What has Nature vs. Nurture got to do with Nature vs. Nurture? II

The previous post asked about the connection between two different Nature-Nurture issues: the matter of fixity versus flexibility in the development of traits in individuals over their life course and the relative degrees of hereditary versus environmental influences on the variation of the trait between versus within groups? (“Groups” here refers to males or females, but the question might be extended to socially defined racial or socio-economic groups.) 

One answer, given in that post, is, in summary:

If three assumptions are made, then partitioning of the variation of the trait within each group can be interpreted as indicating the relative degrees of hereditary versus environmental influences on the variation of the trait, even if the specific genes making up the hereditary influence are yet to be identified. Once they are identified, the hypothesis that those genes are involved in variation between the averages of the groups can be examined. If the hypothesis is confirmed, then we have gained knowledge about the differences between the averages of the groups.  The ways that this knowledge about difference is pertinent to the other Nature-Nurture issue—fixity versus flexibility in the development of traits—depends on whether the study of difference is seen as a way to probe development or as something that takes development as given.

However, none of the three assumptions is reliable, for the reasons given below.  Noting this invites us to ask what leads people to make the assumptions (perhaps unwittingly) when they see the two Nature-Nurture issues as related.

Unreliability of the assumptions

a. Genetic gradient: “a gradient of a measurable genetic factor (or composite of factors)… run[s] through the differences among variety means” (Taylor 2014, 28) (where for humans a variety could be twins).

Recall that heritability is the technical name for the ratio of variation among variety means to the overall variation for the trait.  From a previous post:

One way to estimate heritability involves comparing the similarity of identical twins, who share all their genes, with the similarity of fraternal twins, who share a smaller %; in both cases, the twins are raised together.  Suppose I provide a height data set for twins of both kinds and heritability is calculated at 90%.  Researchers seeing the 90% as genetic might plan to search for the height genes.  The problem with that move is that in my data the twins included humans, snakes, and sorghum plants.  So we wouldn’t expect the same genes to be involved in height from one pair to the next.  [We wouldn’t expect there to be a genetic gradient.]  Yet there is nothing in the data analysis to expect that even if the twins had all been humans.

b. Underlying homogeneity is the absence of underlying heterogeneity, which is possible in partitioning variation because, “[e]ven if the similarity between twins or a set of close relatives is associated with the similarity of yet-to-be-identified genetic factors, the factors may not be the same from one set of relatives to the next, or from one environment to the next” (Taylor 2014, 19-20).

We know, for example, that people arrive at the adult height in many different ways, not only in the timing of growth (early vs. late growth spurt), but also the make-up of height (e.g., long-legged vs. long torso).  What evidence do we have that other traits, from heart disease to intelligence test scores, are not similarly developmentally heterogeneous?  “[G]enomic studies have had very limited success identifying causally relevant genetic variants behind variation in human traits (McCarthy et al. 2008, Couzin-Frankel 2010), a result that is not be surprising if there is heterogeneity in the factors underlying most traits” (Taylor 2014, 44).

c. Within-group causes extend to explanation of differences between the averages of groups.  That this is not always a warranted assumption is evident when considering, for example, the trends in average height for Japanese during the C20 (graph, original source not given), which presumably are accompanied by variation around those averages.  Explanation of the trends focuses on improvements in diet, but no-one suggests that variation among people at any point in time is dietary.   Average IQ test scores have shown marked generation-to-generation increases in industrialized nations (the “Flynn effect”).  The explanation is not yet clear, but it is not change in gene frequencies, while most researchers accept a role for genes in the variation in any generation.  Everyone accepts a role for genes in height variation among women; similarly for height variation among men.  But is there any reason to assume that the same genes are involved in explaining the difference in average height between women and men, as against factors, such as sex-related hormonally mediated age of puberty and cessation of height growth?

When the assumptions are taken together, we can puzzled over what it means to explain a difference between averages for groups.  Drawing from Taylor (2014, 90ff):

[T]he conventional mode of explaining the difference between individuals in the two groups… involves two steps: first we account for the difference between the average values for the groups, then for the difference of the individual from their group’s average. In the conventional mode we would say “Euro-American females are, on average, taller than Asian-American females” or “Watutsis are taller than Pygmies.” In contrast to such two-step accounting we could take the spread within both of the two groups as our starting point and attempt to expose the heterogeneous combinations of factors that influence the development of the trait for the range of individuals…

The figure below depicts the frequency of a trait, such as height, for two groups of people raised in two situations, a and b (which may or may not be the same). (Here, four underlying factors are included and are linked so as to indicate that the influence of a genetic factor on the dynamics of development is dependent on the environmental factors, and vice versa.)  [The overlap of the two groups’ genetic factors and environmental factors indicates schematically that the factors underlying the trait are heterogeneous.]  If there is heterogeneity of underlying factors, there are many subsets of group A who share more of the genetic and environmental factors that influenced the development of their height with some subsets of the group B than they do with the other individuals in group A.

TwoGroupUnderlyingHeterogeneity

 

The picture of underlying heterogeneity does not rule out the possibility that within each group certain genetic and environmental factors are common to the development of all individuals. (Common factors would mean that differences between those factors are shared by each pair of individuals from the two groups.) However, explanation would not begin by assuming that is the case, let alone assuming that factors shared within a group were the dominant ones in accounting for differences between individuals. Such patterns would have to be demonstrated, not assumed.

Of course, the picture of underlying heterogeneity does not rule out the possible difference in averages for the underlying factors (as well as the trait in question).  It does, however, reduce whatever grounds or inclination one might have had for using an individual´s membership in a group to formulate reliable expectations or make pre-judgements for any given individual about the trait or the factors underlying the trait.  (A probabilistic expectation could be made, but knowing the distribution of, say, IQ test scores is not helpful for a teacher interacting with a specific child.)

Given that none of the three assumptions is reliable, what leads people to make the assumptions (perhaps unwittingly) when they think that the two Nature-Nurture issues are related?  My conjecture (taken up in a future post) is that the significance given in society to divisions by gender and race feed back into giving plausibility to the unreliable assumptions.

References

Couzin-Frankel, J. (2010). “Major heart disease genes prove elusive.” Science 328(5983): 1220-1221.

McCarthy, M. I., G. R. Abecasis, et al. (2008). “Genome-wide association studies for complex traits: consensus, uncertainty and challenges.” Nature Reviews Genetics 9(May): 356-369.

Taylor, Peter J. (2014) Nature-Nurture? No: Moving the Sciences of Variation and Heredity Beyond the Gaps.

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