HBD Jump Starter
These “Social Constructs” That Nobody Can Shutup About
This article is going to serve as a jump starter for people who are concerned about the topic. Only about 5% of Americans truly believe in genetics and evolution. Many in my sorts of internet circles are more charitable than I am. Most tell the opposition “you think evolution stopped at the neck,” and I disagree with this assessment of their views. The failure to recognize systemic biochemical, anatomical, and physiological differences is simply a rejection of both genes and evolution being facts.
Your political ideology should consider science. This is not limited to science about the climate. This means all of it. When we have these discussions about “racial equity,” immigration, policing, healthcare, and so on, there needs to be a scientific basis to these things that we take as true. The assumptions that most affluent people have surrounding race are factually incorrect and should be met with the relevant science.
Introduction to the Existence of Human Diversity
Here is an article that can replace the entire part 1 in a little bit, however only take the race is real part from it. The rest of it is rambling. Charles Murray called it orthodoxy in his book human diversity to say that race is a social construct. I would call it a sociological mantra, a progressive saying, or a postmodernist cope. A lot of people actually believe it. Elite Universities like Harvard have pages that cite outdated “science,” and have probably convinced themselves that calling it a social construct makes it different. This is probably not how most people think. I think that most people know that there is some genetic basis deep down, but I cannot prove that. I will stick with what I can prove.
The fact is, human evolution accelerated in the last 40,000 years (Hawks, 2007) which is around when humans left Africa. This is contrary to the notion of “actually, there was not enough time for evolution to make these group differences that you speak of!”
Lastly, if you believe that more variation within each group than between them means that they are not real groups, consider applying that argument against the idea of racial inequality. There is more variation within each race than between them in:
— Institutional power (the gap in power between me and a Mitch McConnell is larger than the differences in average institutional power between any two races)
— Experience with police officers
— Prison sentence duration for any given crime
— Incomes
— Number of patents filed
— Number of businesses owned
— Number of houses owned
— Life expectancy at birth
— Educational attainment
— Local school funding
— Standardized test scores
How does this argument sound? It sounds absurd on its surface. This could not possibly be an honest argument.
“There is more variation within Africa than outside of it” is another fallacious argument. For nearly any given trait, there is more variation in men than in women. The biological reality of human sexes is not erased by this.
Many people who say that race is a social construct will argue that there is human diversity, but it is a spectrum so the delineations are arbitrary. This is not really accurate. There is a way to maximize the accuracy of these groups using software programs like PLINK.
The easiest way to put it is the following:
(1) We have these groups that are “socially constructed” or whatever you want to call them.
(2) We cannot reverse these groups. A traditional criteria for sub-speciation was that you could visually identify with 75%+ accuracy, anyways.
(3) There are genetic differences in these groups.
(4) When you ask a computer to make groups of people based on the SNPs or the genes, the computer makes groups that are pretty much the same as what we made on our own.
(5) It does not matter if we do or do not fit the criteria for taxonomic recognition in a biology textbook, group differences in important traits such as aggression or intelligence could exist without using race as a level of taxonomy.
How Different Are We?
We are actually not that different, but it is not an amount of differentiation that should be ignored. It has been previously estimated that two individuals are 99.9% genetically the same, however, these estimates must have excluded variation from deletion and insertion mutations.
Inclusion of insertion and deletion genetic variation into our estimates of inter chromosomal difference reveals that only 99.5% similarity exists between the two chromosomal copies of an individual and that genetic variation between two individuals is as much as five times higher than previously estimated. — Levy et al., 2007
And that number was found only using white people!
Eugenelabs, an Australian company that does DNA tests, has put the number 99.3% on their website. I think that the number will probably reach 99% with time, as not that long ago scientists were saying 99.9%.
It has previously been estimated that humans share somewhere between 98% and 99% of our DNA with Chimpanzees, with common point estimates being about 98.8%. I find this increasingly unlikely — it appears that the number is about 4% different (Varkie & Altheide, 2005, Varki & Neslon, 2007), some have suggested that it may be a larger difference. For the sake of argument, let’s say humans are 99.5% the same and we are 95% the same as chimpanzees. That means that means the genetic difference between you and another person is about 1/10th that of you and a chimpanzee. Again, there are studies that say we are 98.76% the same as chimpanzees, but that is not likely to be true in my opinion.
Regardless, this is still not the best way of measuring diversity. Heterozygosity is a better measure of diversity within a species between individuals.
“Heterozygosity is the proportion of heterozygotes in the population and is defined as H = 2 p q. Note that heterozygosity is zero at “fixation”, the case where only one allele exists (p = 0 or 1), and that heterozygosity is at a maximum when alleles are equally frequent (e.g., p = q = 0.5).” — Brown University
So humans tend to be at the middle of the road it seems. Not as diverse as many of these animals, by certainly not lacking diversity. There are species far more diverse than humans, and species far less diverse, but humans are by no means exempt from typical biology.
I Meant “How Different are Human Races?”
The first thing that we have to do is redefine the language. Ancestral population/ancestry is the best way to go. The way we use the term race in modern context as a separate word from ethnicity is kind of weird. Historically, you will hear people talking about the British Race, the French Race, and so on. For this reason, replacing the word “race” with ancestry gives us the best approach. Within each “race” using modern context, you have subpopulations. The same applies to the word ancestry. Within European Ancestry, you have regions of Europe and within each region is ethnic backgrounds, and so on. Beyond this, the better question to start out with is to explore how effective these categories are.
How Accurately Can DNA Guess Your Ancestry?
The short answer is upwards of 99%, 23&me.com, ancestry.com, and many other cites can break it down by what % each ethnicity you are. So even if this race stuff is just a social construct, we can still guess which “social construct” you are based on your DNA.
Here are images from a person complaining about how terribly inaccurate these cites are:
The secret is that there is no official definition of what is and is not Ashkenazi Jewish, which the author admits in the article that I got this from. The truth is that you have to do mental gymnastics to deny the legitimacy of these DNA tests. Getting stuck up over small errors is silly.
Determining ancestral populations with DNA predates ancestry.com or whatever websites people like to use for that. Rosenberg et al., 2005, Witherspoon et al., 2007, and Porras-Hurtado et al., 2013 examined population structure as well. These are not new by any means.
“correct assignment to the continent of origin (Africa, Asia, or Europe) with a mean accuracy of at least 90% required a minimum of 60 Alu markers or microsatellites and reached 99%–100% when 100 loci were used. Less accurate assignment (87%) to the appropriate genetic cluster was possible for a historically admixed sample from southern India.”
Modern technology that processes much more of the genome than 100 gene loci and 60 Alu markers is going to make far fewer errors with admixed populations.
How Far Apart?
As far as quantifying the distance between two populations, this is done with fixation index
“Population structure is usually quantified by a simple statistic known as Fst. This stands for the “fixation” index resulting from comparing sub populations to the total population, and is used to quantify the proportion of genetic variation that lies between subpopulations within the total population. An important way of thinking of this problem is to compare the mean heterozygosity averaged across all demes to the heterozygosity that would result if all demes were pooled into one big population.” — Brown University
To visualize this better, here is a graph from Human Diversity by Charles Murray. The colors (socially constructed) seem to correlate a lot with the biological clusters (clusters of dots).Yes, when you give GWAS data to a computer (Murray used PLINK), and you ask it to make groups of people, these are the groups it makes.
Obviously there is much more diversity inside of Africa that you may not see on this on this map, however, the discontinuities are apparent.
Being said, “PCA only partially identifies population clusters and does not separate most populations within a given continent, such as Japanese and Han Chinese in East Asia, or Mende and Yoruba in Africa”(Gaspar and Breen, 2019).
This really shows how accurate race is as a taxonomy. It is really hard to tease apart the different ethnic groups. In fact, here are some Fst values from the 1000 genomes project with a little bit of visual assistance to help understand the genetic distance of people within races vs. between races
Cat/Dog Breed Analogy?
While some have argued that human populations are not comparable to dog breeds or cat breeds, others have been more curious.
It is true that a whole lot more of the population variance in dogs can be explained by breeds than “races” can explain in humans. One sleight of hand trick in this point is that if I were to replace the word “race” with “ethnicity,” I could close the gap a good bit. By making more groups that are more specific, you can increase the total variance explained by the groups.
Overall, I am going to have to disagree with Emil and others who suggest that the human races and dog breeds may be comparable, however, I do understand there argument and it is more of a trollish thing to due than anything else.
Here are cat breeds from Menotti-Raymond et al., 2008 for another reference — again, Fst values mean different things depending on the total population variance of the species.
Future of Human Population Genetics
There are newer methods to calculate Fst that are much more complicated, but will have more practical utility in the medical field. Using these methods, you find much larger numbers.
It should be abundantly clear that the number of subpopulations is undefined and do not have to be objective. It is similar to asking how many kinds of cake there are. It depends on how specific you want to be — in real life, what you would do (if you are like me) is ask if you lump all the kinds of ice cream cake together or if they want you to name each specific kind. In genetics, you do not do that. There is a value called a K value which means the number of subpopulations. When given a K value, software programs (such as PLINK) can be used to form groups that maximize the genetic variation between groups.
The red/orange dot above the Caucasus cluster is the Kalmyks. The Kalmyks migrated from Dzungaria, China in the early 1600’s. Them not clustering with the Caucasus group is not so much the slam dunk that you wish it to be. Yemenis clustering with North Africa is not a surprise either, given the out of Africa migration.
