The Coates article is wonderful. He takes a historical look at how race has been deployed over the last 150 years. Along the way, he makes all the good points that can be made with the census, and some others as well. It is a nice reminder that far from being fixed, race is a potently flexible concept which can and has been use to classify (or cluster) humans based on any number of arbitrary factors. That is, he gives the classically anthropological argument that arbitrary classifications are taken up as naturalized in the support of explicitly political designs.

Which brings me around to Khan.

After first giving a brief history of the world as told through the clustering of genes in patterns – a la Cavalli-Sforza – Khan turns to the power of his beloved PCA:

When you take multiple dimensions and transpose the data geometrically you quickly see population structure fall out of the data set.

As if by magic, unsullied by the subjective whims of human judgment, PCA objectively does the work of racial classification. Khan eventually draws the following conclusion about race:

So there you have it. An underlying biological reality which is a reflection of deep history. It may not be real or factual, but it is consistent and coherent. Then there are innate faculties which lead us toward categorization of humans into various kinds, for deeply adaptive purposes. Finally, there are historically contingent events which warp our perception of categories so as to fit into power relations in a straightforward sense.

And here I agree with Khan. What he does is neither real nor factual, but it is consistent and internally coherent. For Khan, race is a biological reality, but historically contingent events conspire to warp our perceptions of this uncomfortable fact.

Steve Hsu, for his part, offers this muddled attempt to use race as a fixed concept without coming off as using race as a fixed concept. Needless to say, it doesn’t add up:

Now plot the genome of each human as a point on our lattice. Not surprisingly, there are readily identifiable clusters of points, corresponding to traditional continental ethnic groups: Europeans, Africans, Asians, Native Americans, etc. (See, for example, Risch et al., Am. J. Hum. Genet. 76:268–275, 2005.) Of course, we can get into endless arguments about how we define European or Asian, and of course there is substructure within the clusters, but it is rather obvious that there are identifiable groupings, and as the Risch study shows, they correspond very well to self-identified notions of race. ….

This leads us to two very different possibilities in human genetic variation:

Hypothesis 1: (the PC mantra) The only group differences that exist between the clusters (races) are innocuous and superficial, for example related to skin color, hair color, body type, etc.
Hypothesis 2: (the dangerous one) Group differences exist which might affect important (let us say, deep rather than superficial) and measurable characteristics, such as cognitive abilities, personality, athletic prowess, etc. …

The predominant view among social scientists is that H1 is obviously correct and H2 obviously false. However, this is mainly wishful thinking. Official statements by the American Sociological Association and the American Anthropological Association even endorse the view that race is not a valid biological concept, which is clearly incorrect.

As scientists, we don’t know whether H1 or H2 is correct, but given the revolution in biotechnology, we will eventually. Let me reiterate, before someone labels me a racist: we don’t know with high confidence whether H1 or H2 is correct.

Finally, it is important to note that group differences are statistical in nature and do not imply anything definitive about a particular individual. Rather than rely on the scientifically unsupported claim that we are all equal, it would be better to emphasize that we all have inalienable human rights regardless of our abilities or genetic makeup.

Hsu’s logic is wrong on several counts here. But, I will discuss the two points which are particularly glaring.

The first is simply the conflation of clustering imposed by PCA (which I will get to later) with the reified category race. He constantly confuses this issue. This is particularly evident when he chides the AAA for noting that race is not a valid biological concept and then points to evidence from PCA as evidence that race is a biological reality.

Second, his attempt to assert legal equality is belied by his other attempts to police access to public institutions based on IQ scores. Hsu’s conceptions of inalienable rights would appear to be taken directly from Plato’s Republic.   

Hsu is also wrong in implying that work on race within anthropology has been stagnate. In a recent (2009) paper titled “How Race Becomes Biology: Embodiment of Social Inequality,” Gravlee puts forth a powerful and subtle account of how social inequalities become reified under the rubric race.

Of interest in the recent back and forth on this blog is Gravlee’s argument about the abuse of PCA in genetics:

Yet some researchers still defend race as a useful
framework for describing human genetic variation—and
for identifying genetic influences on racial differences in
disease (Risch et al., 2002; Gonzalez Burchard et al.,
2003; Bamshad et al., 2004). The defense of race relies
on two related lines of evidence: 1) studies of worldwide
genetic variation show that individuals from the same
continent reliably cluster together (Rosenberg et al.,
2002; Bamshad et al., 2003; Shriver et al., 2004;
Rosenberg et al., 2005), and 2) in the United States,
‘‘self-identified race/ethnicity’’ is a useful proxy for
genetic differentiation between groups that vary in conti-
nental ancestry (Tang et al., 2005)…..

First, the claim that recent genetic studies ‘‘have recapitulated the classical definition of races’’(Risch et al., 2002, p 3) misrepresents the purpose of cluster analysis, which is to detect pattern in a given dataset, not determine the essential number of subdivisions in our species. An example of this error is the common interpretation of Rosenberg et al. (2002) as evidence that humans are divided into five genetic clusters (e.g., Bamshad et al., 2004; Mountain and Risch, 2004; Leroi, 2005; Tang et al., 2005). Evidence that humans can be divided into five clusters does not mean they are naturally divided, as the classical definition of race would suggest. In fact, the number of clusters necessary to describe global genetic variation has been inconsistent; some studies report five (Rosenberg et al., 2002) and others seven (Corander et al., 2004; Li et al., 2008). Even when the number of clusters is consistent, their boundaries and composition are not [compare Corander et al., (2004) and Li et al., (2008)], and finer substructures are obscured.

Gravlee goes on to offer three further points of rebuttal, all equally powerful. But, Gravlee’s argument about clustering points us towards another classic anthropological point; drawing boundaries, whether through language or mathematics, is political work. Further, what Gravlee argues about PCA holds true of all statistical techniques.

A cursory glance at the historic malleability of racial categories from any census, or a look at Ta-Nehisi Coates article will demonstrate this point. Race is undeniably a social category that carries real consequences for those caught on the wrong side of the classificatory scheme. How one chooses to classify is a political act and no amount of technical mediation can change that.

Gravlee, Clarence C. 2009 How Race Becomes Biology: Embodiment of Social Inequality. American Journal of Physical Anthropology 139(1): 47–57.

Here is a recent article about test scores from the New York Times, “No Rich Child Left Behind.”  They got through the entire article without connecting cognitive abilities to inherited intelligence.  Instead, the connection is made to wealth, poverty, and early childhood development.  Do middle/upper class things for a child at night (“Goodnight Moon time”), and they are going to fit into the academic world created by the upper and middle classes in the schools.  Goodnight Moon time in turn is highly correlated with poverty.

Note too that widening gaps between test scores for the upper 10% and the lowest 10% in terms of income have widened over the last 50 years. This in large part is because economic inequality has increased, and could not plausibly have to do with shifts in the gene pool of the last two generations (i.e. 50 years).

I am of course a Social Scientist, and much more in tune with what Michael Scroggins and Max Holland write.  They are squarely in the traditions of the social sciences regarding the nature of culture, definitions, and interpretations of data.  They are also well-read in the natural sciences, and trying to tie the two fields together, a difficult task.  As several of Michael’s earlier posts point out, his dissertation work brings him into close contacts with biologists in DIY bio labs.  He does this on the general assumption (as I understand it) that biologists have culture too, and that the techniques and approaches Boas used to study Native Americans, and Malinowski used to study Trobriand Islanders in the early 20^th century are relevant to studying scientists in 21^st century California.  Max has written an engaging thesis (and book) about similar issues which I have so far only skimmed.  It is worth a closer look, as you can see from his blog from earlier this week.

Much of the discussion at Ethnograpy.com over the last few months frankly exhausts me.  It points out how little other people have read in my social sciences as they point to the psychometric, population, and other studies which they regard as more important than Boas, Malinowski, and their successors.  But it also points out how much I have to read in their fields.  Most important it points to different criteria for validity used between different disciplines.  Frankly, I don’t get what is so great about physics and mathematics.  Both sound like great disciplines, but why are SAT scores on the math portion of the SAT “better” than those on the English portion? How could anyone think that Physics is harder than Philosophy? Have they ever tried to read Hegel?

I guess the sum of this rumination is to say that while I continue to disagree with dad, Dailliard, Razib Khan, Randall Parker and others who posted here, I also appreciate their comments which both help me examine my own positions, and point me to the many many things that I have not read.  Inter-disciplinary work is difficult—more difficult I think than staying comfortably within our own disciplines where we can go to seminars of the converted, and perform the self-congratulatory rituals needed to preserve the status quo.  This is why I appreciate it that they take the time to write thoughtful comments.

And “dad” for what it is worth, I still don’t think it makes much difference whether the sperm donor for my putative child is a nuclear physicist or the ticket taker at the movie theater.  Still, you rhetorical question helped me frame my thoughts more precisely—it was a good question!

PS.  What do you think of the Dennett quote that Max posted?  “There is no such thing as philosophy-free science; there is only science whose philosophical baggage is taken on board without examination” (Dennett 1995)?

But Campbell noticed something else to, the emergence of “corruption pressures,” based on the general principle that is now known as “Campbell’s Law.”

The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.

      In different ways, both Michael Scroggins and Max Holland have pointed at this basic problem in their recent blogs critiquing intelligence tests ranging from the standard tests, to the SAT and college entrance exams.  Such intelligence tests are indeed used to divide up the spoils of placement spots at elite schools, and not surprisingly, ambitious parents seek to corrupt it by means both fair or not. But for use in general analysis like that done by the evolutionary psychologists, the consequences are that their data source over time is corrupted.  The cheating scandals associated the No Child Left Behind Act are a byproduct of Campbell’s Law.  So is the fact that the SAT exam was recently cancelled in South Korea due to widespread cheating.  However most of the corruption does not come from cheating.  It also comes from the fact that such standardized tests are routinely gamed by testing companies which guarantee 100 extra points on the SAT through $1000 prep courses (I used one of these classes for my daughter—it worked!).

For what it is worth, tests like the internationally administered National Association of Educational Progress (NAEP) which do not have consequences attached to them are much less likely to be gamed.  They do not have consequences for funding, admissions, etc., attached to them because they sample across broad areas, and report results on large geographical areas rather than individuals.

Which brings up the BGI Cognitive Genetics Gene Trait Association Study of Intelligence that Michael Scroggins wrote about, and which Dr. Steve Hsu is promoting as a member of the Core Team of BGI.  The Chinese company is seeking people with “high cognitive abilities,” as defined by high scores on the SAT and other standardized tests, or PhDs in a limited number of fields (e.g. physics, computer science, electrical engineering) from “top” US universities.

The implicit assumption is that these people must have DNA which makes them higher functioning than the rest of us.  There are a number of flaws with this approach, starting with those pointed to by Donald Campbell—particularly the fact that the measures they are using long ago lost the validity and reliability due to corruption pressures.  There is also the problem that Michael, Max, and I have been hammering home here at Ethnography.com, which is that “intelligence” is always culturally defined, typically by those who have the power to define people like themselves as, well, “intelligent.”  (Perhaps this is why BGI does not want people with PhD degrees in fields they have not studied, or from universities outside the US–this is who they are).

There are of course other reasons why BGI are off on a fool’s errand, some of which is described in Chapter 5 of my recent (2012) book Schooling, Childhood, and Bureaucracy: Bureaucratizing the Child.  Chapter 5 is called “The Sorting Function of Schools: Institutionalized Privilege and Why Harvard is a Social Problem for Both the Middle Class and Public School 65 in the Bronx.”  For that matter Chapter 8 “Seeing Like a State: Efficiency, Calculability, Predictivity, Control Testing Regimes, and School Administration” is also relevant.  (Sorry the book is still only out in hardcover at $90, and Kindle for $72—check your library for a copy, or wait for the paperback version).  To summarize the findings in my book:  Success on tests are inevitably associated with reproducing the status quo, whatever status quo the elites of the day might be promoting.

As for Campbell’s Law, I hope that the people organizing such projects as the Gene Trait Association Study of Intelligence read Donald Campbell’s article carefully, even if he is not an electrical engineer or physicist with a PhD from a top US University, or an 800 on the math portion of the SAT.