Human Biological and Psychological diversity

An important new academic paper was recently published.

Many evolutionary psychologists have asserted that there is a panhuman nature, a species typical psychological structure that is invariant across human populations. Although many social scientists dispute the basic assumptions of evolutionary psychology, they seem widely to agree with this hypothesis. Psychological differences among human populations (demes, ethnic groups, races) are almost always attributed to cultural and sociological forces in the relevant literatures. However, there are strong reasons to suspect that the hypothesis of a panhuman nature is incorrect. Humans migrated out of Africa at least 50,000 years ago and occupied many different ecological and climatological niches. Because of this, they evolved slightly different anatomical and physiological traits. For example, Tibetans evolved various traits that help them cope with the rigors of altitude; similarly, the Inuit evolved various traits that help them cope with the challenges of a very cold environment. It is likely that humans also evolved slightly different psychological traits as a response to different selection pressures in different environments and niches. One possible example is the high intelligence of the Ashkenazi Jewish people. Frank discussions of such differences among human groups have provoked strong ethical concerns in the past. We understand those ethical concerns and believe that it is important to address them. However, we also believe that the benefits of discussing possible human population differences outweigh the costs.

Notable quotes include:

Mainstream textbooks, for example, document many instances of human biological diversity. Despite this, the basics of human biological diversity are not integrated into the social sciences.

Evidence from a variety of disciplines, including genetics, anthropology, archaeology, and paleontology, indicates that human populations evolved distinctive features after spreading from Africa and settling in different ecological and climatic niches (Bellwood 2013; Cavalli-Sforza et al. 1994; Molnar 2006; Wade 2014). Although such human biological variation is often ignored by social scientists, it is not really a matter of dispute among researchers in the relevant disciplines.

In a meta-analysis of racial and ethnic differences in self-esteem, Twenge and Crocker (2002) found a pattern of self-esteem differences (Blacks scored higher than Whites after the 1980s and Asians scored lower than both), but ruled out, a priori, the possibility that such differences were related to biology because, according to them, “racial and ethnic categorizations are socially constructed” and are not based on “shared biological characteristics” (p. 371). This means that an entirely legitimate and plausible hypothesis about the etiology of self-esteem differences was ignored, leaving only social or cultural hypotheses. It is, of course, possible that the differences are entirely environmental in origin, but it is not certain, and ruling legitimate hypotheses out a priori on flimsy arguments (see “Race and Human Populations” section) about the nonreality of human biological diversity potentially prevents researchers from fully understanding the causes of differences in self-esteem.

In a paper on racial and ethnic differences in violent crime rates, Sampson et al. (2005) asserted that biological differences among human populations do not hold “distinct scientific credibility as causes of violence,” and proceeded to adjudicate between three environment-only hypotheses about the causes of disparities in violence (p. 224). So, again, these researchers ruled out a priori a perfectly legitimate and plausible hypothesis and proceeded to approach the data with a self-imposed theoretical limitation.

I wonder why this academic blindness is so common? I also wonder why there are so few researchers willing to challenge the egalitarian orthodoxy despite plenty of empirical evidence to the contrary:

Rushton (1995), for example, forwarded an expansive account of population differences based on life-history theory. However, he was viciously attacked by many scholars (e.g., Barash 1995), and his work was quickly marginalized.

There are plenty of examples in the animal kingdom of both behavioral and physical evolution of species in what most biologists would consider a relatively short time. 20 generations or so seems to be enough time for noticeable adaptations to occur, which is approximately 400 years in humans.

Thus far, we have introduced what we called the SEPP, and noted that we were going to recalibrate two of its basic premises. The first premise was gradualism, which contends that evolution by natural selection is a very slow phenomenon and that human populations have not had enough time to evolve meaningful differences. We argued that this position requires adjustment because (1) natural selection can differentially sculpt traits quite rapidly, as documented by many researchers (see “Background” section), and (2) there is copious evidence that human populations differ from each other somewhat physiologically and that natural selection continues to affect human populations (Hawks et al. 2007; Zuk 2013). Adjusting gradualism in this manner requires that we reconsider the idea of a panhuman nature. It would be remarkable, as we will discuss below, if human populations were completely similar psychologically despite having endured different selective regimes in different environments.

There are notable adaptations in humans which likely evolved during geologically short periods of time, such as cold adaptations in high latitudes or low oxygen adaptations at high altitudes. Other examples include darker skin in mid latitudes to protect from ultraviolet radiation or conversely light skin in high latitudes to enhance vitamin D production, or lactose digestion in adults in communities which domesticate milk producing animals.

The article also goes over some of the common, and false, arguments against race being a biological construct including lewontin’s fallacy, which I have previously covered myself.

A final argument often forwarded against the use of racial classifications is that the genetic variation between human populations is small and dwarfed by the genetic variation within populations (Lewontin 1972; Templeton 2013). Therefore, so this argument goes, racial classifications contain almost no meaningful biological information. There are two counterarguments to this. First, if one focuses on the correlational structure among multiple genetic loci instead of serially examining single loci or averaging over multiple loci, then there are clear and biologically informative differences among human populations (Cochran and Harpending 2009; Edwards 2003; Tang et al. 2005). In other words, different human population groups are recognizable by their genetic profiles but only if one examines a pattern of genetic loci. Tang et al. (2005), for example, reported evidence that self-reported ethnicity corresponded very closely with genetic clusters derived from 326 microsatellite markers. Other studies have found similar power to detect accurately people’s ancestry (Guo et al. 2014; Moreno-Estrada et al. 2014). Of course, this would be impossible without sufficient genetic information to distinguish among human populations.

Importantly, it highlights the reality that personality and psychology also has a biological component, and this varies across races:

The human brain is the same as the human body in this regard and is not somehow immune to natural selection. Or, as Nicholas Wade (2014) succinctly noted, “brain genes do not lie in some special category exempt from natural selection. They are as much under evolutionary pressure as any other category of gene” (p. 106). It is almost certain that human populations vary psychologically in interesting, important, and scientifically meaningful ways because they were subject to different selective regimes (Rushton 1985; Wade 2007). To preview one example briefly, natural selection may have slightly dialed up the general intelligence knob on Ashkenazi Jews (i.e., an adjustment on an existing adaptation), who score roughly 110 on standardized intelligence tests (Cochran et al. 2006; Lynn 2011). Whether humans share a universal psychological profile depends upon the question one is trying to answer. If, for example, one wants to know how humans learn to recognize siblings, the concept of a panhuman psychical nature is probably fruitful (Lieberman et al. 2007). If, however, one wants to know why the Ashkenazim prosper in many societies, often despite virulent anti-semitism, then the concept of a universal psychical profile is not only wrong, but it also positively prevents researchers from accurately answering the question (because it leads to a fruitless exploration for sociocultural causes which cannot be the entire story).

Citing specific studies with specific genes, the authors discuss some personality traits which seem to vary over different populations, quite likely due to the genetic differences mentioned, including collectivism (east Asians) vs. individualism (NW Europeans) and Ashkanazi Jewish intelligence.

For additional information on the likely evolutionary pressures which led to an increase in pro-civilizational traits in Europeans, I recommend A Farewell to Alms: A Brief Economic History of the World by Gregory Clark. One of these days I am going to get around to doing a full review of this book.

By political necessity, the article is very conservative with its discussion of racial differences. However, it is a useful step in the right direction in gaining a mainstreamed understanding of the reality of race. The article calls out the social “scientists” who categorically rule out biological causes of racial differences as being unscientific. These “scientists” do so for no particular reason other than personal ideological preference. The article further proposes future research more openly and directly pursue possible biological explanations. Despite the obvious qualification that the article doesn’t go far enough in honestly admitting the primacy of biology in racial differences, it is still an important contribution in advancing the our understanding of human nature by addressing the largest problem currently extant in the academic community: Left-wing bias in favor of (false) universal egalitarianism.

We are not naive about the obstacles a Darwinian approach to human biological diversity faces. We hope only to start a candid discussion and to forward some suggestions about how to proceed with this paradigm. Doubtless, some will continue to resist the notion that human populations differ in biologically meaningful ways. But it seems clear to us that biological diversity is the rule across the vast tapestry of life. It is true among plants, among animals, among humans, and among human populations.

Read full article here.

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Race Hustlers on Reddit are spreading misinformation on /r/”science” again

/r/science on reddit is having a race hustler thread where cathedral academics are telling everyone the same tired nonsense that differences in outcomes between groups are caused by SES and discrimination by white men. I decided it would be valuable to post an excerpt from my book which discusses the left wing bias in academia because there is a lot of it and I don’t think these people should get a free pass on spreading misinformation like this. If you have a reddit account, I think it would be a good idea to go in and counter these false claims. There is plenty of evidence that IQ differences have genetic causes, and that thread should be littered with links to it.

Since the probability that my comments will be removed is high, I decided to make a copy of them here [edit: I checked and as expected the comments are already removed. Check out this site which saves all the removed comments. Notice a pattern? Edit2: Apparently this thread was made because high level progressives in science journals or media demanded it in order for the sub to have advance access to new announcements of interesting research. In other words, spread our ideology and we will give you insider access and other perks.]:

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IQ is the single best studied and understood psychological trait. It has been studied for over 100 years and has consistently found that the black/white IQ gap on average is about 15 points. It has also found that the male distribution is significantly more variable than the female curve. What this means is that among the smartest people, those most likely to do well in science, the population is about 2 males for every 1 female. Intelligence level has been shown to be mostly determined by genetics. You can see a large compilation of studies and findings which demonstrate how strongly genetic intelligence and other traits are here. These innate IQ differences explain the differences in outcomes of different populations of humans without needing to resort to unfalsifiable and unscientific concepts like “white privilege” or bias.

I gave you enough links above to start on this. Instead of repeating this easily findable information, I am going to talk about the progressive/far left wing bias that exists in academia. This bias seriously undermines the credibility of race and gender hustlers who try to use credentialism to support untrue opinions about white/male privilege. For an independent opinion, see the website of liberal social psychologist Jonathon Haidt where he and others admit to and discuss the problems caused by this progressive bias.

I wrote a book on gender differences in intelligence called smart and sexy, and it cites hundreds of studies which together confirm and explain why gender differences in outcomes exist and that they are mostly biological in origin. You can find a wealth of data in there for biological mechanisms. However, I also took the time to analyze the current state of academia and what I found was extremely troubling. Below is an excerpt of a section of that book. Remember that the focus of the book is on gender, but this left-wing bias also applies to claims about race.  Citations for all my claims will be at the end.

Saying that the academic community has a large progressive bias is a very strong claim and such an extraordinary claim requires extraordinary evidence. So what is known about the “scientists” who publish “research” in politically charged areas? Diederick Stapel was previously a highly regarded and influential Dutch social psychologist who did a lot of work on stereotype threat until it came to light that he “routinely falsified data and made up entire experiments.” Another example of his politically biased work was a “scientific” article which sanctimoniously claimed to find that meat eaters were more selfish and less agreeable than vegans. Unfortunately, it is impossible to be surprised by outspoken priggishness from vegans and their sympathizers.

Thanks to this media attention, Stapel is now the most notorious charlatan in the field of social psychology, which is saying a lot for what appears to be a regularly fraudulent and pseudo-scientific discipline. Social Psychologists as a group do not make the data they collect available for outside review 2/3rds of the time. This stinginess with data is actually against the ethical rules established by social psychologists themselves and suggests that there are likely many more Stapels out there who simply haven’t been caught. A survey by the Harvard business school found that 70% of social psychologists admitted to cutting corners in reporting data, 30% reporting unexpected findings as if they were expected from the start, and 1% admitted to falsifying data.

Another meta-analysis of papers published in high-tier psychology journals found that 50% of papers surveyed contained at least one statistical error and 15% contained an error so severe that the conclusion drawn would have had to have been reversed.i, ii A meta-analysis which looked at whether or not positive results from stereotype threat studies could be replicated found that almost half could not, and that a further 25% were confounded by methodological issues.iii Methodological issues, especially in determining statistical validity, have even been used by one Social Psychologist to publish in a major, respected journal that he had proven the existence of psychic ability. His finding used standard statistical practices in psychology and resulted in heavy criticism by professional statisticians of both the specific paper and the psychology community generally.iv

This high publicity criticism led to a fair degree of soul searching among the psychological community and led some researchers to undertake the task of evaluating how widespread these problems are. One analysis reviewed articles from the last 100 years in the top 100 journals based on the impact factor; a measure of the level of influence a paper or journal has on the field. It found that in that time, for the highest impact journals, only 1% of all research findings in psychology had ever been replicated. Of that 1%, only 14% were in fact direct replications. The rest tested similar hypotheses under different conditions. However, successful replications themselves have to be received critically. Half of the 1% of replications had authors from the original study; this is troubling because the presence of the previous author greatly impacts the chance of positive replication and implies bias might be playing a role. 92% of replication studies with an author from the original paper confirm the original result, while only 65% of replications by independent researchers confirm the original finding.v

Problematic methodology isn’t the only issue in psychology. Ideological bias is rampant in the humanities generally, but especially in social psychology; both among individual researchers and among the journals publishing papers. Beyond the lack of objective critical evaluation of papers, the field itself is essentially an ideological and political echo-chamber that is considerably more left-wing politically than the general population. 80% of social psychologists identify as liberal, while only 3 out of 1000 identify as conservative. Contrast this with the general population which is 40% conservative and only 20% liberal; the remainder being moderate or apolitical. Looking through all social sciences, the ratio of liberals to conservatives varies from 8:1 to 30:1.vi Were these sorts of numbers occurring with an ideologically designated protected class, these same social psychologists would be the first to use it as incontrovertible proof of discrimination.vii, viii

Considering what is now known about the biological origins of cognition and intelligence (discussed in more detail in future sections), it is generally difficult to take claims of discrimination seriously when underrepresented groups also display relatively lower intelligence profiles. However, in this case there is no reason to think that conservatives as a group have an intellectual profile below the general population. Social conservatives tend to be a little lower in intelligence relative to liberals, but free-market conservatives (libertarians) tend to be smarter than liberals. Being very partisan, either liberal or conservative, tends to be associated with high IQ as well.ix Increased income levels, which are a proxy for IQ, also moves people right ideologically.x In other words, there is nothing that biologically determined intelligence can do to explain the lack of conservatives, and even moderates, in the humanities.xi

In a survey of social psychologists, it was found that conservative respondents feared negative consequences from revealing their political affiliation and that they were right to do so as liberal respondents expressed willingness to discriminate against conservatives in approving papers, grant proposals, and hiring decisions.xii The more liberal a social psychologist is or the more consequential the decision would be for the conservative, the more willing liberal social psychologists are to discriminate.

The temptation . . . to advance a political agenda is too often indulged in sociology, especially by activist faculty in certain fields, like marriage, family, sex, and gender . . . Research programs that advance narrow agendas compatible with particular ideologies are privileged . . . the influence of progressive orthodoxy in sociology is evident in decisions made by graduate students, junior faculty, and even senior faculty about what, why, and how to research, publish, and teach . . . The result is predictable: Play it politically safe, avoid controversial questions, publish the right conclusions…

[Compared to conservative sociologists] Politically-correct sociologists enjoy certain privileges in a very politically conscious and liberal discipline. They can, for example, “paint caricature-like pictures based on the most extreme and irrational beliefs of those who differ from them ideologically without feeling any penalty for doing so,” and “can systematically misinterpret, misrepresent, or ignore research in such a manner as to sustain [their] political views and be confident that such misinterpretations . . . are unlikely to be recognized by [their] colleagues” [Social science researchers believe] “that social science should be an instrument for social change and thus should promote the ‘correct’ values and ideological positions”vi

With this sort of cultural climate, exploring gender differences, or even just acknowledging that such differences exist is extremely difficult for professional scientists to do today. The pattern of ideologically driven academics significantly undermines the ability of an objective outsider to trust the conclusions coming out of certain fields, especially when it is related to such a politically charged subject as gender (and race) differences in test scores. It is quite clear that the overwhelming majority of researchers working on this topic possess a politically desired outcome of these studies. The great potential for this systemic Lysenkoism to motivate the production of inaccurate results and interpretations contrary to reality can’t be overestimated. The objectivity of the field in concluding stereotype threat is a real and large effect phenomenon in particular is highly questionable.

Calling cynical skepticism of the social sciences “anti-intellectual,” a common criticism directed towards conservative thinkers, is only so in the sense that these “scientists” have misdefined the word “intellectual” to describe their political ideology and therefore themselves. It is quite conceivable that the modern attitudes described as “anti-science” attributed to conservatives are fundamentally merely a non-inevitable reaction to what can only be described as pseudo-science being published by leftist activists in academia; and stereotype threat is just one example of peer-reviewed pseudo-science.xi

Certainly in some cases there are conservatives that legitimately hold anti-scientific views, such as in the case of evolution generally. But when it comes to evolution of the human species specifically, many liberals are just as anti-scientific as the most hardcore creationist. The main difference is that the left, being dominant in state institutions and having ample government funding, has the power to enforce idealism contrary to reality while most conservatives do not have symmetric influence. This asymmetry in power makes leftist anti-reality beliefs of far greater concern and consequence than the equivalent conservative anti-reality beliefs.

For the average person, it isn’t so hard to notice some of the more egregious examples of leftist pseudo-science. Since most people do not have the time or energy to independently evaluate every pronouncement from every field coming out of the scientific community, it is more efficient (and natural) to use a quick short-hand, or stereotype, to extrapolate from a more narrow range of data for which they do have time and interest to look into. If their interest happens to be in an area replete with pseudo-science, and that’s likely because politically controversial areas are both the most likely to be interesting and to contain pseudo-science, then they have found themselves an extraordinary indicator of dishonesty which they then extrapolate from.

As a consequence of general distrust, society is more likely to develop unreasonable movements like that against vaccinations. It is not reasonable for the scientific community to expect the average person to evaluate every single scientific finding themselves. They have real lives that do not, and should not, have to deal with academic politics. Therefore, scientists need to do a better job rooting out bias, and especially liberal bias, in their fields so the public can actually trust what they say. If academics want to be trusted, they first must be trustworthy because trust, for institutions as much as individuals, must be earned.

I don’t mean to be misinterpreted when I point out these biases in scientific research. To their credit, the main people who have identified and raised alarm about the bias against non-liberals in academic papers have themselves been liberal social psychologists such as Jonathon Haidt. In fields that are outside of the social sciences or on the periphery, real bravery is often demonstrated in their defiance of orthodoxy. Perhaps my favorite treatment of Cultural Marxism came from a paper which starts by stating “putting aside political correctness” and then continues on to discuss multiple heretical topics and never references it again. Political correctness is mentioned only long enough to dismiss it as the irrational and fallacious sentiment that it is. This is a hopeful sign, but it must be noted that no serious efforts to actively alleviate the problem within the social sciences beyond talking about it have so far been undertaken.

I have a great respect for science generally and see it as the best method so far developed by humans to separate truth from fiction, at least when the core principles of scientific philosophy are actually followed. But the scientific establishment is still a human institution and therefore fallible. The community at times moves unacceptably far away from its core principles and this usually happens when research topics might have strong implications for an over-arching political ideology. The Lysenkoist effect of an overwhelmingly liberal character is just one problem. Another is that senior research scientists often spend as much or more time begging for money than they do actually trying to discover truth. Whether or not they actually get money is often dependent on how much they publish which creates an incentive to publish even if the research isn’t very good. Conforming to the political biases of other researchers thus constitutes a quick way to look better with lower quality research.

From the state of academia, it can be taken that the discrimination hypothesis has a great deal of influence on our current culture and the determination of public policy through the publication of questionable research. If the discrimination hypothesis is only partially true or largely wrong in the present, then social policies based on it are likely to be largely ineffectual and possibly harmful. Intelligence researcher Dr. Wendy Johnson has stated the importance of this possibility with reference to X linked intelligence succinctly,

Values create the emotionally charged climates pervading discussions of sex differences, making it difficult to evaluate scientific data objectively. Values are extremely important and appropriately form the basis of many actions and social contracts. But the laws of nature are not responsible to us or to our values and may not conform to them. It is important to understand the laws of nature as completely as possible within our circumstances in order to actualize our values as we intend. We can only develop coherent and realistic actions and social policies that will actualize our values if we understand the laws of nature as they exist.ii

Wicherts, J. Bakker, M. (2011) The (mis)reporting of statistical results in psychology journals. Behav Res Methods. 43(3): 666–678.

Franklin, K. (2011) Psychology rife with inaccurate research findings. Psychology today. http://www.psychologytoday.com/blog/witness/201111/psychology-rife-inaccurate-research-findings

Stoet, G., Geary, D. (2012) Can stereotype threat explain the gender gap in mathematics performance and achievement? Review of general psychology. Vol 16(1), 93-102

Wagenmakers, E., Wetzels, R., Borsboon, D., Van der Mass, H. (2011) Why psychologists must change the way they analyze their data: the case of psi: Comment on Bem. Journal of Personallity and Social Psychology. Vol 100(3). 426-432.

Makel, M., Plucker, J., Hegarty, B. (2012) Replications in psychology research: How often do they really occur? Perspectives on psychological science.Vol 7(6). 537-542.

Redding. R. (2013) Politicized Science. Society. Vol 50(5), 439-446

Haidt, J., Post-Partisan Social Psychology. http://people.stern.nyu.edu/jhaidt/postpartisan.html

Tierny, J. (2011) Social Scientist Sees Bias Within. New York Times. http://www.nytimes.com/2011/02/08/science/08tier.html?_r=5&ref=science&

Kemmelmeier, M. (2008) Is there a relationship between political orientation and cognitive ability? A test of three hypotheses in two studies. Personality and Individual Differences.Vol 45(8), 767–772

Morton, R., Tyran, J., Wengström, E. (2011) Income and Ideology: How Personality Traits, Cognitive Abilities, and Education Shape Political Attitudes. Univ. of Copenhagen Dept. of Economics Discussion Paper No. 11-08. Available at SSRN: http://ssrn.com/abstract=1768822 or http://dx.doi.org/10.2139/ssrn.1768822

Duarte, J., Crawford, J., Stern, C., Haidt, J., Jussim, L., Tetlock, P. (2014) Political Diversity will Improve Social Psychology. Behav Brain Sci. Vol 18. 1-54

Inbar, Y. & Lammers, J. (2012).  Political diversity in social and personality psychology.  Perspectives on Psychological Science, 7, 496-503.

Abramowitz, S. I., Gomes, B., Abramowitz, C. V. (1975), Publish or Politic: Referee Bias in Manuscript Review. Journal of Applied Social Psychology, 5: 187–200. doi: 10.1111/j.1559-1816.1975.tb00675.x

Ceci, S. J., Peters, D., Plotkin, J. K., Alan E., (1992). Human subjects review, personal values, and the regulation of social science research. Methodological issues & strategies in clinical research., American Psychological Association, 687-704

Crawford, J. T, Jussim, L., Cain, T. R., Cohen, F.  (2013).  Right-wing authoritarianism and social dominance orientation differentially predict biased evaluations of media reports.  Journal of Applied Social Psychology, 43, 163-174.

Munro, G. D., Lasane, T. P. and Leary, S. P. (2010), Political Partisan Prejudice: Selective Distortion and Weighting of Evaluative Categories in College Admissions Applications. Journal of Applied Social Psychology, 40: 2434–2462. doi: 10.1111/j.1559-1816.2010.00665.x

Rothman, S., Lichter, S. R., Nevitte, N. (2005) Politics and Professional Advancement Among College Faculty. The Forum. Vol 3(1). Article 2.

Harvard sex row and science. BBC News. Jan 18, 2005. http://news.bbc.co.uk/2/hi/uk_news/education/4183495.stm

Lallensack, R. (2014) UW to host first feminist biology post-doc program in the nation. The Badger Herald. http://badgerherald.com/news/2014/04/21/madison-host-first-feminist-biology-post-doc-program-nation-rl/#.VO5GIS6GN8H

Pinker, S. (2009  Letter from Steven Pinker to Aarhus University in defence of Prof. Nyborg, December 9, 2009. http://www.helmuthnyborg.dk/Letters-Of-Support/PinkerLetter.pdf

Nyborg, H. (2013) Danish Government Tries to Censor Science it Doesn’t Like. American Renaissance, November 14, 2013 http://www.amren.com/news/2013/11/danish-government-tries-to-censor-science-it-doesnt-like/

Thompsom, J., (2013) Helmuth Nyborg gets Watson’d. Psychological Comments. http://drjamesthompson.blogspot.com/2013/11/helmuth-nyborg-gets-watsond.html

Nyborg, H. (2003) “The Sociology of Psychometric and Bio-behavioral Sciences: A Case Study of Destructive Social Reductionism and Collective Fraud in 20th Century Academia.” The Scientific Study of General Intelligence: Tribute to Arthur R. Jensen.

Nyborg, H., The Greatest Collective Scientific Fraud of the 20th Century: The Demolition of Differential Psychology and Eugenics. The Mankind Quarterly. University of Aarhus (Retired, 2007)

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One of my favorite twitter accounts deleted (On peer review and social “science”)

Recently, one of my favorite twitter accounts was deleted. The name of the account was @realpeerreview and the main focus of this account was to take excerpts from truly retarded social “science” research papers and show how stupidly our tax money is being wasted. You can see an archive of his work here and an archive of the archive in case that goes down. I would read through all those. It is both hilarious and infuriating at the same time. Why does the public have to pay for such stupidity?

Of course, other social “scientists” didn’t like public attention to their “research” and threatened to doxx the individual broadcasting how atrocious most social “science” research actually is. These cockroaches prefer to stay in dark under the rug and don’t like anyone lifting up a corner. @realpeerreview was, I guess, left no choice but to back off because his career was possibly on the line. Some one else quickly snatched up the account name after finding out about this typically leftist hiding of the truth to continue on the good work. I don’t know if she will do as good a job, but I hope she can give them hell.

Anyway, just one more example why academia, at least in the humanities, should not be trusted at all. I have written on stuff like this before on how stereotype threat is bunk and how standardized tests are rigged against boys, however, it was nice to see how widespread the sickness is. It spans hundreds of papers and hundreds of topics. Defunding the humanities would wipe out 100 times more cancerous tumor than healthy tissue. It is time for some emergency surgery.

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Wikipedia in Action on Race

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

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

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

Here is an old archived version of this article.

Here is an archived version of the current article.

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

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

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

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

In the old article this:

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

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

expanded into this:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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