violentmetaphors | To begin with, Wade can’t provide a clear definition of “race.” He
tries to rely instead on loose associations rather than definitive
characteristics, which forces him to conclude both that physical traits
define race but that the traits can vary from person to person: “races
are identified by clusters of traits, and to belong to a certain race,
it’s not necessary to possess all of the identifying traits” (p. 121).
With such a shifty, casual footing, it’s no surprise that Wade’s
conclusions are unsound. He can’t keep the number of races straight:
Wade can’t settle on a definite number of races because he can’t come
up with a consistent, rigorous definition of what “race” means. He uses
terms like “major race”, “race”, “subrace”, “group”, or “population,”
but doesn’t provide any serious, objective ways to distinguish between
these terms for arbitrary groupings of people arbitrary groups.
Rather than just announcing his subjective opinions about race, Wade
wants to ground them in science. He tries to use genetics: “Such an
arrangement, of portioning human variation into five continental races,
is to some extent arbitrary. But it makes practical sense. The three
major races are easy to recognize. The five-way division matches the
known events of human population history. And, most significant of all,
the division by continent is supported by genetics.” (p. 94)
To support his claim, Wade relies heavily on a 2002 paper (by Rosenberg et al.) that used a program called structure
to group people based on similarities in markers distributed across the
genome. He notes that the program identified five major clusters in
this 2002 study, which corresponded to the major geographic regions
(Africa, Eurasia, East Asia, Oceania, and America) of the world.
Therefore, Wade argues, these results clearly show that humans are
divided up into racial categories that match continents.
Charles Murray, author of The Bell Curve, who recently reviewed Wade’s book in the Wall Street Journal, agrees:
A computer given a random sampling of bits of DNA
that are known to vary among humans—from among the millions of them—will
cluster them into groups that correspond to the self-identified race or
ethnicity of the subjects. This is not because the software assigns the
computer that objective but because those are the clusters that provide
the best statistical fit.
But Wade and Murray are both wrong. Structure didn’t simply identify five
clusters. It also identified two, three, four, six, and seven clusters.
(Rosenberg et al. 2002 actually identified up to 20 divisions, but 1-7
are the primary ones they discussed. They also divided their worldwide
sample up into regions, and then ran structure within those regions, to look at more fine-scale population structure.)
Why? Researchers using structure have to define the number (K) of clusters in advance, because that’s what the program requires. The program was designed to partition individuals into whatever pre-specified
number of clusters the researcher requests, regardless of whether that
number of divisions really exists in nature. In other words, if the
researcher tells structure to divide the sampled individuals into 4 clusters, structure will identify 4 groups no matter what–even if there is really only 1 group, or even if there are really 14 groups.
So, when Rosenberg et al. (2002) told structure to use K=6?
They got six clusters, with the sixth corresponding to a northwestern
Pakistani group, the Kalash. Does this make the Kalash a separate race?
Wade doesn’t think so. When they told structure to use K=3?
They got three clusters back, corresponding to Africa, Europe/Middle
East/South Asia, and East Asia/Oceania/Americas. So are Native Americans
and Australians not separate races? Rosenberg et al. never published
any statistical evidence that justifies picking 5 races instead of 7, or
4, or 2 (although such methods do exist–see Bolnick et al. 2008). Wade
seems to like K=5 simply because it matches his pre-conceived notions of
what race should be:
“It might be reasonable to elevate the Indian and Middle
Eastern groups to the level of major races, making seven in all. But
then many more subpopulations could be declared races, so to keep things
simple, the five-race, continent-based scheme seems the most practical
for most purposes.” (p. 100)
Practical. Simple. Wade wants us to cut up human diversity into five
races not because that’s what the statistical analyses show, but because
thinking about it as a gradient is hard.
Wade isn’t even using the tools of genetics competently. The authors of
the paper he relied on, as well as subsequent studies, showed that
different runs of the program with the same data can even produce
different results (Bolnick, 2008). Structure’s results are
extremely sensitive to many different factors, including models, the
type and number of genetic variants studied, and the number of
populations included in the analysis (Rosenberg et al. 2005). When
Rosenberg et al. (2005) expanded the 2002 dataset to include more
genetic markers for the same population samples, they identified a
somewhat different set of genetic clusters when K=6 (Native Americans
were divided into two clusters and the Kalash of Central/South Asia did
not form a separate cluster). In fact, Rosenberg et al. (2005)
explicitly said:
“Our evidence for clustering should not be taken as evidence of our support of any particular concept of ‘biological race.’”
Finally,
the creators of structure themselves caution
that it will produce rather arbitrary clusters when sampled populations
have been influenced by gene flow that is restricted by geographic
distance (i.e. where more mating occurs between members of nearby
populations than between populations that are located farther apart, a
pattern we geneticists refer to as
isolation by distance). As this pattern applies to the majority of human populations, it makes the results of
structure
problematic and difficult to interpret in many cases. These limitations
are acknowledged by anthropological geneticists and population
biologists, who interpret the results of
structure cautiously.
It’s very telling that Wade, a science reporter, chose to ignore the
interpretations of the experts in favor of his own.