The depressing story of the American continent.

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[–]Fitter_HappierWhite Nationalist 5 insightful - 3 fun5 insightful - 2 fun6 insightful - 3 fun -  (54 children)

those countries are poor because they lack Jewish leadership

You're a fucking retard.

[–]Node 5 insightful - 2 fun5 insightful - 1 fun6 insightful - 2 fun -  (0 children)

More like novelty account or troll. I'm betting on troll, whether it's an actual jew or just a hateful leftist.

[–]milkmender11 2 insightful - 3 fun2 insightful - 2 fun3 insightful - 3 fun -  (52 children)

Wow, you guys descended from supposedly rational arguments into belligerent name-calling but right quick. I haven't got a horse in this race, just here to see both sides, but they say that the side which resorts to this 'argument' first is the one with the losing rhetoric, and it sure looks that way from here. Even if he is a troll, did you not have a better retort? Will you spout profanity at me now, too? How far your 'proud' race has fallen! You don't come across as proud so much as bitter and jaded. Are you mixed?

[–]EuropeanAwakening14 5 insightful - 2 fun5 insightful - 1 fun6 insightful - 2 fun -  (46 children)

Looking at your post history, you already decided we were wrong because we correctly identify Europeans as White and visa versa. You have a very strange and poor understanding of race. Watch some alternativehypothesis/peoplesveto on YouTube or Odysee and try again.

https://impute.me/ethnicity/

Use the code id_613z86871. Go to advanced settings. Select European and individually compare to every other category one at a time and then all at once. Tell us what you learned.

[–]milkmender11 2 insightful - 1 fun2 insightful - 0 fun3 insightful - 1 fun -  (45 children)

Please, educate me on race. I'm published on the subject--I'm an anthropological geneticist.

What race are you, and what is your justification for the claim? Your link there, unfortunately, is not scientific. Do you know what a SNP is? Do you know what an 'ethnically dependent' SNP is (hint--it is not a scientific term)? Do you know how we do these cluster analyses, and did you know that the assumptions involved in performing this kind of analysis actually invalidate your point before you even try to make it?

You didn't think that's how this research worked, did you? Do you know how we perform these studies? Do you know what software we use, and what markers we look at to make our 'race' designations, and do you know why we do it? These are very important questions, but most people who are not professionally involved with the science don't know the answers.

Please, let's have a discussion about this. This is what the sub is for, after all! I have seen people on the alt-right say, "academics please respond!" Well, here I am :)

I am especially hoping that we get as far as the mythical ML 'objective k.' I would be impressed!

[–]shilldetector 3 insightful - 1 fun3 insightful - 0 fun4 insightful - 1 fun -  (0 children)

Bragging about being published on the subject isn't helping your case any. We all know the only way to get published on this subject is to tow a particular line, so you are basically admitting that this is what you've done. I'm far less knowledgeable on the subject than you, but there are many people who are almost certainly more knowledgeable and accomplished on the subject who vehemently disagree with you. They just aren't able to be as open about it.

One of the ways I differ greatly from the alt right is their obsession on race and genetics. I see it as largely irrelevant. Regardless of whether being white is a social construct it is very much a thing, as the media continually remind us. If you are white in our increasingly anti white society, there's pretty much no way to weasel out of it, despite millions of whites attempting to do exactly that.

To me being white means being of indigenous European ancestry. Period. Sure Europeans differ from each other to a fairly large extent, but they are still more genetically related to each other than they are to non Europeans, and more importantly they have a shared history with each other, even if much of it was warring with each other. Denying that shared heritage and now shared discrimination isn't going to work out well for those who do it in the long run.

I also differ from the alt right in that I don't stress too much about declining numbers. As our numbers grow smaller, those that are prone to hating themselves and other whites will breed out or die out, which is fine, that is their choice, but we aren't going away. We are simply trimming down to fighting weight.

[–]MarkimusNational Socialist 2 insightful - 2 fun2 insightful - 1 fun3 insightful - 2 fun -  (5 children)

Proof or ban for misrepresenting yourself. (Rule 3)

[–]milkmender11 2 insightful - 1 fun2 insightful - 0 fun3 insightful - 1 fun -  (4 children)

But I would have to dox myself in order to prove it. Are you asking me to dox myself?

[–]MarkimusNational Socialist 2 insightful - 2 fun2 insightful - 1 fun3 insightful - 2 fun -  (3 children)

If you're a public intellectual why would you care about discussing your own work? Unless of course you're just lying to try to stifle discussion.

[–]milkmender11 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (2 children)

I'm no public intellectual. I am an anthropological geneticist employed by a university. If they knew I was debating alt-right folk at all, it would create professional problems for me. I can only request that the mods see my post below as a proxy for 'proof'--you might disagree with me, in fact I expect that you do, but only educated researchers have that much knowledge of this subject. Certainly, at the very least, a talented graduate student.

[–]MarkimusNational Socialist 4 insightful - 1 fun4 insightful - 0 fun5 insightful - 1 fun -  (0 children)

I don't have a horse in this race at all, I don't give a fuck about gay continuum fallacy bullshit or materialistic analysis of race. Race is an idealistic and social reality regardless of how much continuum fallacy soyentists can apply to try to deboonk it.

I was just saying if you're going to try to use anti-debate tactics IE 'I am an intellectual in this field therefore I'm correct and you're not allowed to disagree with me' you should at least prove it otherwise it's clear you're just trying to stifle discussion and not engaging in good faith. If your arguments are correct they are correct regardless of you posturing as the Almighty Authority and Holder of Truth™. (by the way doing this is cringe and not impressive in the slightest, appealing to your supposed credentials online, especially if you don't even prove it, makes you look like a bugman faggot)

[–]shilldetector 3 insightful - 1 fun3 insightful - 0 fun4 insightful - 1 fun -  (0 children)

I am an anthropological geneticist employed by a university. If they knew I was debating alt-right folk at all, it would create professional problems for me.

That says something about the state of modern academia that a supposed scientist is unable to debate matters of science for fear of professional repercussions. You are admitting that you would be cast out for debating heretics.

[–]DragonerneJesus is white 2 insightful - 1 fun2 insightful - 0 fun3 insightful - 1 fun -  (37 children)

Finally, I would love to have this debate if you want to do that in good faith.

The best argument for race is that when we put the genetics of different populations into a clustering algorithm we see that the clusters closely relate to what we consider races. Blacks cluster together, Europeans cluster together, East Asians cluster together, Oceanians cluster together and american indians cluster together etc.

If race didn't exist we wouldn't expect that to happen. It could've just as well have been eye colors, hair color or some other random attribute or combination of attributes that would best represent the clusters, but what we find is that RACE is what the generic clustering algos produce.

Another argument is that if you take 2 whites or 2 blacks they will always be more similar than say 1 random black and 1 random white. This indicates that races are surprisingly well seperated. The famous saying: "more distance between than within populations" (tongue in cheek)

Now of course you will have mixed race people like a color spectrum between the races/colors. Arguing against races is like arguing against blue, red, green, yellow etc.

[–]milkmender11 2 insightful - 1 fun2 insightful - 0 fun3 insightful - 1 fun -  (36 children)

The program we usually use is called STRUCTURE. It's likewise the program where nearly all of the data from your link came from. STRUCTURE is hardly equipped to perform objective scientific analysis--it is, like many things in social science, a program which draws upon some scientific data to infuse it with social hypotheses and answer a specifically formulated, purposeful question. We can't use STRUCTURE to figure out true things about reality, the way we can use astronomical analysis packages to derive conclusions based on the data that a space probe collects. STRUCTURE requires a human element--the data, on its own, speaks for itself, as far as it can. We need to tell STRUCTURE what to look for, and in doing so, we tell it what is important to us, personally.

Take racial clusters, for instance. Those uneducated in genetic sciences see your link and assume that racial clusters are real, that they are true, and located in the data. They mistakenly believe that STRUCTURE draws this truth out of the data for all to see. However, STRUCTURE has no way to determine the correct number of racial clusters. We actually have to tell it how many we want to see. If you want to believe that there are 7 racial clusters, you can tell STRUCTURE to look for 7. It will find 7--after all, that's what you told it to do. If you ask it to find 12, it will find 12. The simplest operation is to tell STRUCTURE to find 1 cluster, and this is presently the most widely accepted number of racial clusters that exist. Sometimes the data looks more visually appealing to us, looks like it 'ought' to be 7, or 12, or 23. But we can always use a sharper magnifying glass, or take a step back, and see that, in terms of genetic science, there are only as many 'races' as we choose to see. Usually, we choose a certain number because we have a specific question, often epidemielogical, that we want to answer. The 'correct' number of races in each instance is whatever helps us answer that particular question.

I should point out that I am providing you the courtesy of pretending that 'race' is a legitimate taxonomic category. It is not. 'Race' typically refers to subspecies, which is likewise not a defined classification. There are hundreds of studies that use hundreds of different definitions of what qualifies as a subspecies. Historically, the definition has only had glimmers of consistency across specific areas of research, for specific species and genera. For example, wolf researchers tend to use 'subspecies' in the same way, because they cite other wolf researchers who used it that way. It is a totally different story for drosophila researchers. So, again, before we have started, your premise is non-scientific. But I don't even need to win on that point--this is my job, I could give you free points all day and still win.

You should be aware: your link is very misleading, and has hoodwinked you. These 'ethnically dependent' SNPs? My, that sounds impressive! Damning, even! How could I possibly argue with 'ethnically dependent' SNPs? Easy.

These SNPs are specifically derived from unexpressed remnants of viral DNA (retrotransposons) that mutate very rapidly. Because they do not have an effect on our phenotype, these mutations are not 'pruned' by natural selection. They are then able to proliferate and diversify, and allow us to compare samples of aDNA (ancient DNA) to modern samples, and match up who is related to what groups based on the pattern of mutations.

Do you see an obvious problem? Humans are so incredibly closely related, so lacking in genetic diversity compared to most animals, that we have to go far out of our way to be able to detect differences at all. We actually need to look at genes that don't do anything. We need to look at genes that have no effects on us, because if we try to find genetic diversity elsewhere, we come across too many stumbling blocks. Your 'ethnically dependent' SNPs, the keystone upon which your link depends, are quite precisely the LEAST MEANINGFUL genes in the human genome. That isn't a coincidence. That's the only way we can reliably distinguish our personally preferred number of races--by looking at genes that don't do anything. You are using genes that don't do anything and saying that they enable us to distinguish race. If race is so self-evident, why don't you look at genes that DO things? Because you can't. The analyses will be inconsistent. You would have to pick and choose genes that make your point, and ignore that vastly higher number of genes that don't. Or, you could perform a genome-wide analysis, which will put you in exactly the same position--the differences will be so small relative to the whole of the genome that, by definition, they will fail to meet the standard of statistical significance. I've been doing this for a long time.

I'm not naive on this science. There are certainly genes that have an effect on IQ, testosterone levels, impulsivity, etc. These genes are predictably distributed in various popilations. We all know where they are prominent, and where they aren't. But you aren't talking about that. You are trying to shoehorn in Biblical 'kinds' into modern science, under the same guise of 'race' that the racialists of the 19th and 20th century used. Your fundamental hypothesis is Biblical, not scientific. And, the anthropologist in me sees your conflict with the Jews for precisely what it is--family squabbles. Jealousy of the more 'successful' big brother, who isn't letting you in his clubhouse.

To be clear, you led with your BEST argument. I didn't characterize it as such, you did. I demonstrated why that argument is, scientifically, nonsense. It is one I have heard many times, and proliferates on boards like this. It is actually a running joke in the genetics community.

Pleaze recognize what has happened here. Your BEST argument (your characterization) was bunk. Total drivel. Useless. 'Pseudoscience' is too decent a label for it. This is why I was hoping you would invoke machine learning as a means of possibly determining an objective k (cluster) value. But we didn't even get that far.

[–]DragonerneJesus is white 3 insightful - 2 fun3 insightful - 1 fun4 insightful - 2 fun -  (35 children)

Ok, did you read my last post or did you go autopilot? Did you notice that the clusters correspond to races, not eye color, not hair color, not some other random combination of attributes? This fact alone should tell you that the concept of race has a significant categorical meaning. The clusters could've been completely unrelated to the races but they are not. In fact the clusters correspond very surprisingly to exactly how humans perceive races (okay, exactly is an exxageration, but you get my point, swedes lie close to danes, greeks close to italians, whites far from blacks and so on, exactly as we would expect). Please try your best to explain away this phenomenon, because you failed to do that so far.

Okay, now I will adress your concern of the arbitrary k. The first point is that it does not matter "how many races you choose", you can pick 10, you can pick 3, you can pick 23 if you want. This is how race is defined and understood in the alt right anyway (and in our genetics circles too).
Now if you have trouble choosing the number of k, I can refer you to this article: https://medium.com/analytics-vidhya/how-to-determine-the-optimal-k-for-k-means-708505d204eb
I personally use the elbow method but either works. This is basic 1 year undergraduate stuff.
I don't use STRUCTURE, I use python.

'Race' typically refers to subspecies, which is likewise not a defined classification.

Again, I already adressed this with the color spectrum fallacy. This is not a very advanced idea that you have. Its a common misunderstanding that is widespread in social sciences because they want everything to be as "subjective" as possible.
With this type of logic, you can make the concept of "species" meaningless, which is simply absurd. We use categorization to say something meaningful about the data. In the case of genetic clustering, we are using a similarity measurement as the target function to optimize. "How similar is this individual that individual", "Sort them into k similar groups", "Here you are".
Your problem is that k is not as arbitrary as you want it to be and also that the clusters correspond perfectly to what people think of as race.
If the clusters didn't correspond to our understanding of race, you might've had a point, but that's not the case.

But I don't even need to win on that point--this is my job, I could give you free points all day and still win.

Your point is that you can use different measures for categorization. You don't ever prove that these measures don't result in racial clusters. But with that said I will gladly say that it seems reasonable to think that you could find some arbitrary clustering measurement (not genetic similarity) where the the clustering does not end up corresponding race, but I don't think this has any relevance for this topic.

If race is so self-evident, why don't you look at genes that DO things? Because you can't.

This is what I call ceding ground. You already acknowledge that races do exist. That whites are genetically more similar to other whites than they are to blacks.
Your strategy now is to claim that the racial clusters aren't "useful enough" and that we should only use a predetermined subset of the genome to create the clusters...
How many loci are you talking about here? How few should we use for you to think it is "useful enough"? Is it curiously so few that it makes the lewontin fallacy relevant? Is that it?

Or, you could perform a genome-wide analysis, which will put you in exactly the same position--the differences will be so small relative to the whole of the genome that, by definition, they will fail to meet the standard of statistical significance. I've been doing this for a long time.

Genome wide clustering seperates the races well. Am I misunderstanding you here? I think I am, if you could reformulate it, because I didn't get your point.

I'm not naive on this science. There are certainly genes that have an effect on IQ, testosterone levels, impulsivity, etc. These genes are predictably distributed in various popilations. We all know where they are prominent, and where they aren't. But you aren't talking about that. You are trying to shoehorn in Biblical 'kinds' into modern science, under the same guise of 'race' that the racialists of the 19th and 20th century used. Your fundamental hypothesis is Biblical, not scientific. And, the anthropologist in me sees your conflict with the Jews for precisely what it is--family squabbles. Jealousy of the more 'successful' big brother, who isn't letting you in his clubhouse.

I don't know why you had this garbage paragraph. Lets keep being on topic, thanks. You're published, so no need to divert attention elsewhere. Would be appreciated.

To be clear, you led with your BEST argument. I didn't characterize it as such, you did. I demonstrated why that argument is, scientifically, nonsense. It is one I have heard many times, and proliferates on boards like this. It is actually a running joke in the genetics community.

No, you had a misunderstanding how clustering algos work that a 1st year undergraduate wont ever have. I think this is included in chapter1 in a lot of books and I just pulled up the first medium post on the search engine. Let's cut the arrogance a bit. I treated you with respect in my initial response and I hope that you will reply properly going forward, otherwise I will return in kind.

Pleaze recognize what has happened here. Your BEST argument (your characterization) was bunk. Total drivel. Useless. 'Pseudoscience' is too decent a label for it. This is why I was hoping you would involve machine learning as a means of possibly determining an objective k (cluster) value. But we didn't even get that far.

I look forward to your next reply. Please keep the arrogant attitude to a minimum. I know you've been taught that we're dumb, so if that is true, less talk and show your knowledge through your presentation of your arguments. They were sorely lacking so far.

[–][deleted] 2 insightful - 2 fun2 insightful - 1 fun3 insightful - 2 fun -  (2 children)

I may be reading this whole process between the two of you incorrectly, and am somewhat skimming, but it looks like she's trying to make the point to you that the systems they use are different than what you keep bringing up. SNP runs quite a bit deeper than just general ethnic analysis, but there are SNPs that they're able to use to relate towards ethnicity. It's like parsing out each little code within your genetic makeup instead of a broad picture. Ethnicity analysis is the cliff notes version, from what I understand. I'll let her explain, she's the one with the education stats and experience.

[–]DragonerneJesus is white 3 insightful - 1 fun3 insightful - 0 fun4 insightful - 1 fun -  (1 child)

Her claim is that we are using data that is meaningless and that the racial clustering is happening in the subset of the data that is meaningless. She wants to strip the data of meaningless data and then cluster based on the remaining meaningful data. Her implicit (never proven, never explicitedly stated) claim is that doing so would result in a clustering that does not correspond to the racial groups.

In the first part, she is saying that race as a concept is biologically real and in the second part, she is moving the goalpost and saying the concept is real but meaningless/worthless/without value.

[–]milkmender11 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (0 children)

That is definitely not my claim! As my superviser said, 'There is no such thing as bad data.' Of course that data is not meaningless it is very useful for tracking ancestry, and that is exactly what we use it for. But it is useless for making meaningful distinctions between groups of people, because the genes don't DO anything. At best, you can try to use them as a proxy to say, "Well, if these do-nothing genes can be shown to form haplotypes, maybe they correspond to do-something genes that are also predictably distributed!" And you know what, it IS possible to demonstrate predictable distribution of some genes along the same lines as ancestral SNPs. But only some genes. And usually NOT the genes we socially consider important when it comes to race, like skin or eye color. It's a pretty pitiful result, but only if people are expecting it to justify race. It is what it is scientifically. Not meaningless, but not as meaningful as many on this board would like.

I never said race was biologically real, I assumed the putative truth of my sparring partner's positon as a Socratic exercise in demonstrating that it cannot be right, even if I operate from his assumptions.

[–]milkmender11 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (31 children)

Dragonere, I dismantled your point completely. Let me try to explain it again.

Your 'clusters' are literally human opinions. They do not exist as scientific data. You are talking about a research package called STRUCTURE which I and other scientists use. In order to get ANY clusters from this program, we must put the desired number of clusters in ourself. You are acting as if these clusters are real data. They are not. Every time you talk about any number of clusters, you are referencing a specific researcher who decided to arbitrarily use a given number of clusters. You actually have to open STRUCTURE and TELL it how many clusters you want. It can't give you ANY clusters, none at all, until you tell it to give you a specific number. Your clusters, literally, are arbitrary opinions. They are not in the data. They never were. There is no 'race' to correspond to, either. Race is not a defined scientific concept. I am talking about science here.

Here is what you are doing: without realizing it, you are choosing to use a number of clusters that corresponds to the 'races' you want to see. You say they 'correspond.' They do not. You have to first choose an arbitrary number of clusters (a k value) for STRUCTURE to give you. Then, you backwards-rationalize that number into alignment with the racial categories that you want to believe in. What about two races? You can tell STRUCTURE, 'give me an output with two clusters,' and it will. What would your preferred two races be? You can ask it to give you 3, 4, 5, literally any number that is equal to or less than the number of individuals. Hell, you could use data that includes multiple samples from single individuals and ask STRUCTURE to give you more clusters than there are individual humans in your sample!! And it WOULD! You are only talking about a program, STRUCTURE, that you are only just learning about from me. I have been using this program for years.

Finally, the ML k values. I read your link. Honestly, I'm not sure why you would use this when I quite literally taunted you to use it in my first post. I asked you to bring this up. Don't you know a trap when you see one?? The first problem is that it assumes a single level of magnification for the sample. It decides to look at the data at one level of magnification--not closer, not further. This is precisely what I said in my previous post. Of course, at a specific level of magnification, it 'looks' like there are 3 clusters. So, again, you arbitrarily choose 3, and just pass the buck to an algorithim which you have chosen in advance. You have not gotten away from the arbitrary nature of the k selection at all. You simply loaded up your data at one level of magnification, chose the number 3, and ran an algorithim that would give you 3, based on your hunch. If you zoom out, you will see 2, or 1. If you zoom in, you will see 4, 5, 6, up to as many individual points of data that you have. This is how cluster analysis works. There is no one 'true' or 'correct' algorithim that will give you an objective k value, and I can prove it right now. I actually found this tidbit in a paper by a researcher who runs exactly this analysis, who used this argument to debunk your claim in advance, because he knew people would make it.

Take your Magic Algorithim, the one that gives you your Objective K. Let's say it's 7. Ok, now an algorithim gave you the k value of 7, and you can pretend that you didn't choose that number, that The Gods of Science did. Wow! What a great algorithim. It is so great, let's run it on the same sample again!

Whoops. 49. Get it?

Algorithims to magically 'justify' k values are not an escape to your problem of arbitrary k designation. They just pass the buck to an algorithim that was likewise developed by a person. You see that graphic in your link, it is obviously 3 clusters at that scale, so you run the algorithim that you already know will give you 3. You are abusing the function of that algorithim. Its intended function is very much like an ANOVA or MANOVA. It is a confirmation test, a way to say: "Hm, I am pretty sure I see 3 clusters here, at this scale, and I do indeed want to use 3 clusters in my analysis. However, I worry that if I eyeball it like this, the peer reviewers will take issue with that. What I can do instead is use this algorithim to confirm that, at this scale, the computer also sees 3 distinct clusters. It might seem obvious, but this way, my reviewers won't be able to chastise me for eyeballing the chart. It is obvious that I see 3 clusters here, but this is just one little test I can use to not make it seem like I am choosing to see the 3." This is common. The more we can seem like we have a test to back us up, that it isn't our opinion, the more likely we are to get through peer review. You seem to think of science as more rigorous and monolothic than it actuall is. Hard reality check, my friend, we are just a bunch of stressed and overworked peons like everyone else. In a way, your idealism is invigorating, and reminds me of my more energetic graduate students. You would have made a decent geneticist, with a proper superviser, of course :)

It's great that you use Python. Wonderful. I am glad you are developing skills. That does not change the fact that your data, the data you cited, with your first link, mostly came from studies which used STRUCTURE. I am quite familiar with those studies, having cited them myself. The same researchers who published them would tell you the same things I am telling you now. I learned much of this from their papers myself.

You didn't address the issue of the taxonomic nonexistence of the race concept. You handwaved it away and made reference to the color spectrum argument, which I didn't use. I understand if these arguments may be new to you, but please respond to the arguments I make rather than the ones you feel you are prepared to debunk, that I never invoked.

You are incorrect that my argument could be used to nullify the species concept. There are several species concepts, each well defined, with conventional classification criteria. This does not exist with the race concept. Actually, this is rich! YOU are using the equivalent of the color spectrum argument to say that my correct designation of the race concept as an undefined taxonomic classification, is tantamount to denying species classification wholesale!! Brilliant! It's as if you are saying that if I throw away the subspecies concept as a scientifically robust taxonomic criteria because it is inconsistent, then I must also throw away the species concept because there are moments when its consistency flickers. But that IS the color spectrum argument, which you already reject!

You then again claim that k is not arbitrary, but fail to recognize that a human told STRUCTURE, or your analysis package in Python, how many clusters to find. At best, you can arbitrarily choose a specific scale where you see 3 clusters, and run an algorithim that will show you 3 clusters. Zoom out, adjust the parameters of the algorithim, and you will see 1 cluster. Zoom in, adjust, you will see 10. Or 100. Arbitrary. Or, just run the algorithim on the clusters it produced. Why not? If it worked so well the first time, why not learn more. And all this on selectively chosen SNPs that do not express in phenotypes, not a random sample of genes. Hell, if you did choose a random sample of genes, you analysis would look overwhelmingly Chinese.

[–]DragonerneJesus is white 4 insightful - 1 fun4 insightful - 0 fun5 insightful - 1 fun -  (19 children)

I will try to teach you some basics of how clustering works. Now I've never used your program STRUCTURE, I use python myself, but I've spend the last minutes reading up on the documentation of your program and its not a surprise to find that your program uses the "k-means clustering algo". Its also unsurprisingly the algorithm used in the link that I sent you.
"The K-Means algorithm needs no introduction. It is simple and perhaps the most commonly used algorithm for clustering."

It is not an advanced clustering algorithm but thats fine. In this, simple is better. With K-means you have to specify K before running the algorithm. You pick say 7 clusters, run the algo and the algo returns 7 best fit clusters, exactly as you specified.

You can pick any number. If you want 10 clusters you set k=10 and the algo will output 10 clusters.

In order to get ANY clusters from this program, we must put the desired number of clusters in ourself.

Yes, that goes without saying. Did you read the article I gave you that described how we can estimate the best K to choose?

Your clusters, literally, are arbitrary opinions. They are not in the data.

See I think this is where your lack of understanding of this subject starts. The clusters are not arbitrary opinions. The number of clusters is arbitrary and must be chosen somewhat subjectively, although we can pick an optimal k using 1st year undergraduate methods.
If you pick 2 clusters, the algo will not give you "arbitrary opinions" as you wrote. Instead it will provide the 2 clusters that best split the data.
0. Preconceived ideas about racial groups
1. Choose K
2. Algo returns K clusters
3. These K clusters that our algorithm returned describe the same groups that we had in our preconceived ideas about racial groups.

Please pay attention here, because you seem to have missed this point several times now. We are NOT telling the algorithm to create K racial groups!!! We are telling the algorithm to create K clusters from the genetic data. This is a VERY important distinction.
Why? Because if racial groups were pseudoscience, then we would NOT expect the algorithm to return K clusters that align almost perfectly with our preconceived ideas about racial groups!!
If racial groups were pseudoscience, we might find that the algorithm would return K clusters that happens to correspond to hair type groups, or eye color groups, or nose length, or height, or IQ, or whatever random group you might think of. But AGAINST ALL ODDS, the neutral algorithm returns K clusters that just happens to correspond to our racial groups! This is a wild coincidence.

Hell, you could use data that includes multiple samples from single individuals and ask STRUCTURE to give you more clusters than there are individual humans in your sample!! And it WOULD! You are only talking about a program, STRUCTURE, that you are only just learning about from me. I have been using this program for years.

Please keep the arrogance down. I could write the clustering algorithm that you're using from scratch, it is nothing special, and I think you might want to read an introduction to k-means clustering algorithms, because you seem to have some very basic misunderstandings about the algorithms that you're using.

Here is what you are doing: without realizing it, you are choosing to use a number of clusters that corresponds to the 'races' you want to see. You say they 'correspond.' They do not. You have to first choose an arbitrary number of clusters (a k value) for STRUCTURE to give you.

I don't know if this is a case of low IQ or you just not being familiar with how the k-means algorithm works.
https://youtu.be/HVXime0nQeI
https://youtu.be/4b5d3muPQmA

Here are some videos for you to watch, which I would advice you to go through. Especially if you've been using that program for years and still haven't taken the time to understanding the fundamentals of how it works.

Assuming its not an issue of low IQ (because then we can keep going back and forth forever), we don't tell the algorithm to give us the racial clusters. We tell the algorithm to give us K clusters. And these K clusters HAPPEN to be the racial clusters. You are saying the opposite: We tell the algorithm to give us K racial clusters and then the algorithm gives us K clusters that of course correspond to the K racial clusters that we told it to give us.
What you are saying is NOT what we are doing. We tell it to pick, say, 7 clusters, the algorithm could decide to give us 7 clusters that correspond to red hair, brown hair, black hair, yellow hair, blonde hair, golden hair, orange hair but thats not what the algorithm returns.
It returns 7 clusters that nicely correspond to 7 racial groups.

It is so great, let's run it on the same sample again!

Whoops. 49. Get it?

The elbow method wont return k=49 after having returned k=7 on the same sample. But, I can see some situations, where the returned k might differ if we introduce randomized initial configuration of the k-means algo. However setting the random_seed to a fixed number solves that "problem" (its not a problem, it just introduces some randomness into the data analysis, which is not even a bad thing imo)
One time the algo gives you optimal value of k = 7 and other times it gives you k = 10.
This is not arbitrary, its not a problem with the concept of race either, its also likely due to how the k-means algo is setup. Randomness does not suddenly introduce any human element to it either.

Are you of the misconception that race realists believe that there exists a fixed number of races? This is not the case. No one holds that position.

That does not change the fact that your data, the data you cited, with your first link, mostly came from studies which used STRUCTURE.

Are you conflating me with someone else?
I simply want to argue that race is real. You have been failing so far to deal with any argument that I've put forth and you have come to this debate underprepared, showcasing poor knowledge/fundamentals of the underlying algorithms and possibly a mental barrier where you conflate "k clusters correspond to k racial groups" with the incorrect view that we "choose k racial clusters and algo returns our chosen k racial clusters" which is not what is happening. This could also be a simple misunderstanding that you have of how the algo works.

You didn't address the issue of the taxonomic nonexistence of the race concept.

Please reformulate it then, because I fail to see how I haven't dealt with this. The same objections that you're using against race can be used to deconstruct the concept of species.

You then again claim that k is not arbitrary, but fail to recognize that a human told STRUCTURE, or your analysis package in Python, how many clusters to find.

No, it didn't.

Could you explain what you mean by "level of magnification"? Is that a structure specific term

At best, you can arbitrarily choose a specific scale where you see 3 clusters, and run an algorithim that will show you 3 clusters.

This is against all laws of data analysis.
Please watch this introduction video:
https://youtu.be/fSytzGwwBVw
And then this video:
https://youtu.be/EuBBz3bI-aA

If you view your data and then decide your parameters based on this, then you don't get an unbiased estimator. In this case your estimator will be very biased and we say that its "overfitting". You're choosing your model based on your data... can't do that.

[–]milkmender11 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (18 children)

Before I start, let us clarify, YOU brought STRUCTURE into this discussion, not me. It's your citation, not mine. The first link you shared uses data from studies that used STRUCTURE as their analysis package. I'm surprised that you freely admit that you didn't know about it and are only reading about it now, because it was the very first thing that you brought into this debate.

Did you read the article I gave you that described how we can estimate the best K to choose?

Yes, but you weren't the first one to show it to me. That's why I asked you to link to it in my first post :)

The clusters are not arbitrary opinions. The number of clusters is arbitrary and must be chosen somewhat subjectively, although we can pick an optimal k using 1st year undergraduate methods.

Well of course the computer doesn't come up with the clusters arbitrarily. It is done through machine learning. Yes, the number of clusters is arbitrary, as you acknowledge here. But there is no such thing as an 'optimal k' outside of a specific question. Again, clusters do not exist in reality. They are scientific tools that allow us to answer specific questions and test specific hypotheses. You are seeing 'optimal' and making the mistake of assuming that 'optimal' means 'correct.' It doesn't mean that. It means 'optimal for the parameters of our research question.' There are as many optimal values for k as there are different ways you can meaningfully analyze the data with different k values. This is how clusters work.

I am noticing a pattern here--you use your space to explain something, then sneak in a (willful?) misinterpretation of what I said, and hope that I let it go unnoticed. It hasn't worked so far, and it isn't going to.

If you pick 2 clusters, the algo will not give you "arbitrary opinions" as you wrote. Instead it will provide the 2 clusters that best split the data.

Here's your problem. You say that the algorithim does not give you arbitrary opinions. However, I have a very good friend who can debunk you right now. I will quote him directly: "The number of clusters is arbitrary" My friend is very smart and you stand no chance of defeating him. In his deep wisdom, he acknowledges that the number of clusters is arbitrary. That assumption, that arbitrary nature, follows the rest of the analysis. It is rooted in something arbitrary. Try to tell a peer reviewer, "Ok, yes, I know I chose the initial value arbitrarily, but I promise, the analysis which proceeded from that arbitrary value is NOT arbitrary!" It is by definition arbitrary. If you want to escape that, you MUST find a non-arbitrary way to determine your original number.

Please pay attention here, because you seem to have missed this point several times now. We are NOT telling the algorithm to create K racial groups!!! We are telling the algorithm to create K clusters from the genetic data. This is a VERY important distinction.

It is a completely unimportant distinction. I am pretty sure that you are again going to try to cross the boundary from science into your own personal opinion of how many races there ought to be, fail to justify why that number is correct, and hope that I don't notice that you just spouted a bunch of 101 cluster analysis stuff that you found just now on Google, all so that it would seem more legitimate when the science suddenly vanishes out window like a stale fart.

Why? Because if racial groups were pseudoscience, then we would NOT expect the algorithm to return K clusters that align almost perfectly with our preconceived ideas about racial groups!!

Lol. Thanks. Really, I'm not psychic, I just know you already. I like you! Always have. What are our preconceived ideas about racial groups? You keep talking about these preconceived ideas over and over again. Preconceived ideas. Preconceived ideas. We have preconceived ideas. What ideas?? I asked you in my last post and you ignored the question. WHAT ARE YOUR PRECONCEIVED IDEAS ABOUT RACE? WHAT ARE OUR PRECONCEIVED IDEAS ABOUT RACE? Your preconceived ideas are not likely to be the same as mine. There are dozens, scores, hundreds of preconceived ideas of how many races there are. Sure, we tend to make small lists, but we are humans. We make small lists of everything. Small lists of gods, small lists of types of foods, small lists of animals, small lists of races.

But I know the answer already. By 'preconceived ideas,' you mean, quite specifically, the ideas of racialist thinkers of the 19th and 20th centuries, and their intellectual descendents--or, rather, you THINK you mean that. You don't know what they actually said. And hoo boy, buddy, I'll tell you what--you know I'm strong on genetics and cluster analysis. I know you are smart enough to recognize that no matter how much you pretend to call me uninformed. But I'm equally informed on racialist thought in the 19th and 20th centuries. That's where a lot of the anthropology comes in.

What preconceived ideas? the preconceived ideas of Thomas Huxley, of E.B. Tylor, of Blumenbach or Linnaeus or Meiners? Let's talk about their preconceived ideas about race. Let's name some races. Anglo-Saxon (dark & white variety), Teuton, Laplander, Fin, Sarmatian/Slav, Hindu, Celtic, Nord, Assyrian, Chaldean, Mede, Scythian, Parthain, Philistine, Phoenician, Jew (Jesus is white), Georgian, Circassian, Mingrelian, Armenian, Turk, Persian, Arabian, Afghan, Egyptian, Abyssinian, Guanche. Whew!! We have barely even covered any geography, and we have a score or more races!!

British physiologist William Lawrence, one of the most important of the racialist thinkers, wrote: "The Caucasian variety encompasses numerous races." Is this the preconceived idea of race you had in mind? I have a feeling that you disagree with Lawrence. Will you classify Caucasian as a race? No? European, then? Preconceived ideas, indeed! I think Lawrence is on to something.

The list goes on. There has NEVER been cohesion about 'preconceived racial ideas.' There is a snapshot in time, right now, where you believe there is some kind of unity of thought on this subject. There is not, and what scant unity you might try to point to unravels completely just 100 years back. Nevermind 200. In fact, for most of Western history, 'race' was primarily wielded as a proxy for distinct kingdoms, a form of crude propaganda which tries to invoke phenotypic differences to drum up nationalistic fervor amongst a populace that was usually closely related to the enemy. This is exactly what your flair means. Your enemy is the Jews. Jesus was white. Jesus was a Jew. Your enemy is your fellow whites, just the ones who have more money and won't share it with you.

[–]milkmender11 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (10 children)

I mean, the clusters ALWAYS correspond to something. Always. If we have one cluster for every single individual in the study, those clusters will correspond perfectly to the number of individuals in the dataset. It will be a 1:1 correspondence. Does that mean there are about 8 billion+ races? Yes. It does. It is the same method that you used to get 3, or 7, or 12, or however many you wanted. There are as many races as you want to see. All an algorithim can do is put a robot-buddy next to you who obsequiously repeats what you programmed him to say. The reality of genetics is in the real genes themselves, genes that modify us. You are trying so hard to turn that reality into some kind of scientific argument for a given k value, and you have failed to do so.

I did not cede any ground. I hypothetically assumed your position for a moment to demonstrate a damning inconsistency inherent within it. Come on, man. I know I was a bit snarky in my previous message, but don't play this game. It's as if I said, "Even if I were to assume your position is true, then there would be this problem of--" "HA!! You just assumed my position is TRUE, I ,got you, you snake in the grass! You admitted it!" You're clearly smart enough to know the game you are playing there, and so you are smart enough to know you won't get away with it.

I never claimed that racial clusters aren't useful enough. Again, you are responding to an argument you have heard in the past, one you feel ready to reply to, but not the one I made. I said, quite specifically, that the utility of clusters depends on the question we ask. This is always the way clusters work. They are, by their nature, supportive classification schemes. They don't exist in nature, we use them as tools to answer scientific questions. Change the question, change the clusters. They could be immensely useful, or not useful at all. How many loci? Depends on the question. How useful? Depends on the question. If your question is, "Why is it possible to choose a k value that corresponds to one of the many available socially popular racial classification schemes?" Now there is a question we could talk about. But it is a specific question. The answer is not 'because race exists.' We would need to talk about why humans evolved to classify each other along ethnic boundaries, how we prioritize our distinctions, what selection pressures might have contributed. Lawrence Hirschfeld is currently the leading expert in this field.

Think about it. Let's pretend you are right (remember, this is a Socratic exercise). Why would humans have evolved to correctly determine the 'correct' racial boundaries? We don't evolve to see scientific truths, we evolve to perpetuate our genes. It ought to be assumed that we are very selective in our racial assignments, that we would care overwhelmingly about clearly expressed features like skin, eyes, hair, and not so much about hidden features that are often much more consequential, like circulatory systems. And this is exactly what Hirschfeld's work demonstrates. Indeed, we humans do have a naive race-assignment module. That is the true home of race, the closest place where race is real science. But that is a real feature of evolved human cognition, not a real feature of human populations. Scientifically, race is in the eye of the beholder. If you want to talk about human populations genetics in a way where it becomes compatible with what we observe in the data, without needless references to what racial categories might be popular in one place or another (it changes from place to place, time to time) then the word 'ancestry' is a good place to go, since researchers have already done pioneering work in that direction.

Genome wide clustering does not separate races at all. It, again, produces the number of races you input into the analysis. In fact, it does a much poorer job than the SNP analyses, because there are far fewer differences to analyze. Of course there will be groups in the data. I'm not saying you won't see obvious clusters. You see obvious clusters in one family. You see them in one individual. There is a reason you keep bringing up the social classifications of race, even though I am staying glued to the science. It's because you know that you need to leave science to come up with a way to justify your k value. You need to find a way to legitimize your preferred race number, and you can't do it with science, so you try to backwards-rationalize into it with popilar opinion, and pretend that there is some grand secret truth here about a magic number that we have intuited, and science somehow justifies. But you haven't even told me how many races you think there are, you just keep saying that society has some number that corresponds to the clusters. What number? I have heard so many. Is it 3? 5? 7? 12? All of these k values have appeared in the literature. They ALL correspond to one view or another of how many races there are. I don't know which number you like, but you seem to believe we all already agree on this. Do you think that most humans today agree about how many races there are? What about 100 years ago? 100 years from now? That is hardly a scientific variable.

My friend, about my 'garbage paragraph.' Oh, my friend. My dear friend, Dragonerne. Please direct your attention to your flair. "Jesus is white." A Jew, is white, apparently, and you feel the need to append that information to every single post you make, right at the top. Yeah, what I said is painfully relevant. In fact, it cuts through this debate and strikes at something personal about your own motivations. Honestly, Dragon, thank you for this. It is a rare day when someone so spectacularly makes my point for me like this. My apologizes for the snark--this one is going right in the scrapbook.

You failed to demonstrate my 'misunderstanding' of the clustering algorithims. Actually, you didn't even know what STRUCTURE was, which is what you didn't know you were citing. You told me that you use Python, as if I had said YOU were running analyses through STRUCTURE. I was talking about your first link. I wouldn't know what textbook you are looking at, because we mostly stop using them in grad school, certainly by our first postdoc. Textbooks are such a vague thing to cite, and become outdated quickly. In academica proper we cite published papers, sometimes edited volumes. If you have a specific paper to cite, please do. I try to avoid doing so myself because it comes across as trying to bully someone into silence by giving them homework. But without meaning to, you are showing your hand by mentioning textbooks at all.

I know you aren't dumb. I already kind of apologized for being snarky, but I will actually apologize here. It's just that I already know you, I have met you and your arguments 100 times, and I can't help but feel as if we are already pals engaged in friendly and lightly abusive sparring. Truth be told, I learn more from altrighters than I have from many professers, who would never acknowledge something as straightforward as the warrior gene. I know you aren't dumb. You're wrong, and you're clearly not formally trained in this, but you are well-spoken and you've retained complex information well.

[–]SamiAlHayyidGrand Mufti Imam Sheikh Professor Al Hadji Dr. Sami al-Hayyid 4 insightful - 1 fun4 insightful - 0 fun5 insightful - 1 fun -  (8 children)

Can two black parents create an Asian kid?

Can two Asian parents create a White kid?

Can two White parents create a black kid?

What we mean by race is simply the fact that all of these questions can only be correctly answered with a resounding "No". Those who believe in race rightly don't care about any of this other stuff (continuum fallacy, '99.X% similarity', etc.) simply because no amount of scientific meandering is even remotely going to turn that resounding "No" into a "Yes" or even a "Maybe".

Your style of argument could just as easily be used to attack dog breeds. Sure, dogs probably are overwhelmingly genetically identical. So what?

Can two Great Danes beget a chihuahua?

Is a chihuahua as equally capable of being a police dog as a Belgian Malinois?

The answers to these questions are evidence enough of the existence of dog breeds for most people. Yet strangely when we substitute 'Great Dane' for one race and 'chihuahua' for another in the first question, suddenly the egalitarians amusingly try to backpedal and declare such arguments unsound.

It's hilarious how Western 'science' is so transparently hellbent on trying to provide quasi-scientific explanations for Left-liberal ideological views. The same people who argue this nonsense are incidentally most of the same people who believe that the male-female distinction is also 'fake', and who simultaneously use the 'born this way' argument and the 'sexuality can change over the course of one's life' argument. Hmm... we see a pattern here. Those who want racial distinctions abolished also want these other distinctions abolished. The 'science' in all three cases is subordinate to purely ideological and quasi-moral reasoning. The presupposed assumptions and the reached conclusions are numerically identical.

Until two black parents can create an Asian kid (i.e. never), there will always be a need for racial classifications among humans. End of. Keep denying race all you like—it's transparently obvious that the underlying reasons for doing so are based in ideology. Eastern European and East Asian geneticists, who overwhelmingly accept race, will bury Western science.

[–]DragonerneJesus is white 3 insightful - 1 fun3 insightful - 0 fun4 insightful - 1 fun -  (0 children)

I mean, the clusters ALWAYS correspond to something. Always. If we have one cluster for every single individual in the study, those clusters will correspond perfectly to the number of individuals in the dataset. It will be a 1:1 correspondence. Does that mean there are about 8 billion+ races? Yes. It does.

Yes, 8 billion+ races. " I mean, the clusters ALWAYS correspond to something."

You never adress the elephant in the room, that when we set the k to a low number we don't just get clusters that correspond to "something", but we get clusters that just HAPPENS out of pure luck, who would have even thought this to be the case: racial clusters

You're clearly smart enough to know the game you are playing there, and so you are smart enough to know you won't get away with it.

Ok, I will admit that I was doing that, and I should've clarified because I knew it might've come off as disingenous. Under the assumption that my position was true, you conceded that race was real and then you moved the goal post to say that race as a concept isn't meaningful (without ever proven that, you just claimed it to be the case)
"I should point out that I am providing you the courtesy of pretending that 'race' is a legitimate taxonomic category"
But then you didn't attack my claim that there is more than 1 human race. You moved the goal post to say that the k racial clusters aren't meaningful.
Forgive me?

If your question is, "Why is it possible to choose a k value that corresponds to one of the many available socially popular racial classification schemes?" Now there is a question we could talk about. But it is a specific question. The answer is not 'because race exists.' We would need to talk about why humans evolved to classify each other along ethnic boundaries, how we prioritize our distinctions, what selection pressures might have contributed. Lawrence Hirschfeld is currently the leading expert in this field.

I can't explain how much I admire this level of subversion. It is simply blows my mind every single time.

I would like you to answer that question though.

"We know that race is not real, so how come when we cluster human genetics, we get racial clusters? Well, since we know race is not real, the explanation must be something else. "

And this is exactly what Hirschfeld's work demonstrates. Indeed, we humans do have a naive race-assignment module. That is the true home of race, the closest place where race is real science. But that is a real feature of evolved human cognition, not a real feature of human populations. Scientifically, race is in the eye of the beholder.

I don't know that this is true. Self-identified race align 98-99% with estimated race. The outliers are just racial boundaries, biracials and so on.

There is a reason you keep bringing up the social classifications of race, even though I am staying glued to the science. It's because you know that you need to leave science to come up with a way to justify your k value. You need to find a way to legitimize your preferred race number, and you can't do it with science

No, as I've said before, race realists don't believe in a FIXED set of races. We don't mind an arbitrary k, in fact we would assume an arbitrary k.

"Jesus is white." A Jew, is white, apparently, and you feel the need to append that information to every single post you make, right at the top.

Its my flair. I don't want to go into a religious/political debate. I've seen a post of yours (yes, I stalked you a bit before deciding to engage you in a debate hehe) and it said that jews are the most pure whites. After we have finished this debate about race. I would like to delve into that subject if it interests you. However it will divert the attention too much away from the current subject thats already huge if we started on it now.

But without meaning to, you are showing your hand by mentioning textbooks at all.

You had a misunderstanding of kmeans algos that even 1st year students don't have because its in chapter1 of most textbooks on this subject. To my recollection 1st year undergraduates do use textbooks.

I know you aren't dumb. I already kind of apologized for being snarky, but I will actually apologize here. It's just that I already know you, I have met you and your arguments 100 times, and I can't help but feel as if we are already pals engaged in friendly and lightly abusive sparring. Truth be told, I learn more from altrighters than I have from many professers, who would never acknowledge something as straightforward as the warrior gene. I know you aren't dumb. You're wrong, and you're clearly not formally trained in this, but you are well-spoken and you've retained complex information well.

Its all good. I will reciprocate your mannerism and conduct. You're not wrong, but you've been misled, have some misguided misconceptions due to a lack of understanding of the fundamentals of the methods that you're using but these can be fixed and once thats done, then you can return the favor and school me, where my understanding reveals to be lacking.

[–]Fitter_HappierWhite Nationalist 4 insightful - 1 fun4 insightful - 0 fun5 insightful - 1 fun -  (2 children)

Clutch your pearls if you must.

Go read this guy's last 10 posts, they're all the same thing; "Jews are responsible for all the good in the world and none of the bad". Next thing he'll be saying they're God's chosen people.

[–]shilldetector 5 insightful - 1 fun5 insightful - 0 fun6 insightful - 1 fun -  (1 child)

He's so far claimed that Jews built Britain, Germany, South Africa, and the US. He's your typical Jewish supremacist. We can laugh at it, but it really is the default view of many Jews, especially Israelis. It might seem like he's an alt right troll trying to make Jews look stupid, but I once wasted a lot of time trying to debate them on reddit and his views are very much part of the Jewish mainstream. They just aren't typically openly displayed to goys. Even amongst themselves they usually aren't discussed so blatantly, outside of maybe Israel.

This is likely the only alt he uses that is remotely honest. I'd be willing to bet he has other alts on several platforms, most of which are dedicated to getting them shut down or otherwise subverting them in some way. You'd be amazed how many Jews do this. They have a spectacularly large and well organized army of shills and trolls. Its extremely rare to see one of them go off script, like this dude, who seems to be doing the equivalent of an end zone dance because his coethnics now pretty much own the internet. They usually keep the mask on at all times.

[–]Fitter_HappierWhite Nationalist 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (0 children)

default view of many Jews

yup

[–]literalotherkinNorm MacDonald Nationalism 4 insightful - 1 fun4 insightful - 0 fun5 insightful - 1 fun -  (0 children)

What do you expect this guy literally just posts his Jewish version of 'We Wuz Kangz' over and over again. He's just the Jewish equivalent of those Afrocentric 'scholars' who are always claiming Beethoven was Black, Negroes taught those Greek homosexuals in caves philosophy and Blacks had flying pyramids in Egypt.

[–][deleted] 3 insightful - 2 fun3 insightful - 1 fun4 insightful - 2 fun -  (0 children)

Being able to call someone a retard on the internet is freeing. You should genuinely try it.