well as his relentless warmongering. The man simply cannot be allowed to die from his disease with dignity; instead he must end his life in disgrace, humiliated and ruined.

Rosit on the Penman Hypothesis

Biohistorical speculations.

I really don’t have much to add to Rosit’s fine analysis, except to note that culture is a proximate interest, albeit the most important proximate interest, and one that – as I have written about extensively – affects our ultimate (genetic) interests.  But, any complete analysis of the decline of the West must put EGI first and foremost.  That would, as a matter of necessity, bring forth, directly, the race issue, the inability to deal with fully and honestly being, as Rosit suggests, a flaw in Penman’s hypothesis. Also, while epigenetic modifications are may in particular contexts be important, there are many, on both the Right and the Left, with an axe to grind against “genetic determinism” that overrate the importance of epigenetics with regards to the final phenotype.  

A reasonable analogy would be that the body is the hardware (computer), the genes are the software, and epigenetics may in part determine whether a particular software program is turned on or off.  That’s important, no doubt, but without the underlying software, there’s nothing to tun on or off, without the software, the hardware is merely a paperweight, and  – and this is crucial – not all computers are running the same software.  If one computer has a particularly powerful program and the other does not, all the “turning on or off” in the world won’t make up the difference.  Epigenetics has become an over-rated meme.

Penman’s grim prognosis is more or less correct, and having the pathetic “movement” as the major vehicle for preventing the racial-cultural disaster that is unfolding is part of the problem.

We need to start rebuilding now, before the collapse, and Der Movement is hardly capable of doing so.