Authors: Harvey Whitehouse (1), Pieter François (1,2), and Peter Turchin (1, 3)
(1 University of Oxford; 2 University of Hertfordshire; 3 University of Connecticut)
In his “Reflections on the French Revolution,” the great Anglo-Irish statesman and philosopher Edmund Burke declared: “In history a great volume is unrolled for our instruction, drawing the materials of future wisdom from the past errors and infirmities of mankind.” But since the 18th century when Burke penned these lines, the “great volume” to which he referred has grown so vast through the accumulated discoveries and writings of historians, classicists, archaeologists and others that “unrolling” it has become practically unthinkable. Until now…
The process of inferring general patterns in human history has usually meant cunningly plucking out facts to fit your argument—for instance ‘cherry picking’ historical events to lend credence to your judgments about the ‘errors’ of the past and your favoured ‘prescriptions’ for the future. However flawed this methodology, alternative options were limited. Anybody seeking to use our accumulated experience of the past to predict likely patterns of history-making in the future has been limited by how much knowledge they could personally command, given the difficulties of accessing information, the limitations of brains (especially memory and processing power), and the shortness of scholars’ lifespans. To overcome these very human frailties, what has long been needed is a computerized database of global history in which patterns of correlations across space and time between variables of interest could be reliably tracked using statistical tools. Seshat: Global History Databank, a vast collection of information gleaned from the work of scholars who study the human past, will provide a new way of addressing this challenge.
Seshat builds upon and radically expands a number of more established initiatives, including the Human Relation Area Files (HRAF) and the Standard Cross-Cultural Sample (SCCS). The crucial added value of Seshat is its longitudinal depth. Pre-existing databases are too historically shallow to understand long-term persistence and trend reversals, but Seshat will provide dynamic data revealing how different aspects of societies change with time. Our work also builds upon earlier efforts to construct and analyse more modest datasets using ethnographic material derived from both HRAF and the SCCS (Atkinson and Whitehouse 2011) and independently assembled archaeological materials (Whitehouse et al. 2013).
We started working together on this massive undertaking about five years ago. By the end of 2015, with the help of many colleagues who have joined forces with us along the way and the generous support of several funding bodies, we will have coded information pertaining to over 500 political systems (or ‘polities’) in 30 ‘natural geographic areas’ (or ‘NGAs’). We call them NGAs because they each cover a geo-ecological zone that has retained its distinctive character over the millennia, even while the scale and structure of human social systems have changed, often quite dramatically. Our NGAs were selected to cover as broad a range as possible of social, cultural, political, and economic variation in world history selected from Africa, Europe, the Pacific, the Americas, and all the major regions of Asia. For each world region, we selected NGAs capable of furnishing examples of polities at all levels of sociocultural complexity (categorized as ‘low,’ ‘medium,’ or ‘high’). Some NGAs yielded polities with richly documented histories, and, taken together, these polities span very long time periods. Other NGAs had much shallower histories and offered thus a smaller number of polities. Overall, however, this sampling approach provided us with a rich slice of variability in human history (see Table 1). For each of the many hundreds of polities included in Seshat, we have been coding for a great range of variables pertaining to social complexity, warfare, ritual, governance, law, stratification, social mobility, religion, quality of life, economy, technology, agriculture, and demography. At the time of writing, we have about 78,000 data points already coded, and, by the end of the year, we expect this to have risen to around 100,000. Coding our initial sample of 30 NGAs is only the starting point, however; by 2025, we expect to hit our target of 100 NGAs, allowing us to test a great variety of hypotheses about the history of humankind and laying the groundwork for others to follow suit when the database ‘goes public.’
World Region
Low Complexity
Medium Complexity
High Complexity
Africa
Ghanaian Coast
Niger Inland Delta
Upper Egypt
Europe
Iceland
Paris Basin
Latium
Central Eurasia
Lena River Valley
Orkhon Valley
Sogdiana
Southwest Asia
Yemeni Coastal Plain
Konya Plain
Susiana
South Asia
Garo Hills
Deccan
Kachi Plain
Southeast Asia
Kapuasi Basin
Central Java
Cambodian Basin
East Asia
Southern China Hills
Kansai
Middle Yellow River Valley
North America
Finger Lakes
Cahokia
Valley of Oaxaca
South America
Lowland Andes
North Colombia
Cuzco
Oceania-Australia
Oro PNG
Chuuk Islands
Big Island Hawaii
Table 1: The World Sample of 30 NGAs (Turchin et al. 2015)
As well as enabling us to avoid the charge of cherry-picking examples to fit our arguments, Seshat will allow us to test predictions formulated before we compiled the database, paving the way for a scientific approach to learning from history. Here, we set out five predictions concerning the relationship between ritual and various wider features of society. For each of these predictions, we provide a rationale or motivation based on the theory of ‘Divergent Modes of Religiosity’ (hereafter DMR theory). When the first phase of data assembly is completed early in 2016, we will begin the process of testing these predictions statistically using our world sample of 30 NGAs.
Five Predictions
DMR theory posits two clusters of features pertaining to collective ritual and social morphology in the world’s religious traditions (Whitehouse 1995, 2000, 2004, 2012). One cluster—the imagistic mode of religiosity—is characterized by low-frequency (i.e., rarely performed), high-arousal (typically painful or frightening) rituals and small but intensely cohesive communities. The other cluster—the doctrinal mode of religiosity—is characterized by high-frequency (i.e., routinized) low-arousal (often tedious and repetitive) rituals and large-scale, hierarchical, but more diffusely cohesive communities. The imagistic mode is thought to be adaptive for groups that need to stick together in the face of strong temptations to defect—for example, when engaging enemies on the battlefield or large prey on the hunting ground. The doctrinal mode is thought to be adaptive for groups seeking to pool small amounts of resource from individuals in a much larger population so as to create a large, centralised resource in the form of charitable donations, legacies, tax or tribute – for example, when competing coalitions are organized via categorical ties of caste, race, ethnicity, or belief. These contrasting patterns of ritual and group formation have been studied in a few select religious groups both past and present (e.g., Whitehouse & Laidlaw 2004; Whitehouse and Martin 2004; Whitehouse and McCauley 2005), as well as in military groups that may or may not subscribe to beliefs in supernatural agents or forces (e.g., Whitehouse and McQuinn 2012; Whitehouse 2013). In addition to analysis of case study material from social-cultural anthropology, history, and archaeology, evidence that imagistic and doctrinal modes constitute universal features of group formation comes from the analysis of approximately 100 variables pertaining to 645 rituals from 74 cultures (Atkinson and Whitehouse 2011). This early database, allowing synchronic comparison, generated a number of predictions that will be testable using a longitudinal dataset such as Seshat.
For each polity coded in Seshat, we record details for five kinds of rituals: the largest scale, the most widespread, the most frequent, the most euphoric, and the most dysphoric. For each of these five rituals, we assemble information on the frequency, duration, scale, and inclusiveness of performances along with evidence of the quality and intensity of the emotions evoked through participation. This information is gathered through direct input from domain experts and through extensive literature reviews conducted by research assistants. As such, the data reflect the most recent scholarly understanding of ritualistic behaviour for each of the polities. Because Seshat also contains extensive information on social complexity, warfare, agricultural intensity, and other variables of relevance to DMR theory, we will be able to test a wide variety of hypotheses concerning the evolution of doctrinal and imagistic modes over time. Here, we lay out five initial predictions to be tested using Seshat. We also provide an alternative to each of our predictions together with competing rationales (Table 2).
Prediction
Explanation
Alternative
1. Dysphoric rituals correlate with small-scale armed groups, intra-elite conflicts, military revolts, and separatist rebellions
Dysphoric rituals lead to local fusion and willingness to fight and die for the relational group—thus increasing the incidence of small-scale intergroup conflict, revolt, or revolution.
Dysphoric rituals have no effect or a negative effect on the incidence of intergroup conflict, revolt, or revolution.
2. Intensification of agriculture leads to routinization and orthopraxy
Agricultural intensification increases the frequency and scale of cooperative activity and, therefore, leads to ritual routinization and standardization
Routinization and orthopraxy are triggered by factors unrelated to agriculture (e.g., warfare, trade, status inequality, polarization of economic classes, etc.).
3. Routinized rituals enabled the emergence of larger polities
Routinized rituals are necessary for the first appearance of large-scale, anonymous, hierarchical, centralized communities. Thus, they appear before such large-scale polities.
Large-scale, anonymous, hierarchical, centralized communities arose first (e.g., due to warfare) and routinized rituals emerged subsequently to help maintain social cohesion.
4. Widespread orthopraxy makes polities more stable and long-lived
Widespread orthopraxy leads to shared identity and deference to a common authority so the more widespread and routinized the polity’s rituals are, the more stable and enduring its political system.
Widespread orthopraxy has no effect on or reduces the stability and longevity of the polity (e.g., because orthopraxy implies rigidity and risk of predation by more agile competitors).
5. Routinization & orthopraxy lead to the expansion of political dominion and trade
Because ritual routinization and standardization produce stable group identities that spread efficiently, they precede the expansion of political systems and trading networks.
Routinization and standardization obstruct assimilation, syncretism and cultural pluralism, inhibiting both political and commercial expansion.
Table 2: Five Predictions of DMR Theory
Prediction 1. Dysphoric rituals produce more tribal warfare, intra-elite conflicts, military revolts, and separatist rebellions.
For each polity coded in Seshat, we are collecting information on the most dysphoric (e.g., painful or frightening) ritual and details of the group(s) performing it. We predict that any tribes, elites, military organizations, or movements in the polity that have highly dysphoric rituals will be more prone to engaging in inter-group conflict than groups lacking such rituals. The logic of this prediction is that groups bound together by dysphoric rituals are more willing to fight and die to defend themselves against perceived external threats. Depending on the groups in question and the nature of the threats they face, we would expect intergroup conflict to take fairly typical forms such as civil war, sectarianism, rebellion, and revolution. The evidence supporting this prediction comes from real-world studies of the effects of shared dysphoria on group cohesion and willingness to fight and die for the group. Dysphoric experiences trigger enduring episodic memories that shape the personal self (Whitehouse 1992; Conway 1995). When such experiences are ritualized, they prompt elevated levels of reflection and meaning-making, increasing their transformative effect on the essential-self concept (Wilson and Ross 2003; Richert et al. 2005). Sharing such self-defining memories with others renders the boundary between self and group more porous, producing ‘identity fusion’—a form of extreme group cohesion associated with willingness to sacrifice self for the group (Swann et al. 2010; Swann et al. 2012). The effects of fusion on willingness to fight and die for the group has been studied empirically with revolutionaries in Libya (Whitehouse et al. 2014), war veterans who served in Vietnam, Afghanistan, and Iraq (Whitehouse et al., submitted), and participants in painful hazing rituals (ibid.). Together, these studies show that the effects of shared experience on fusion with the group is mediated by reflection on transformative dysphoric experiences and gives rise to extreme self-sacrifice in defence of the group’s interests (Whitehouse and Lanman 2014).
Prediction 2. Routinized rituals enabled the emergence of larger polities.
For each polity coded in Seshat, we will code details of the most frequently performed collective ritual supporting the prevailing power structure. It is a truism of social science research that rituals bolster the status quo, but it is only possible for rituals to serve this function if they enshrine a set of features common to the entire subject population. In order for a set of beliefs and practices to become standardized across large populations, however, they need to be enacted with sufficient regularity that everyone remembers their content and meaning in more or less the same way (Whitehouse 2000). When the frequency of complex cultural practices drops below a certain threshold, the tradition becomes prone to unauthorized innovation, giving rise to localized or regional offshoots and factions, undermining the unity of the tradition as a whole (Whitehouse 2004). Thus, in order to establish a large polity in the first place and to maintain it over time, the beliefs and practices of the population need to be homogenized through the process of routinization, typically in tandem with processes of centralized monitoring and control. Whereas local communities (e.g. tribes and villages) may be bonded through lower frequency rituals, ranging from annual festivals to rites of passage to once-in-a-generation events such as chiefly installation rites, state and world religions rely heavily on repetitive (e.g., daily or weekly) rituals to maintain their collective identities. We therefore predict the rise of ritual routinization prior to the appearance of large-scale political systems.
Prediction 3. Intensification of agriculture leads to routinization and orthopraxy.
One of the main drivers of routinization is thought to be the intensification of farming. In our survey of 74 cultural traditions and their rituals (Atkinson and Whitehouse 2011; see above), we established a strong negative correlation between ritual frequency and agricultural intensity. A possible explanation for this pattern is that as subsistence strategies become increasingly reliant on regularized forms of cooperation punctuated by collective ritual, polity-wide beliefs and practices become more standardized, stably uniting a wider and larger population. There is some evidence that these processes began in Western Asia with the Neolithic transition from foraging to farming. Over a period of nearly two thousand years, we have attempted to unpick the intricately entwined relationships between agricultural intensification, ritual frequency, and the standardization of communal identities (Whitehouse and Hodder 2010). We then constructed a database of Anatolian and Levantine sites from the end of the Palaeolithic through the beginning of the Bronze Age, showing a gradual shift from imagistic to doctrinal modes of group formation as the cultivation of crops and the domestication of animals emerged and slowly intensified (Whitehouse et al. 2013; see above). Eventually, Seshat will be able to link to databases of this kind so that we can compare the complex relationships between agriculture, ritual, and social morphology across multiple regions and time periods, potentially on a global scale.
Prediction 4. Widespread orthopraxy makes polities more stable and long-lived.
To the extent that routinization leads to the standardization of beliefs and practices and the emergence of centralized hierarchies responsible for maintaining adherence to the authorized canon, we would expect the resulting orthopraxy to inspire deference to the status quo and so contribute to the stability and endurance of the social order. Functionalist arguments of this kind, once enjoying almost hegemonic status in the social sciences (Parsons 1961), became a target for criticism in recent decades mainly on the grounds that not all societies are functionally integrated and stable—and even if some are, it is hard to explain how that functional integration came about (Barnard 2000). Some of these issues will be possible to address empirically for the first time using Seshat. Are certain features of rituals correlated with political stability over time, as we would predict? Are there conditions (e.g., pressures external to the polity) under which those same ritual features become dysfunctional (e.g., in inter-group competition)? DMR theory presents a series of sub-hypotheses regarding patterns of change in the relationship between routinized ritual, the ‘tedium effect,’ splintering, and reformation (Whitehouse 2004)—all of which lend themselves to empirical testing using the kind of longitudinal information that Seshat will provide (Turchin et al. 2012; Turchin et al. 2015; Francois et al. submitted).
Prediction 5. Routinization and orthopraxy lead to the expansion of political dominion and trade.
In addition to the possibility that the establishment of an orthopraxy might help to legitimate the power structure, we predict that it will facilitate the expansion of its dominions. As empires grow and expand into new territories, they must run the risk of losing sovereignty over distant outposts. Establishing a routinized ritual system can help to ensure the loyalty of subjects distant from the centres of control. But we hypothesize that it can also facilitate expansionary trading networks, allowing prospective partners to extend bonds of trust and cooperation based merely on exteriorized evidence of common belief and practice. In some cases, this trading advantage might consist mainly of a preference for ingroup over outgroup where a range of commercial partners is present. But it can run deeper still, where, for example, the religious system promotes particular ethical standards and associated sanctions or provides other assurances of the reputational standing of prospective associates in business.
And a Drum Roll
Making predictions is a scary business. The initial analysis of our first database of 645 rituals from 74 cultures (Atkinson and Whitehouse 2011) was accompanied by much anxious anticipation. Prior to it, there had been no shortage of scholars claiming to have shot down DMR theory on the grounds that they had found a low-frequency low-arousal ritual, or a high-frequency high-arousal one. Explaining that DMR theory was claiming to pick out statistical tendencies across space and time, not to explain every individual case, was often met with great affront as if one were claiming that the theory could not after all be empirically refuted. To be fair, it was more like claiming that the theory could not be tested on the evidence currently available. With the new rituals database, this changed for the first time. We were finally able to see whether rituals statistically clustered as predicted around imagistic and doctrinal ‘attractor positions.’ To our immense relief, they did. But this was only the beginning.
Not every prediction of DMR theory was capable of being tested by the Atkinson and Whitehouse database. In some cases, this was simply because we were unable to find compelling proxies for variables of interest. For example, levels of social cohesion were surprisingly difficult to measure using ethnographic sources. In other cases, the problem was simply that the rituals database was synchronic—we couldn’t test hypotheses about causation based on the assumption that causes usually precede effects. With Seshat, this will change.
Seshat will allow us to test hypotheses longitudinally for the first time—not only in one culture area or geographical region but across the entire globe, reaching as far back into the mists of times as historians and archaeologists have been able to go. The five predictions plucked out here for consideration will not be everyone’s cup of tea, but they will nevertheless allow us to demonstrate proof of concept. In the years to come, we will be able to test many more hypotheses with ever more precision, providing a whole new way of thinking about the human past. We will at last bring history under the purview of experimental science. Surely this is an act that deserves a drum roll?
Acknowledgements:
This work was supported by an ESRC Large Grant to the University of Oxford, entitled “Ritual, Community, and Conflict” (REF RES-060-25-0085), a John Templeton Foundation grant to the Evolution Institute, entitled “Axial-Age Religions and the Z-Curve of Human Egalitarianism,” a Tricoastal Foundation grant to the Evolution Institute, entitled “The Deep Roots of the Modern World: The Cultural Evolution of Economic Growth and Political Stability,” and a grant from the European Union Horizon 2020 research and innovation programme (grant agreement No 644055 [ALIGNED]). We gratefully acknowledge the contributions of our team of research assistants, post-doctoral researchers, consultants, and experts. Additionally, we have received invaluable assistance from our collaborators in the construction of Seshat. Please see the Seshat website for a comprehensive list of private donors, partners, experts, and consultants and their respective areas of expertise. We benefited from comments on an earlier draft of this paper from David Sloan Wilson.
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