In my previous post, Historians and Historical Databases, I discussed how the Seshat Databank would be impossible without a close collaboration with historians and other humanities scholars. Today I want to give a specific example of how this collaboration works.

For those who have not followed the Big Gods controversy closely, last Spring the Seshat project published an article in Nature, Complex Societies Precede Moralizing Gods throughout World History. The article generated a ton of positive press (as is usual for a Nature article), but it also elicited critique from some, including supporters of the Big Gods theory. We have responded to these critiques on the preprint server SocArXiv (https://osf.io/preprints/socarxiv/xjryt; https://osf.io/preprints/socarxiv/t8hgu).

The heart of a departed is weighed against the Feather of Ma’at Source

But the Nature paper was only the first of many planned articles investigating the role of religion, morality, and other factors in the evolution of social complexity. We have recently completed a further wave of analyses using more detailed data on moralizing religion, and testing additional theories explaining the evolution of Big Gods. The new analyses confirm our original headline finding (that Big Gods come after Big Societies) and also explore additional dimensions to this complex topic. Before we submit it a journal, however, we want to get feedback from all interested parties, including our critics.

To make the whole process extra transparent, we have posted all related documents online. The main article is on SocArXiv: https://osf.io/preprints/socarxiv/2v59j/, and it is accompanied by supplementary online materials that include the data and the analysis scripts. Our aim is to achieve maximum transparency and critical engagement—everyone who wants, can critique and comment on each phase and reanalyze the data.

But we are also breaking new ground in this project. In addition to posting data and programs, we have invested a huge amount of effort into clarifying where the data come from. And this is where the collaboration with humanities scholars become critical. Most of the work during the past several months was devoted to building “analytic narratives” underlying the Seshat data.

Analytic Narratives are formalized verbal accounts focusing on several (in our case, many) in-depth case studies. The goal of this methodology is to employ the specialized knowledge possessed by historians, archaeologists, anthropologists, and religious studies scholars, who have the understanding of the particular, for the purpose of testing theories that may apply more generally. General theory (which focuses on moralizing religion in our case) imposes structure on verbal accounts by specifying which aspects of past societies we would like to get information on. But within this framework, scholars are free to explore variability between different societies, different continents, and different eras. The aim is to reflect in the document evolving interpretations and persisting controversies. Such qualitative nuance provides a much needed counterbalance to the “hard” quantitative data, which by their nature strip it away.

For those interested in looking “under the hood”, the current draft of this document is posted here:

http://seshatdatabank.info/wp-content/uploads/2019/11/MSP_Narratives_CurrDraft.pdf

Keep in mind that it is very much work in progress—some chapters and sections contain much more text and references than others. There are several reasons for this, the main being that there are societies for which we haven’t yet been able to recruit experts. Our approach in such cases is to “prime the pump” by including an initial description, based on the reading of available sources and then invite expert feedback and elaboration on this initial text.

As I stressed in my previous post, the success of Seshat critically depends on close collaboration with professional historians and other humanities scholars. By adding Analytic Narratives to the spectrum of products from the Seshat project we aim to deepen this collaboration and, more generally, to contribute to a dialogue between humanities and sciences. The richness and quality of Seshat results will also be enhanced. I am very keen to see how this will develop in the near future.

In recent days there was much discussion by historians on Twitter of the proper and improper uses of historical knowledge in testing social science theories. It was initially prompted by the publication of a Science article last week on historical Church exposure and global psychological variation. Most of it was quite negative (I am still reading the article and its voluminous appendices, so I reserve judgment). Some of this negative reaction spilled over to Seshat as a result of Laura Spinney’s publishing yesterday a “long read” on Cliodynamics and the Seshat Databank in the Guardian. But such criticism can only come from those who know nothing about how Seshat works.

The Seshat Project is a collaboration between historians, archaeologists, and social scientists. Historians play key roles in all phases of building the Databank. Two out of five members of the core group have PhDs in History. Historians are involved in the workshops in which we develop conceptual scheme for translating knowledge about past societies into data; they consult Seshat research assistants and check Seshat data, and they fully participate in writing the resulting articles. Seshat articles typically have dozens of authors (in two cases over 50), most of them historians. Seshat would be impossible without such intense collaboration between scientists and humanities scholars. You can read more about how Seshat operates in “An Introduction to Seshat: Global History Databank,” in press in Journal of Cognitive History (SocArXiv Preprint).

Collaboration between scientists and humanists requires a lot more work than other interdisciplinary projects. The “two cultures” are often motivated by different research interests and goals, and use very different methodologies and languages. This is one of the reasons why Seshat spent such a long time in gestation (the project was launched in 2011, but the first article fully utilizing Seshat data was published only in early 2018). Our multi-authored articles go through innumerable iterations before the co-authors, coming from very different research traditions, can arrive on mutually intelligible and agreeable texts. This is a stiff price, but well-worth paying.

Seshat goals also reflect the diversity of motivations of the project participants. As a scientist I am primarily motivated by using the rich knowledge, possessed by the scholars of the past, in testing scientific theories about how human societies evolve over time. But over the last three decades I read and enjoyed thousands of books and articles by specialist historians and archaeologists, who delve into the intricate inner working of past human societies. Such knowledge is fascinating to me because of its intrinsic worth, irrespective of whether we capture it in the Databank.

Initially I thought that only a small fraction of historians would be interested in the Seshat data. I am happy to report that I was wrong. In fact, most historians we approach get involved. The degree of involvement varies. Some help us with identifying good general sources and answer a few questions. Others write detailed narratives and code datasheets with hundreds of variables. Most find a comfortable level of involvement somewhere in between.

Furthermore, many historians are interested not only in studying a particular society, or a segment of it, at a particular time (which is a very worthwhile and important), but also care about comparative history. Seshat allows one to start in a particular society at a particular time and focus on a particular aspect of it, and then “travel” back and forth in time, or in space, or in the conceptual space of different variables. It’s like “comparative history on steroids.”

Thus, Seshat is not only a vehicle for testing scientific theories, it is also a great informational resource both for the scholars of the past and (eventually) for general public. We are currently working on implementing features in the Databank that would make travel in time, geographical space, and conceptual space effortless. And Seshat publications are not limited to articles in scientific journals. We also produce “Analytic Narratives”, formalized verbal accounts focusing on multiple in-depth case studies. The first such narrative, Seshat History of the Axial Age, will be published in early December, and two more are in the works.

In closing, I want to reiterate that Seshat is far from being a threat to History. Seshat depends on the work of countless professional historians who are contributing to a remarkable store of knowledge about the human past. It also builds on and expands comparative history, which has been what historians have done ever since Polybius and Ibn Khaldun. Seshat also allows us to test various theories about the functioning and dynamics of past societies proposed by historians, archaeologists, anthropologists, and economists. By doing that, the Databank increases our understanding of how present-day societies work. And perhaps it will even enable us to change our societies so that they could deliver better human well-being. The last is not certain, but we will not know whether it is possible until we try.

Last week I visited Centre for Complex Systems Studies (CCSS) in Utrecht, where I gave a talk about my research results and plans for the Ages of Discord project. Several people on Twitter asked to see the slides, and so I am posting them on this blog.

First, here’s an abstract of the talk:

A History of the Near Future: What history tells us about our Age of Discord
Peter Turchin
Complexity Science Hub Vienna, and University of Connecticut

Social and political turbulence in the United States and a number of European countries has been rising in recent years. My research, which combines analysis of historical data with the tools of complexity science, has identified the deep structural forces that work to undermine societal stability and resilience to internal and external shocks. Here I look beneath the surface of day-to-day contentious politics and social unrest, and focus on the negative social and economic trends that explain our current “Age of Discord.”

Second, the slides are posted as PDF here.

Third, you might be interested in two articles that provide more detail on our research plans:

Turchin, Peter, Nina Witoszek, Stefan Thurner, David Garcia, Roger Griffin, Daniel Hoyer, Atle Midttun, James Bennett, Knut Myrum Næss, and Sergey Gavrilets. 2018. History of Possible Futures: Multipath Forecasting of Social Breakdown, Recovery, and Resilience. Cliodynamics 9: 124–139.

Turchin, Peter, Sergey Gavrilets, and Jack A. Goldstone. 2017. “Linking ‘Micro’ to ‘Macro’ Models of State Breakdown to Improve Methods for Political Forecasting.” Cliodynamics 8: 77–99.

As the readers of this blog know, a big chunk of my research focuses on why complex societies go through cycles of alternating internally peaceful, or integrative, phases and turbulent, or disintegrative periods. In all past state-level societies, for which we have decent data, we find such “secular cycles” (see more in our book Secular Cycles).

What was a surprise for me was to find that pre-state societies also go through similar cycles. Non-state centralized societies (chiefdoms) cycle back and forth between simple (one level of hierarchy below the chief) and complex (two or more hierarchical levels) chiefdoms. But now evidence accumulates that even non-centralized, non-hierarchical societies cycle. The work by archaeologists, such as Stephen Shennan, showed that various regions within Europe went through three or four population cycles before the rise of centralized societies (see, for example, his recent book The First Farmers of Europe).

These cycles were quite drastic in amplitude. For example, last month at a workshop in Cologne, I learned from archaeologists working in North Rhine that population declines there could result in regional abandonment. Several hypotheses have been advanced, including the effects of climate fluctuations, or soil exhaustion. But there is no scientific consensus—this is a big puzzle.

One hypothesis, which, for some reason, doesn’t get much attention, is the role of warfare in all this (I’ve written about this curious bias in this post and others). For example, a recent, and otherwise excellent article by Hofmann et al. on the rise and collapse of Tripolye mega-settlements (Governing Tripolye: Integrative architecture in Tripolye settlements) doesn’t mention words “warfare” or “war” even a single time! I’ll return to this article in a bit.

To fill this theoretical gap, I am starting a project in which we will model the rival hypotheses, including the one focusing on warfare, and will do a systematic empirical test of their predictions using data on several Neolithic populations.

But back to the Tripolye article. Hofmann et al. integrated the data coming from high-resolution magnetometry surveys (it never ceases to amaze me how rapidly archaeological methodology is advancing) of 19 mega-settlements and discovered that they all had large communal buildings. Here’s a map from the article of one well-studied settlement, Maidanetske:

The big red square with numeral 1 appears to be the main meeting/ritual building. There are 12 more intermediate size buildings, which are much larger than residential houses, and were also “integrative buildings” where joint decision-making meetings could take place (followed, it goes without saying, by feasting). What is particularly interesting is that we have a three level hierarchy here:

1. Usual houses (around 3,000 of them, implying total population in excess of 10,000)

2. Mid-level integrative buildings (12 of them), probably used to govern each district

3. Top level integrative building to govern the whole settlement.

At least, this is the reconstruction by the authors, which makes a lot of sense to me.

What is particularly interesting is the dynamics between 4100 BCE, when these giant settlements formed, and 3600 BCE, when they collapsed. It is schematically depicted in this figure from the article:

The mega-settlement was formed by a number of groups moving together. Each of the groups probably occupied a separate district with its own integrative building, and then they added the top-level meeting hall to work out the issues affecting the whole community. Later, however, mid-level meeting halls disappear, and only the top-level integrative building remained. And soon after that the whole settlement collapsed.

The authors argue that “the non-acceptance of this concentration of power and the decline of lower decision-making levels might be a crucial factor for the disintegration of Tripolye giant-settlements around 3600 BCE”. Perhaps. But this conclusion leaves a lot of questions unanswered.

First, why did the different groups move together in the first place? From almost any point of view, except one, this was a really poor decision. Such crowding together resulted in serious problems with sanitation and disease. Additionally, farmers had to waste a lot of time traveling to their fields, because such huge settlement required a lot of land to support it. The only reason for such population concentration that makes sense to me is collective defense.

There are many signs pointing to warfare as the primary mover behind the rise of Tripolye mega-settlements. The Tripolye people constructed elaborate defenses with not just one but two concentric rings of ditches. Another indicator of external conflict is burned houses. Of course, wooden houses can burn as a result of an accident, but note the green-colored “houses burnt (settlement 1)”. These houses are outside the ditch, and quite spread out. Enemy action is more likely as the cause of burning then accidental fire leaping from house to house. Finally, the authors note that the size of mega-settlements increases as one travels in the southeastern direction, and thus towards flatter steppe region, where defense is more difficult.

The second question is that at the end of the mega-settlement period, the population didn’t simply disperse out; there was a very substantial population collapse. Again, what was the reason for this? In historical periods the usual answer is pervasive endemic warfare. Not only war kills people, its effect on demography is even more due to the creation of a “landscape of fear,” which doesn’t permit farmers to cultivate fields, so that the local population gradually starves, has fewer babies, and is further diminished by out-migration. Such landscape of fear is not easily detectable archaeologically, because few people die violently (they keep to fortified settlements and are afraid to venture out).

As I said earlier, this internal warfare hypothesis is just one of possible explanations for the Neolithic collapses. We will get better answers by comparing model predictions to the data, and it looks like Tripolye would make a great case study in this research.

Scott Alexander wrote two reviews of my work on the structural-demographic theory: Book Review: Secular Cycles and Book Review: Ages of Discord. The first one, on Secular Cycles, is quite positive, but the tone of the second review is a bit uneven–generally positive, but with some notes of critique and suspicion. His suspicions of the data and theory in Ages of Discord (AoD), however, are misplaced. Still, I would be the first person to admit that AoD is a highly technical and, thus, difficult book — full of models, formulas, tables, and graphics. I am constantly thinking about a popular version of AoD, but I haven’t yet figured out how to lay it out for the general public (I am also currently completely occupied with the analysis of Seshat data). Here I offer a few thoughts in response to issues raised by Alexander.

While what follows may sound critical of his review, I emphasize (and reiterate at the end) that I greatly appreciate the amount of time and effort he invested into reading and digesting my books.

First, Alexander starts the review of Ages of Discord with on overview of empirical patterns and only much later gets to theory. This is not how AoD is organized and, as a result, he ends up confusing himself and, I think, readers. AoD is only the latest installment in my work on structural-demographic theory (see Chapter 7 and 8 in Historical Dynamics published in 2003). By the time I wrote AoD, structural-demographic theory has matured to the point where one could (and I did) make predictions about novel cases. AoD, thus, is mainly an empirical test of predictions for the USA between 1780 and 2010. It is true that the US has gone through only 1.5 secular cycles in its history, but my identification of these cycles is not based on just these 1.5 “points”. The case of the US is an “out of sample prediction”, as it is known among the analysts.

Predictions were listed in Table 1.1 of Secular Cycles, published in 2009. I devoted two chapters at the beginning of AoD to extending the structural-demographic theory to industrializing societies and refining the predictions for the US. These two chapters, however, have very significant mathematical component. By his own admission, mathematics is not one of Alexander’s strong suits, which is probably why he jumps into data right away. But by doing this, his review fails to give justice to the logical structure of AoD.

Second, Alexander does some “spot-checks to see whether the data are any good”. This is somewhat strange — all data sources are listed in AoD, does he think that I have falsified them? Naturally, he concluded that “Turchin’s data all seem basically accurate.”

Next, in an attempt to check whether I “cherry-picked the data series that worked”, he looks at a variety of random indicators, for example, treasure bonds. Here again, by missing the theoretical part he doesn’t do justice to AoD. The variables I focus on all follow from general theory. There are fundamental variables in the theory that drive the dynamics (immiseration, elite overproduction, state strength, and socio-political instability) and there are “proxies” — variables closely correlated with the fundamental drivers. Then there are variables about which the theory is silent. Treasure bonds in no way are part of the theory, and I have no idea whether they would correlate with anything important, so I never looked at them.

There are also variables that are affected by fundamental ones, but are not part of the feedback web (they don’t affect the main drivers). For example, homicide rates. We expect that popular immiseration and elite overproduction would result in social pressures for instability, and one surface indicator of that could be growing homicide rates. I discuss homicide data in both Secular Cycles and AoD. However, one should keep in mind that there are many other factors, apart from structural-demographic ones, acting on this class of variables. Thus, we do not necessarily expect a perfect correlation. In fact, while structural-demographic pressures continued to grow during the last four decades, homicide rates actually declined during the 1990s. One possible explanation is that incarceration rates have quadrupled over this period of time. But the more important point here is that homicide rates are not a fundamental driver in the theory.

A particularly strange indicator that Alexander looked at is the USD/GBP exchange rate. I have no idea why he did that. Once again, in my research on structural-demographic dynamics I do not trawl through the thousands of time-series available on the web to look for correlations. Such trawling inevitably will yield correlations, but with high probability such correlations will be spurious.

Third, one has to be careful with data on meaningful indicators, and examine its provenance. In his first review (of Secular Cycles), Alexander starts by showing “Chinese population over time.” He doesn’t specify the source, but I recognize it — it’s McEvedy and Jones. 1978. Atlas of World Population History. Unfortunately, this resource is quite dated. Furthermore, it smooths out a lot of cycles in the data. Compare it with this chart (for provenance, see Historical Dynamics):

Quite a difference! Not everything in this graphic is solid, but the main point I am making is that one simply can’t grab the first available chart; it’s important to give thought to data sources and to understand their limitations.

Fourth, you cannot take on faith various opinions — myths is not too strong a word — propounded by social scientists; they have to be evaluated critically. This is particularly true of economics, because economists have an enormous vested interest in propounding theories that would please various powers-that-be. I’ve written about it in several of my blog posts, e.g.

I am often asked, after my talks or on social media, to pass a judgment on the stability, or lack of it, of a particular country. For example, looking across the Atlantic to the United Kingdom, one sees a lot of parallels with the crisis we are currently living through in the US. The rise of populism, increasing fragmentation of the political landscape—do these similarities reflect deep structural trends below the surface? Such questions can only be answered with a proper structural-demographic analysis.

A research team based in Moscow’s Higher School of Economics recently published such an analysis in Cliodynamics. The article by Ortmans and colleagues brings a wealth of quantitative data (with over 30 figures) to inform our understanding of social pressures for instability in the UK. And it shows that similarities between the UK and the US go deep below the surface events.

As I explained in Ages of Discord, one of the most important factors in the structural-demographic analysis is the balance between the supply and demand for labor. The American economy has been operating under the conditions of labor oversupply since roughly the 1970s. The main causes were immigration, the entry of massive numbers of baby boomers and women into the labor force, the export of jobs overseas, and a few others (see a series of blogs I wrote on this).

Ortmans et al. show in their article that the UK developed the conditions of labor oversupply also during the 1970s, and for very similar reasons. The shift from labor undersupply to oversupply in the UK is clearly visible in the data on unemployment rate. While before 1975 the unemployment rate stayed below the four percent level, after 1975 it never declined to that level again:

Charts in this post are by the author, using data from the Ortmans et al. article

Labor oversupply is only one part of the story. To understand the “extra-economic” factors we need to go even further back in time than the 1970s.

In the United States persistent socio-political instability, peaking in c.1920, resulted in an adoption of an unwritten social contract between the labor, the capital, and the state which ensured that workers would get their fair share of the economic growth (see Chapter 10 of Ages of Discord for details). This social contract unraveled during the 1970s.

In the UK the timing of the shifts in the social norms and institutions that regulate labor-capital relations was very similar. The first shift is vividly represented by the rise of the Labour Party, which really took off after 1910:

Source: Wikipedia

The second shift was signaled by the rise of Reaganomics in the US and Thatcherism in the UK, which resulted in determined attacks on trade unions by governments and employers, epitomized by Reagan’s victory over the Air Traffic Controllers and Thatcher’s breaking of the National Union of Mine Workers. As a result, the participation of British workers in trade union has been declining since the peak of the early 1980s:

As workers and their institutions lost political power, they similarly lost economic power. This trend is quantified by the “relative wage”—median (typical) wage divided by GDP per capita, which tells us what proportion of gains from economic growth goes to the workers. Until 1975 relative wage fluctuated around a constant level, but between 1975 and 2015 it declined by roughly a third:

Other UK structural-demographic variables (economic inequality, elite overproduction, mass-mobilization potential, and intraelite conflict) also followed trends that were very similar to those in the US (see Ortmans et al). What accounts for such a remarkable degree of parallelism between the two countries? Note that such synchronized structural-demographic dynamics are not a foregone conclusion. Although all countries in the world are affected by the same global trends, which tend to make their internal dynamics to converge, there are many internal reasons, most importantly, differing histories and cultures, that work against such synchronization. As an example, France, just across the English Channel from the UK, also an economically developed liberal democracy, resisted the trends that we saw in the UK (and the US). In particular, economic inequality in France stayed roughly constant until recently, although in the US and the UK inequality has been growing for nearly 40 years.

Ortmans and colleagues offer an answer—the rise and rapid triumph of neoliberalism, which happened during the same period in both countries. It would be interesting to make a formal test of this hypothesis. If we can develop a quantitative measure of the influence of neoliberal ideas over the minds of various governing elites in European countries, then would it correlate with the increased economic inequality and other structural indicators? This would be a very interesting project.

I just came back from a trip to China, during which I and two friends traveled along the section of the Silk Route that passes through PRC. We started in Luoyang, then went to Xian, made three stops in the Gansu corridor, and finally reached Turpan and Urumqi in Xinjiang. Our main interest was geographical, historical and archaeological. I’ve written extensively about the northwestern frontier of China, and the role of the nomads in state-building, for example, in War and Peace and War. And I wanted to see both the landscapes, the archaeological sites, and historical museums (which turned out to be excellent — very well organized and highly informative). So the trip was a great success.

Historical museum in Luoyang, built on a typically gigantic scale. All photographs in this post are by P. Turchin

But an additional, and somewhat unexpected outcome of this trip was my much better understanding of the modern China. The previous time I was in China in 2004. Although there were already signs of impending change, the overall impression I got then was of China as a third-world country. Riding a bus through the Yangtze River Valley, we saw peasants using water buffalo for field work. And most towns and cities (including Beijing) we visited then looked “scruffy.” Here’s a picture I took back in 2004:

China 15 years ago

It was stunning to see how much the country changed in the last 15 years — really, a very short period of time, especially in the historical perspective. For me it was particularly interesting to see the transformation of China in light of periodic predictions one sees in the mass media about how China is about to collapse (imperial collapse being one of two of my main directions of research). For examples of such predictions see here, here, and here. I’ve been skeptical about these forecasts, and the ones made in early 2000s that China would collapse in 5, at most 10 years have completely missed the mark, of course. And what I saw this year, as well as changes over the previous 15 years, makes me even more convinced that such predictions are driven more by wishful thinking than serious science. Granted, what follows is based on personal impressions, not on a systematic study, so take it with a grain of salt.

The most visible sign of China’s transformation is the spectacular improvement in the quantity and quality of the infrastructure. While our infrastructure in the United States decays, China has been building high-speed railways, highways, and apartments.

View from the airplane approaching Beijing airport

Everything is done on a gigantic scale, which reflects the cultural predispositions of the Chinese going back at least two millennia. Everything works (e.g., trains arrive on time — something that the British, pioneers in building railways, cannot deliver any more).

A high-speed train arrives at a station. Our travel from Luoyang to Urumqi was entirely ground-based: mostly by high-speed train, with some segments by van.

Less visible to a traveler, but equally real, is a dramatic improvement in the quality of life for the ordinary people. I went to the same hutong (traditional neighborhood) in Beijing that I visited 15 years ago. The, it was “scruffy” — a dilapidated slum inhabited by poor people. The change in 15 years was remarkable. Note, in particular, the air conditioners in the metal cages:

One of the non-touristy hutongs

There has been a wholesale replacement of old and dilapidated housing, with people moving into apartments in high-rise apartment blocks. There are costs, of course. Personally, I much prefer living in a low-story individual house in the countryside. And the Chinese ironically refer to their apartments as “bird cages.” But these apartments are large (between 90 and 140 square meters; by comparison, when I grew up in the Soviet Union, and apartment of 50 square meters was considered to be large). Furthermore, it is quite likely that the move to the high-rise apartment building is a phase that will eventually be succeeded by the backward movement to the countryside, as it happened in America and, more recently, Russia. Given how rapidly things change in China, the next phase may not be too far ahead.

The rapid change of living standards is illustrated by biological (lots of tall young Chinese) and cultural change. Back in the 1980s, when a young man wanted to marry, he needed to demonstrate his material success by being able to buy for his wife a bicycle, a sewing machine, and a watch. Today the symbols of success are a car, an apartment, and jewelry.

Back in 2004 the streets of Beijing were dominated by myriads of bicyclers. Today, you hardly see any bicycles — they’ve been replaced by cars and electric scooters.

The Chinese themselves are highly aware of how rapidly their material well-being increased. This is, probably, why the levels of trust in government in China are the highest in the world.

At the same time, there is no question that China is a police state and many political freedoms are limited or lacking. As the most visible reminder, I couldn’t access Google, Wikipedia, or Amazon while in China. You need your passport not only for travel and hotels, but also to get into a museum.

However, there is no oppressive feeling engendered by large numbers of heavily armed police or soldiers (as one experiences in, for example, Mexico). In fact, I haven’t seen armed police anywhere, except for Xinjiang. We toured Tienanmen Square on June 5, precisely 30 years after the famous Tank Man event at the end of the 1989 Tienanmen Square protests. Yet there was no unusual activity by the police. This is what the area in front of Mao’s Mausoleum looked like:

Population is controlled and regulated, but not as much by the police, as by “public security volunteers” wearing red armbands. Another way of regulating population is that queuing up is typically enforced by metal guardrails.

In closing, while I haven’t done a formal structural-demographic analysis of China, my informal impression, based on what I’ve seen, suggests that China is a long way from a collapse.

A guest post by Harvey Whitehouse and Pieter Francois

This is an interesting moment in the development of history as an academic discipline. We stand on the brink of a sea change, not necessarily in the way historical evidence is gathered and documented, but in the way the resulting data can then also be compared across space and time. For those who are interested in theories about how human societies have evolved, these are exciting times. But they are also turbulent times because many of those theories will turn out to be wrong. One of the first casualties appears to be the hypothesis that big societies require moralizing gods.

Our Nature paper is just a first step towards adjudicating on the moralizing gods hypothesis. But it is an important step because it demonstrates that even using very lenient criteria for the presence of beliefs in supernatural punishment, such beliefs appear late in the rise of social complexity. Advocates of the view that such beliefs occur much earlier include distinguished academics whose work we respect. But the way some have recently gone about defending their cherished hypothesis is problematic.

In the first of two papers posted online our critics have argued that they can reverse our results by systematically changing the data to adjust for what they call ‘forward bias’. Unfortunately, half the adjustments they propose are indefensible on factual grounds effectively beyond dispute. Even if we adjust all the remaining data in their favour exactly as they propose, this doesn’t reverse our main finding, as claimed.

The second paper challenges the quality of our data and will be published in the Journal of Cognitive Historiography alongside a rebuttal that we are currently working on. The fact that both critiques have been ‘pre-published’ online, and that considerable effort has been invested to disseminate them to the widest possible audience, means we can no longer restrict our rebuttal to academic journals and the pressure is on to summarise key points at a much faster pace on more informal platforms, such as blogging sites. This situation has its limitations but it also affords novel opportunities.

A limitation of this informal online approach to debating scientific findings is that it is hard to coordinate critique and response. The pre-published attack on our work submitted to the JCH includes a substantial appendix, the contents of which we need to rebut at length (and will do so). But in the meantime, it could look to some as if a valid pre-published critique stands while the main finding of our Nature paper, which underwent rigorous peer review, can simply be dismissed. It would arguably have been better for science if critique and rebuttal had appeared side by side, as the journal editors in this case intended.

More positively, though, online debate allows us the license to step back more informally and consider bigger-picture issues. For example, are we really at a turning point in the history of history? Potentially yes. The likes of Marx, Spencer, Tylor, Frazer, and Durkheim – among other big-thinking Victorians – dreamt of establishing generalizable theories of history but they were held back by the ‘cherry picking problem’. That is, theories of history – from grandiose visions of economic and technological determinism through to the idea that the division of labour in society evolves through discernible stages – have always rested on evidence selected because it supported the theory, while less congenial evidence was rejected or overlooked. What is radically new about the approach adopted in our Nature paper is that it tests theories of history based on a serious effort to avoid bias in the selection of data by coding for features of social complexity, religion, and ritual, in exactly the same way across hundreds of polities. The data itself and the methods used to gather and analyse it are all publicly available so that colleagues can inspect it, replicate and criticize our efforts, and run analyses of their own. As we have seen, they can even run analyses that explicitly bias the data to fit their own theories if they so wish – but at least we can see clearly that this is what they are doing.

Seshat: Global History Databank allows us for the first time to address the problem of selection bias convincingly in our efforts to test theories of world history empirically. Fully realizing this vision requires the input of very large numbers of experts from fields as diverse as history, archaeology, classics, anthropology, comparative religion, and others. Many scholars in these fields, however, are wary of scientific methods so it is no mean feat to have attracted such large numbers (around 100 or so currently) to the Seshat enterprise. Can we continue to do so?

The very public attack on our data, analysis, and methods launched online, albeit using material that has not been peer reviewed, has the potential to undermine confidence in Seshat. Those leading the criticisms against us are closely associated with a rival database which is at a much earlier stage of development but which may hope to catch up if only we can be slowed down. Attacking Seshat could, however, hamper everyone’s efforts in this new field and not just our own.

If our new approach to the study of global history survives, this will be very good news for the humanities. It will not change the fundamental methods of historical enquiry but will complement them. Existing historical research will become more thoroughly integrated with many areas of the social sciences and attract more resources. On the other hand, it will be mostly bad news for theories.

Few theories will survive unscathed. But that is a desirable situation scientifically. What is undesirable is to try to smother the latest prodigies of science before they are old enough to speak or loud enough to be heard.

Harvey Whitehouse and Pieter Francois are both at the University of Oxford, and (together with Peter Turchin) are Seshat Databank Founding Directors

Our recent article in Nature, Complex societies precede moralizing gods throughout world history has been generally very well received, but this week we got slammed with two critical articles, both published as preprints on PsyArchive. It will take us some time to carefully evaluate these claims and publish responses in academic journals. A response to Beheim et al. on analysis issues is in the works, but on my blog I am going to focus more on the criticisms of the Seshat data in Historians Respond to Whitehouse et al. (2019), “Complex Societies Precede Moralizing Gods Throughout World History”. The first author of this piece is Prof. Slingerland who is the head of the Database of Religious History (DRH), a rival project to Seshat. His co-authors are also associated with the DRH.

One particular issue that they discuss at length is, when did moralizing gods appear in Chinese history? This is an important case study, because it is often used by the proponents of the Big God theory to support their claims (for example, see Section 3.2.2 in The cultural evolution of prosocial religions).

The data coded in Seshat, which we analyzed in the Nature article, suggest that moralizing high gods appear in North China around 1000 BCE during the Western Zhou period (c.1040–771 BCE). First truly large-scale societies in North China appeared roughly half a millennium earlier. During the Erligang period (1650–1250 BCE) the population of the Early Shang polity was at least 1 million, and likely more. The Shang capital city was huge, sprawling over 2500 ha with a population numbering in the hundreds of thousands. In other words, the North China sequence – first large-scale societies, then moralizing gods – supports the general conclusions of the Nature article.

Here’s what Prof. Slingerland and his colleagues have to say on this issue:

These coding errors undermine the analysis presented in Whitehouse et al. (2019). For instance, a crucial datapoint for Whitehouse et al. (2019), a supposed instance of a Natural Geographic Area (NGA) that possessed writing before a moralizing high god, is the Middle Yellow River Valley (MYVR). This is because the Late Shang polity was coded as lacking a moralizing god, based on a citation from Robert Eno, an expert on the area. Eno’s opinion, however, is in the minority in the field, as anyone familiar with the literature would know. A look at expert-generated, pre-coded data from the DRH shows that Eno’s view (https://religiondatabase.org/browse/299/#/) is contradicted by the other two entries on the Shang, by the eminent scholars David Keightley (https://religiondatabase.org/browse/23/#/) and Lothar von Falkenhausen (https://religiondatabase.org/browse/187/#/). Re-coding this variable as 1 (based on majority opinion) or weighting it as .66 would seriously undermine Whitehouse et al.’s conclusion.

This paragraph is a good example of the strident, self-righteous tone permeating Prof. Slingerland’s critique. Wherever there is a difference between a Seshat code and a DRH code, the professor counts it as a Seshat error. But is this conclusion justified?

In the Early Shang/Erligang period (1650–1250 BCE), archaeologists find bone fragments and ceramic jars with inscribed characters, but no records that could tell us about the specific tenets of religious practices in this period. Records become abundant during the late Shang (1250–1045 BCE). Most of what is known of Shang’s religion is written on 107,000 “oracle” bones.

Di, the High God of the Shang, was the god of rain, snow, hail, wind, thunder, and disasters. According to Robert Eno’s translations of Shang oracle bones, Di could summon natural phenomena to ruin harvests or call lightning, but also could support or ruin political and military endeavors. The Shang king acted as an intermediary to appease or influence Di through the correct ritual sacrifices. Eno concludes there is no evidence in the oracle bone records for Di as a moralizing force: “Nowhere in the texts do we see clear indication that the Powers are beneficent …. The Shang rulers seek advance approval for their actions – sometimes, it seems, obsessively – but there is no suggestion that the basis for approval will be anything other than the arbitrary inclinations of the Powers” (Eno 2009: 100).

The introduction of the concept of Tian (Heaven) in Western Zhou inscriptions has prompted scholars, such as archaeologist Li Feng, to question the nature of religious continuity between the Late Shang and Western Zhou. The doctrine of the Mandate of Heaven became a central concept in the Western Zhou, making a significant change in the Chinese religious landscape. Evidence from the Western Zhou on the Mandate of Heaven is sparse. Robert Eno points to a 998 BCE Western Zhou inscription that quotes a ruler named King Kang claiming the Shang had lost the Mandate of Heaven because of its king’s acceptance of poor behavior like drunkenness and overall bad governance.

To summarize: we have plenty of evidence from the Late Shang period about horrifying and capricious deities, who exhibit a complete lack of concern for human moral behavior, and instead need to be placated by sacrifices and rituals. David Keightley provides numerous examples of such, distinctly not moralizing, behavior in the Shang inscriptions. The first signs of a moralizing high god appear only during the Western Zhou period. So why did the DRH experts coded it differently?

Let’s look into the DRH data coded by Prof. von Falkenhausen. For China, 1750–850 BCE, the DRH asks, is there supernatural monitoring of prosocial norm adherence?  The answer by the expert is “yes.”  It would be interesting to know what Prof. von Falkenhausen thinks about the Shang-Zhou transition, but all we have is a “yes”. This is quite different from the Seshat record, which provides a paragraph explaining the basis of the code (“no” for Late Shang and “yes” for Western Zhou) and gives an academic reference for the change.

Furthermore, we might ask, what is the basis for coding “yes” for the whole period, 1750–850 BCE. During this period, nearly a millennium, the society and polity of North China was utterly transformed. It seems foolhardy to code it as one period. In contrast, Seshat not only breaks up this millennium in four phases, but also allows us to capture any changes within a phase by attaching such a change to a date. Furthermore, 1750 BCE falls into the Erlitou period (1850–1600 BCE) for which there are no records that could throw light on Erlitou religion. One wonders, what is the evidential basis for the code in this early period. Unfortunately, “yes” for 1750–850 BCE as a whole is all we have.

I want to emphasize that the preceding is in no way a criticism of Prof. von Falkenhausen, who is an excellent and broadly respected archaeologist of Ancient China. This strange coding – indeed, one could use Prof. Slingerland’s term and refer to it as a “coding error” – is, rather, a failure of the DRH.

Now, unlike Prof. Slingerland and his DRH, we at the Seshat project make no claim that we know the ultimate truth. All data codes in Seshat are subject to change as new or additional evidence is brought to bear. But in this particular case I see no reason why Seshat codes for the Shang and Western Zhou periods need to be adjusted.

In this blog post I delved into just one, although important, example from the critique leveled at us by Prof. Slingerland and his co-authors. But more broadly their critique is full of gross misrepresentations, simple misunderstandings, and false charges. We are currently writing a scholarly response to it, which will eventually be published in the Journal of Cognitive History. In our response we will demonstrate that Seshat is the most reliable source of data ever created to test cultural evolutionary hypotheses using world history.