Posts tagged ‘genetics’

Social Structures

| Gabriel |

Shortly before ASA, I finished John Levi Martin’s Social Structures and I loved it, loved it, loved it. (Also see thoughts from Paul DiMaggio, Omar Lizardo, Neil GrossFabio Rojas, and Science). I find myself hoping I have to prep contemporary theory just so I can inflict it on unsuspecting undergrads. The book is all about emergence and how fairly minor changes in the nature of social mechanisms can create quite different macro social structures.* It’s just crying out for someone to write a companion suite in NetLogo, chapter by chapter. In addition, JLM knows an enormous amount of history, anthropology, and even animal behavior and uses it all very well to both illustrate his points and show how they work when the friction of reality enters. For instance, he notes that balance theory breaks down to the extent that people have some agency in defining the nature of ties and/or keeping some relations “neutral” rather than the ally versus enemy dichotomy.**

An interesting contrast is Francis Fukuyama’s Origins of Political Order, which I also liked. The two books are broadly similar in scope, giving a sweeping comparative overview of history that starts with animals and attempts to work up to the early modern era. (There are also some similarities in detail, such as their very similar understandings of the “big man” system and that domination is more likely in bounded populations). There is an obvious difference of style in that Fukuyama is easier to read and goes into more extended historical discussions but the more important differences are thematic and theoretical. One such difference is that Fukuyama follows Polybius in seeing the three major socio-political classes as the people, the aristocracy, and the monarch, with the people and the monarch often combining against the aristocracy (as seen in the Roman Revolution and in early modern absolute monarchies). In contrast, JLM’s model tends to see the monarch as just the top aristocrat, though his emphasis on the development of transitivity in command effectively accomplishes some of the same work as the Fukuyama/Polybius model.

The most important difference comes in that  Fukuyama is inspired by Weber whereas JLM uses Simmel, a distinction that becomes especially distinct as they move from small tribal bands to early modern societies. Fukuyama’s book is fundamentally about the tension between kinship and law as the fundamental organizing principle of society. In Fukuyama’s account both have very old roots and modernity represents the triumph of law. In contrast, JLM sees kinship (and analogous structures like patronage) as the fundamental logics of society with modernity being similar in kind but grander in scale. In the last chapter and a half JLM discusses the early modern era and here he sounds a bit more like Fukuyama, but he’s clearly more interested in, for instance, the origins of political parties than in their transformation into modern ideological actors.

In part this is because, as Duncan Watts observed at the “author meets critics” at ASA, JLM is mostly interested in that which can be derived from micro-macro emergence and tends to downplay issues that do not fit into this framework.*** This is seen most clearly in the fact that the book winds down around the year 1800 after noting that (a) institutionalization can partially decouple mature structures from their micro origins and (b) ideology can in effect form a sort of bipartite network structure through which otherwise disconnected factions and patronage structures can be united (usually in order to provide a heuristic through which elites can practice balance theory), as with the formation of America’s original party system of Federalists and Democrats which JLM discusses in detail. Of course as I said in the “critics” Q&A, at the present most politically active Americans have a primarily ideological attachment to their party without things like ward bosses and perhaps more interestingly, a role for ideology as a bridge is not an issue restricted to the transition from early modern to modern. As is known to any reader of Gibbon, there was a similar pattern in late antiquity in how esoteric theological disputes over adoptionist Christology and reconciliation of sinners provided rallying points for core vs periphery political struggles in the late Roman empire. Since this is largely a dispute over emphasis, it’s not surprising that JLM was sympathetic to this but he noted that there are limits to what ideological affinity can accomplish and when it comes to costly action you really need micro structures. (He is of course entirely right about this as seen most clearly in the military importance of unit cohesion, but it’s still interesting that ideology has waxed and patronage waned in party systems of advanced democracies).

There are a few places in the book where JLM seemed to be arguing from end states back to micro-mechanisms and I couldn’t tell whether he meant that the micro-mechanisms necessarily exist (i.e., functionalism) or that such demanding specifications of micro-mechanisms implied that the end state was inherently unstable (i.e., emergence). For instance, in chapter three he discusses exchange of women between patrilineal lineages and notes that if there is not simple reciprocity (usually through cross-cousin marriage) then there must be either be some form of generalized reciprocity or else the bottom-ranked male lineages will go extinct. On reading this I was reminded of this classic exchange:

That is, I think it is entirely possible that powerful male lineages could have asymmetric marital exchange with less powerful male lineages and if the latter are eventually driven into extinction then that sucks for them. (The reason this wouldn’t lead to just a single male lineage clan is because, as Fukuyama notes, large clans can fissure and tracing descent back past the 5th or 6th generation is usually more political than genealogical). This is the sort of thing that can actually be answered empirically by contrasting Y chromosomes with mitochondrial DNA. For instance, a recent much publicized study showed that pretty much all ethnically English men carry the Germanic “Frisian Y” chromosome. The authors’ interpretation of this is that a Saxon mass migration displaced the indigenous Gallo-Roman population but I don’t see how this is at all inconsistent with the older elite transfer model of the Saxon invasion if we assume that the transplanted foreign elite hoarded women, including indigenous women. A testable implication of the elite transfer model is that the English would have the same Y as the Danes and Germans but similar mitochondria as the Irish and Welsh. Similarly, a 2003 study showed that 8% of men in East and Central Asia show descent on the male line from Ghengis Khan but nobody has suggested that this reflects a mass migration. Rather in the 12th and 13th centuries the Mongols used rape and polygamy to impregnate women of many Asian nations and they didn’t really give a damn if this meant extinction of the indigenous male lineages.

A very minor point but one that is important to me as a diffusion guy is that chapter five uses the technical jargon of diffusion in non-standard ways, or to be more neutral about it, he and I use terms differently. That said it’s a good chapter, it just needs to be read carefully to avoid semantic confusion.

This post may read like I’m critical of the book but that’s only because I prefer to react to and puzzle out the book rather than summarize it. What reservations I have are fairly minor and unconfident. My overall assessment is that this is a tremendously important book that should be read carefully by anyone interested in social networks, political sociology, social psychology, or economic sociology. For instance, I wish it had been published before my paper with Esparza and Bonacich as using the chapter on pecking orders would have allowed us to develop more depth to the finding about credit ranking networks. (That and it would have given us a pretext to compare Hollywood celebrities to poultry and small children). Despite the book’s foundation in graph theory, this interest should span qualitative/quantitative — at ASA Randy Collins praised the book enthusiastically and gave a very thoughtful reading and from personal conversation I know that Alice Goffman was also very impressed. I think this is because JLM’s relentless focus on interaction between people is a much thinner but nonetheless similar approach to the kinds of issues that qualitative researchers tend to engage with. Indeed, at a deep level Social Structures has more in common with ethnography than with anything that uses regression to try to describe society as a series of slope-intercept equations.

————-

* Technically, it’s about weak emergence, not strong emergence. At “author meets critics” JLM was very clear that he rejects the idea of sui generis social facts with an independent ontological status rather than just a summary or aggregation of micro structure.

** One of the small delights in the early parts of the book is that he notes how our understanding of network structure is driven in part by the ways we measure and record it. So networks based on observation of proximity are necessarily symmetric whereas networks based on sociometric surveys highlight the contingent nature of reciprocity, networks based on balance theory tend to be positive/negative whereas matrices emphasize presence/absence and are often sparse, etc. I might add to his observations in this line that the extremely common practice of projecting bipartite networks into unipartite space (as with studies of Hollywood, Broadway, corporate boards, and technical consortia) has its own sets of biases, most obviously exaggerating the importance and scalability of cliques. Also, I’ve previously remarked on a similar issue in Saller’s Personal Patronage as to how we need to be careful about directed ties being euphemistically  described as symmetric ties in some of our data.

*** Watts also observed that JLM’s approach is very much a sort of 1960s sociometry and doesn’t use the recent advances in social network analysis driven by the availability of big data about computer-mediated communication (such as Watts’ current work on Twitter). JLM responded with what was essentially a performativity critique of naive reliance on web 2.0 data, noting for instance that Facebook encourages triadic closure, enforces reciprocity, and discourages deletion of old ties.

August 24, 2011 at 3:54 pm 9 comments

Or you could just do regressions

| Gabriel |

Over at the “Office Hours” podcast (née Contexts podcast), Jeremy Freese gives an interview about sociology and genetics. The main theme of it is that when you have a model characterized by nonlinearity, positive feedback, and other sorts of complexity, you can get misleading results from models with essentially additive assumptions like the models we use to calculate heritability coefficients. (Heritability is closely analogous to a Pearson correlation coefficient. It is usually calculated from data about outcomes for fraternal vs identitical twins and uses reasonable assumptions about how much genetics these twins share, respectively 0.5 vs 1.0).

Jeremy gives the example that if people have small differences in natural endowments, but they specialize in human capital formation in ways that play to their endowments, then this will show up as very high heritability. Jeremy suggests this is misleading since the actual genetic impact on initial endowment is relatively small. I agree in a sense, but in another way, it’s not misleading at all. That is, the heritability coefficient is accurately reflecting that a condition is a predictable consequence of genetics even if the causal mechanism is in some sense social rather than entirely about amino acids.

This is exactly the same issue as an argument I had with one of my co-authors a few years ago. We were studying how pop songs spread across radio and dividing how much of this was endogenous (stations imitating each other) versus exogenous (stations all imitating something else). The argument was how to understand the effects of the pop charts published in Billboard and Radio & Records. One of my co-authors was arguing that these are not radio stations but periodicals and therefore should be considered exogenous to the system of radio stations. Myself and the other author held the position that appearing on the pop charts is an entirely predictable consequence of being played by a lot of radio stations and therefore it is endogenous, even if the effect is proximately channeled through something outside the system. I believe this is true in an ontological sense but it’s also a convenient belief since it’s necessary to make the math work.

Anyway, back to Jeremy’s case, you have a lot of things that are predictable outcomes of genetic endowment but for the sake of argument we can assume that we are really dealing with a small initial effect that is greatly magnified by a social mechanism. I would submit that in the current set of social circumstances the heritability coefficient as naively measured is very informative. This is sometimes contrasted with how informative it is in the abstract, but if you take gene-environment interdependence (or any complex system) seriously, then “in the abstract” is a meaningless concept. Rather you can only think about a counterfactual heritability coefficient in a counterfactual social system. This calls out for counterfactual causality logic to see how effects vary on different margins, etc, of the sort developed by Pearl and operationalized for social scientists by Morgan and Winship.

Currently, American social structure allows a lot of self-assignment to different trajectories, including an expensive (at both the personal and societal level) system of “second chances” for people to get back into the academic trajectory whether they show much aptitude for it or not and have sufficient remaining years in the labor market to amortize the human capital expense or not. As such there is sorting but it’s fairly subtle and to a substantial extent voluntary. This is the situation Jeremy describes in his stylized example of people voluntarily accruing human capital to complement natural endowments.

We can contrast this with two hypothetical scenarios. In counterfactual A, imagine that we had perfect sorting to match aptitude to development. Think of how the military uses the ASVAB to assign recruits to occupational specialties. Better yet, imagine some perfectly measured and perfectly interpreted genetic screen for aptitudes measured at birth, and on that basis we sent people from daycare onwards into a humanities track, a hard science track, or various blue collar vocational tracks with no opportunity for later transfers between tracks. That is, in this scenario we would see much stronger sorting to match aptitude and career than in the status quo. In counterfactual B, we can imagine that people are again permanently and coercively tracked, but tracking is assigned by a roulette wheel. That is, there would be no association between endowments and later experiences. In these two scenarios we could puzzle out a variety of consequences. Aside from the degradation of freedom taken as an assumption of the counterfactuals, the most obvious implications are that higher sorting would increase the dispersion of various outcome measures and the apparent heritability effect whereas random sorting would decrease outcome dispersion and measured heritability.

When people talk about heritability coefficients being biased as high, they seem to have in mind something like the random sorting model. This model strikes me as only useful as a thought experiment to establish the lower bounds of heritability since in the real world a Harrison Bergeron dystopia isn’t terribly likely. Rather we can think of scenarios that are roughly similar to reality, but vary on some margin. For instance, we can imagine how various policies (e.g., merit scholarships vs. need-based scholarships) might increase or decrease the sorting of genetic endowment and complementary human capital development on the margin and by extension what impact this would have on the distribution and covariation of outcomes.

[Update 10/22/2010: On further reflection, I can think of a scenario where a naive reading of heritability coefficients would still strike me as grossly misleading, even if it were reliable, and I would prefer the “random assignment” counterfactual as “true” heritability. Imagine a society that is genetically homogenous as to skin pigmentation genes, but where having detached earlobes were a social basis for assigning people to work indoors. In this scenario, there would be non-trivial heritability for skin color even though (by assumption) this society has no variance (and hence no heritability) for genes directly affecting pigmentation. Similarly, imagine a society where children without cheek dimples were exposed to ample lead and inadequate iodine, thereby making the undimpled into a hereditary caste of half-wits even though the genes that create dimples have no direct effect on g. I suppose what I’m getting at is that social mechanisms that select on and magnify genetic endowments are one thing, whereas social processes based on completely orthogonal stigma are another.]

October 20, 2010 at 5:18 am 3 comments


The Culture Geeks