After a long and turbulent history, the study of human cultural evolution is finally becoming comparable to the study of genetic evolution, with human history the counterpart of the biological fossil record. One of the most remarkable products of cultural evolution has been an increase in the scale of human societies by many orders of magnitude, which can be called human ultrasociality. Human ultrasociality has evolved repeatedly around the world and across time, reflecting both common selection pressures and the unique contingencies affecting each case. An enormous amount of historical information exists but has not been studied from an evolutionary perspective. The purpose of this initiative is to create a database for the cultural evolution of human ultrasociality that explicitly adopts the methods of phylogenetic analysis developed for the study of genetic evolution. The database will bring together, in a systematic form, what is currently known about the sociopolitical organization of complex human societies. It will be used (by us and many others) in analyses to determine how characteristics of large-scale organization vary with culture, institutions, world region and historical period, and whether there are any universal features that all complex societies share. It will also enable us to test a variety of theories about the selective forces that shaped the cultural evolution of large-scale societies. Finally, the database will be highly relevant for addressing the challenges of large-scale cooperation and conflict in the modern world.
The great majority of humans today live in large-scale complex societies, which can exist only on the basis of extensive cooperation among large numbers of individuals. Such cooperation can take many forms: volunteering for the army when the country is attacked, willingly paying taxes, voting, helping strangers, refusing to take bribes, etc. In each case, the result of cooperation is production of a public good (that is, no one can be effectively excluded from using the good), while the costs of cooperation are born privately (for example, one can be killed defending the country). Ultrasociality, the ability of humans to cooperate in huge groups of genetically unrelated individuals (Campbell 1983) presents a great puzzle to both evolutionary and social theories (Richerson and Boyd 1998). We now understand that neither the “selfish gene” perspective (Dawkins 1976), nor rational choice theory (Becker 1978) is capable of resolving this puzzle (Turchin 2006: Chapter 5).
Human ultrasociality is a major evolutionary transition. Other transitions include those from independent replicators to chromosomes, from a procaryotic to a eucaryotic cell, from unicellular to multicellular organisms, and from solitary individuals to eusocial colonies (Maynard Smith and Szathmáry 1995). A powerful conceptual framework for understanding major transitions is the multilevel selection theory (Sober and Wilson 1991, Okasha 2007, Wilson and Wilson 2007). Generally speaking, major transitions involve several interacting processes: evolution of cooperation among lower-level units (“particles”), selection acting on higher-level “collectives,” policing mechanisms suppressing “free riders” and competition among lower-level units, and increased functional integration of collectives, making them increasingly organism-like. Eventually higher-level collectives become so well integrated that they can be treated as “individuals” in their own right (and can serve as lower-level units for the next evolutionary transition).
Evolution of human ultrasociality fits quite well into this scheme, but with one important twist: it occurred in two stages (so, perhaps it is best to think of two transitions instead of one). The first stage was the evolution of cooperation in small-scale groups (hundreds or, at most, a few thousand of people). Our theories of how small-scale sociality evolved in humans are rapidly maturing (Sober and Wilson 1991, Wilson 2002, Boyd and Richerson 1985, Richerson and Boyd 1998, 2005, Bowles 2006, Choi and Bowles 2007, Turchin 2006, Lehmann and Feldman 2008). The mechanisms involved were (a) warfare, which intensified between-group selection; (b) inequity aversion and other levelling mechanisms (food sharing, monogyny, social control of “upstarts”), which reduced within-group variation in fitness and, thus, the strength of individual-level selection; (c) moralistic punishment, which suppressed free-riding, and (d) culture, which (via conformist transmission) reduced within-group variability and enhanced between-group variability. Evolution of small-scale sociality operated in both genetic and cultural modes; in fact, the key process was gene-culture coevolution (Richerson and Boyd 2005). Because cooperation in small-scale societies relies on face-to-face interactions it required large brains to store and process social interactions data (Byrne and Whiten 1988). However, once a human group attains the size of 100–200 individuals (Dunbar 1992, Dunbar and Shultz 2007), even the hypertrophied human brain becomes overwhelmed with the complexity of social computation. Thus, in order for group size to increase beyond the few hundred individuals typical of small-scale human societies, evolution had to break through the barriers imposed by face-to-face sociality.
The second stage, evolution of large-scale ultrasociality, was enabled by several additional key adaptations. First, humans evolved the capacity to demarcate group membership with symbolic markers (Shaw and Wong 1989, Masters 1998, Richerson and Boyd 1998). Markers such as language and dialect, religion, clothing, and ornamentation allowed humans to determine whether someone personally unknown to them was a member of their cooperating group or, vice versa, an alien and an enemy. Another evolutionary innovation was hierarchical organization that allowed unlimited growth in the scale of cooperating groups, simply by adding extra organization levels. Centralized hierarchies are also much more effective in war, which is why all armies have chains of command (Andreski 1971). However, the downside of hierarchical social organization is that it inevitably leads to inequality (Mosca 1939, Michels 1915). As a result, evolution of complex societies reversed the trend to greater egalitarianism that had previously characterized human evolution. Other key innovations during the second stage include literacy and record keeping, formal legal systems, bureaucracies, organized religion, urbanization, and states. The primary mode of evolution was clearly cultural, although recent analyses indicate that genetic evolution did not cease with the rise of civilization (Hawks et al. 2007).
Cultural evolution has had a turbulent history and it remains a highly controversial field. Even the nature of cultural variation is in contention, with rival approaches (evolutionary psychology, memetics, the dual inheritance theory, etc) each offering a variant view. Nevertheless, the study of human cultural evolution is gradually becoming comparable to the study of genetic evolution, as evidenced, for example, by the successful deployment of the methods of phylogenetic analysis (Mace and Holden 2005, Fortunato and Mace 2009). Evolutionary theory, thus, provides a powerful framework for the study of human ultrasociality. It can serve as a unifying conceptual framework for the multitude of theories proposed by political thinkers, anthropologists, and social biologists to explain how complex societies and, in particular, states evolved (for reviews, see Mann 1986, Chase-Dunn and Hall 1997, Sanderson 1999, Grinin and Korotayev 2009). These theories invoke a variety of mechanisms: warfare, population pressure, class struggle, economic exchange, and large-scale irrigation works. I recently added to this growing theoretical corpus a model based on a central mathematical result in multilevel-selection theory, the Price equation (Price 1972), which proposed that evolution of prosocial traits is favored not only when group-level selection is strong, but also, and most importantly, when between-group variability is maximized (Turchin 2009, 2010, Turchin and Gavrilets 2009).
So far the theories have not been confronted with data in a systematic way, a procedure that would allow us to reject some in favor of others. The main stumbling block has been a lack of good databases codifying information on cultural variation in a broad spectrum of societies. As a result, previous empirical tests have been ad hoc and haphazard, tending to focus on those aspects and regions with which individual authors were familiar. To make further progress we need to start testing theories, and that requires a much better empirical base than we currently have.
We propose to construct such a database that would bring together, in a systematic form, what is currently known about the social and political organization of large-scale human societies. We will then use this database to perform a first-cut test of the theories of evolution of large-scale sociality. However, the value of the database will be much greater than could be exploited by a single group of researchers. As experience in both social and natural sciences shows, a well-constructed database often provides a precipitation nucleus for a self-organizing community of scholars who continue enriching the database and come up with novel ways of using the data.
For all of its focal topics, the EI has developed an innovative three-tier population structure for intellectual interactions. The Community of Interest (COI) includes any qualified scholar who wants to become involved. The core advisory group is drawn from the COI and includes members who have committed to making a serious contribution to the project. The group that physically meets is drawn from the core advisory group and can rotate membership between meetings. This three-tier structure has a number of advantages, and meshes naturally with NESCent’s working group approach. The broadest group creates an audience for the project that can grow as large as needed and allows active participation on a voluntary basis. The middle-level group creates a committed core that is not restrained by limitations of a physical meeting. The smallest subset that participates in actual meetings benefits from the advantages of face-to-face interactions. In this fashion, the physical meetings become nodes in a larger organized process. This organization also facilitates the creation of a diverse intellectual community, including young-career scholars, members of groups that are underrepresented in science, and those located in far-flung regions. Every person invited to join the core advisory group is asked to nominate colleagues who will contribute to its diversity.
The database should reflect political, miliary, social, economic, and ideological aspects of historical societies, as these are the variables that we will need to test the theories. The primary focus will be on historical states and empires, because we are interested in how large-scale complex societies evolved from simpler ones, and also because such societies are much better documented in the historical record. However, the database will be supplemented with the information on small-scale societies, extracted from such anthropological sources as the Human Relations Area Files (HRAF). Unlike HRAF, though, our database will be diachronic, which will allow us to explicitly test evolutionary (and, therefore, dynamic) theories.
The data will be entered in two ways. One is the comprehensive free-form text with linked tables, maps, and figures organized as a Wiki web resource. The second is a numerical distillation in a two-dimensional table (a comma-delimited file that can be read by any spreadsheet progam) modeled on the SCCS, where each row represents a particular polity and each column a particular variable.
Because the specialist knowledge on different regions and periods is widely dispersed among many institutions and individual historians, this project will eventually require large-scale cooperation among a very diverse group of researchers and an evolutionary approach. The particular approach adopted here is described below.
1. The first step is to establish a Web-based Wiki, based on Wikimedia software. The advantage of the Wiki approach is that it allows multiple experts to access the database, add data to it, and correct mistakes. The Wiki software keeps track of changes and allows users to discuss changes and achieve a concensus. Ability to write to the database will be password-protected to prevent frivolous or malicious use. The database structure will be text-based and flexible, so that new categories and subcategories can be easily added as a need for them arises.
2. Next, the database is ‘populated’ with easily obtainable data that can be simply lifted from the multitude of historical web sites (including those on Wikipedia). The initial seeding of the database will be accomplished by the posdoc (who will be hired in Summer of 2011) under the supervision of the PI (Turchin). Data entered at this stage will cover a limited number of regions, and will suffer from some errors and inaccuracies. This is not a problem in the long run, because such initial deficiencies will be corrected in later rounds. This is the evolutionary aspect of the proposed approach (it is important to remember that any large database will contain errors; the primary goal is to reduce their incidence as much as possible – complete elimination is not a realistic possibility).
3. Additionally, the initial coding of certain polities will be accomplished by specialist historians. All efforts will be made to recruit as many of them as possible at the earliest stage. However, it would be a mistake to limit initial seeding of the database to specialists. It is much easier to induce busy people to correct an occassional mistake, rather than code data ‘from scratch.’ Also, there is no sharp boundary between a specialist and a non-specialist. Several knowledgeable nonspecialists, profiting from the ‘wisdom of the crowds,’ may be as good, and perhaps even better, than a single specialist.
4. After the initial seeding, we will recruit as many specialist historians as possible to go over the data correcting the mistakes and filling in the gaps. This recruiting will take place through personal connections, announcements at professional conferences and journals, and at appropriate web sites.
5. Once the database reaches the ‘critical mass,’ it is expected that the process of adding data and correcting errors will become self-sustaining.
The main product will be the database that will be accessible free of charge. Writing to the database will be password protected. Any bona fide researchers willing to contribute to the expansion and correction of the database will be offered to join the COI. The database will be such a significant resource that we also anticipate a number of publications in high-profile journals.
In the long term, a general database to assess and refine theories will inevitably have policy implications. As a more robust theory of state formation (or, in more general terms, of organizational forms of large-scale social integration) is developed and tested with cross-cultural data, we will obtain a much better toolkit for answering such questions as, how do we fix failed states? How can we end civil wars and evolve political structures for nonviolent methods of resolving conflicts? How can we promote integration at the global level and stop interstate wars?
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