
When you do this with genetic data and human populations and use adequate sample representation PC1 is almost always African vs. non-African and PC2 is West Eurasia/North Africa vs. the rest of the world that’s not Africa. Though one can quibble with the details the reality is that these patterns are easy to reconcile with evolutionary history. Humans first split between Africans and non-Africans, and the west vs. east division in Eurasia is arguably the next major bifurcation (and gene flow barrier).

If you look at the distributions pretty much none of them should be surprising to you historically. Protestant Northern Europe was very different in 1700 from today, but it was already a coherent socio-cultural phenomenon. Similarly, Russia has been historically distinct from Western Europe culturally for nearly the whole of its existence as a coherent polity (from ~1000 AD on). In fact, the marriage of Ann of Kiev into the French royal family in the 11th century may be indicative of the closest relationship of what became Russia to the West before the early modern period.* On this map, Russia and other Eastern European nations are quite distant from Northern Europe, and to some extent from Catholic Europe.
But this map isn’t just a reflection of geography. You see that Serbia, Bosnia, Croatia, and Slovenia occupy positions in relationship to Russia and Western Europe exactly where you would predict from their history. Serbia has a much stronger affinity with Russia, Croatia is in Catholic Europe, while Slovenia seems more like Northern European nations than Croatia. Bosnia occupies a position between Croatia and Serbia. These variations are important because ethno-linguistically the divisions between Serbians, Croatians and Bosnians (and lesser extent Slovenians) are minor. They originate from groups of Slavs who settled among the native Pannonians, whether Latin or Illyrian speaking, only in the centuries before 1000 AD.

But most people don’t know much history. This is why visual representations of quantitative social science data are quite useful. It’s almost impossible to convince the ignorant of historical truths when they don’t know any history because they can’t tell if you are making things up. Usually they trust you if you are part of their in-group, and distrust you if you are of an out-group.
For example, over the years a few times I’ve had really strange conversations about whether Russia is a Western nation or not on Twitter. There are roughly two groups that assert Russia is a Western nation: 1) white nationalists, for whom whiteness is necessary and sufficient for being Western 2) historically naive public intellectuals who can’t evaluate competing hypotheses, and implicitly impute Western identity to Russia because Russians are white and Christian (at least culturally). With white nationalists obviously there isn’t going to be a major argument. Their framework is just so different.


This brings me to a new paper in PNAS (OA), Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization. It’s one of the first results from the Seshat: Global History Databank. Peter Turchin is heavily involved in this, but I notice the above paper also includes Harvey Whitehouse on the author list. I’ve long admired his work on the cognitive dimension of cultural production and variation.
Here’s the abstract:
Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as “Seshat: Global History Databank.” We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years. We were able to capture information on 51 variables reflecting nine characteristics of human societies, such as social scale, economy, features of governance, and information systems. Our analyses revealed that these different characteristics show strong relationships with each other and that a single principal component captures around three-quarters of the observed variation. Furthermore, we found that different characteristics of social complexity are highly predictable across different world regions. These results suggest that key aspects of social organization are functionally related and do indeed coevolve in predictable ways. Our findings highlight the power of the sciences and humanities working together to rigorously test hypotheses about general rules that may have shaped human history.
Intuitively most people would have guessed this. Social complexity is a thing. Human cultural evolution has exhibited some directionality or at least a general secular trend. If you have read a lot of history and thought about these things you’d come to these conclusions intuitively.
I could also assert that northern France in the 12th century AD was a more socially complex society than the one the Romans conquered in the 1st century BC. Why? I could give plenty of reasons. But it is at this point that a fashionable viewpoint in some academic circles would problematize this assertion, and argue that characterizing High Medieval France as more complex than pre-Roman Gaul exposes one’s own assumptions and beliefs, as opposed to facts about the world.

This is why figures like the one to the left are important. It shows values on the social complexity factor, PC1, for Latium (red), the Paris basin (blue) and Iceland (green). What you see is that the Paris basin lags Latium up until around 0 AD. At this point there is catch-up. Though Gallic social complexity was already increasing in the centuries up to the Roman conquest (one reason the Romans found conquest of Gaul useful was that it was wealthy enough to steal from), it was only around the time of assimilation into the Roman state that it caught up to Latium.
Latium and the Paris basin both decrease in social complexity after the fall of the Roman Empire. But after 1000 AD the Paris basin outstrips Latium. In the 12th century it does seem that the Paris basin was more socially complex than it was in the pre-Roman period.

The authors show that the nine complexity characteristics are highly correlated with each other. Some of these make sense (those related to polity scale). But others are not as straightforward, though the verbal arguments present themselves (e.g., polities with lots of people are more likely to need written scripts for bureaucratic record keeping; the data show this to be true). Additionally, the models that are general can predict patterns in individual regions. That implies that the same dynamics are occurring cross-culturally. Each society is not sui generis for the purposes of analysis.
Of course a standard retort will be that the selection and coding of criteria of complexity itself is biased. That’s fine. But with formal methods we can actually hash out disagreements and points of interpretation in a much simple and clear manner than before. Ultimately I think those who object to this sort of analysis actually object to analysis driven by data and formal methods, as opposed to their own intuitions and personal preference. After all, it’s not a great discovery to find that there is a common cross-cultural dynamic which underpins social complexity.
But in the future Seshat and the researchers who utilize it will smoke out counter-intuitive or surprising results. The data and methods are there.
* Ann herself seems to have been mostly of Scandinavian ancestry as was the norm for the early Kievan nobility. Her mother was a Swedish-born princess, while her father was a Slavicized Rurikid.

