Reviewed by
Armando Geller
Scensei, Fairfax, VA
For some time now I have admired a slew of anthropological social simulation by say Fischer (2008), Hoffer (2006) and Lansing (2009). With Calculating Chiefs, a book about modeling and simulating the logic of leadership writ large in Oceania, Stephen Younger has added another piece to this library. I highly suggest Calculating Chiefs to anyone interested in building evidence-based multi-agent models and simulations of social systems. (Those interested in alternatives to regressions in conflict research will enjoy it too.) Younger processes an impressive amount of empirical data, both breadth and depth, framing the book around two themes: Finding clues in the institution of chiefdom to the evolution of modern polity and facilitating a conversation between observational anthropology and computer simulation. In my review of Calculating Chiefs I will be focusing on the social simulation theme. Earle (2012) has written a good review of the anthropological theme.Younger's work demonstrates the practicability and timeliness of the "complementary alternative" nature of social simulation. He plunges forward with messy qualitative data and abstracts the very same data into something with which he can work formally. While at first glance the cultural data in the book can be confusing, especially for the Oceania layman, the process of modelling organizes the data into a tightly knit ethnographic account of life, leadership and warfare in Oceania. The main contribution of the book, however, is formulating "residual questions" that cannot be answered empirically and addressing them by multi-agent modelling and simulation. "Filling these gaps might benefit from an organized interplay between observation and simulation". The results of this interplay are summarized in Table 10.2 where Younger lists his general research questions, presents anthropological evidence, formulates the "residual questions" for simulation, and presents the results of the simulation as a synthesis between real- and synthetic-world observations.
Younger's research provides interesting insight into the logic of leadership and violence in Oceania that are difficult to gain by using other methodologies. For example, he finds that violence increases with increasing population size due to social anonymization, not due to increasing population density. The empirical data available to Younger does not contradict this finding, but testing for the causal mechanisms underlying violence is close to impossible without using multi-agent social simulation. The same applies to other questions Younger studies: how leadership style influences the economic performance of a society (non-monotonically), whether the society forms a leader's leadership style or the leader's leadership style shapes the society (unidirectional influence from the leader onto the society) or the relationship between leadership, interpersonal violence and warfare (leadership exacerbates violence).
Despite its merits, the book is saddled with some weaknesses. From a didactic and modelling point of view I would have preferred the empirical part of the work knit more tightly to the modelling and simulation part. Younger does not introduce a meta-ontological principle or alternatives like "contexts" (Geller, Latek and Mussavi Rizi 2012) nor does he ensure exact correspondence between the data and the model (see for an example (Geller, Harrison and Revelle 2011). Therefore, the relations among empirical evidence, the model and simulation remain ambiguous. Younger uses drive, altruism, fighting ability and aggression to model leadership. These attributes intuitively make sense, but leave the reader wondering why not others. Not that such correspondence between a modeller's choice and the real-world can ever be established conclusively, but the rules defining correspondence between data and model should be made intelligible and reproducible.
My second criticism is aimed at the model's unifying power. Diverse situations as the islands in Micronesia, Polynesia and Melanesia compel Younger not to aim at "unification". However, his simple, stylized model leads to it. So instead of building a simple model, a body of models, simple or otherwise, could have been more truthful to the data, and arguably heuristically more insightful. With the amount of data available to Younger his model and simulation appear too simplistic and some of his conclusions, like comparing simulation results to specific islands, seem overly interpreted.
Yet, all in all Calculating Chiefs is an excellent book, because it is based on "good social science" (Edmonds and Moss 2005).
ReferencesEDMONDS, B. and S. Moss (2005). Towards Good Social Science. Journal of Artificial Societies and Social Simulation 8(4): https://www.jasss.org/8/4/13.html.
FISCHER, M. D. (2008). Cultural dynamics: formal descriptions of cultural processes. Structure and Dynamics: eJournal of Anthropological and Related Sciences 3(2): http://escholarship.org/uc/item/557126nz.
GELLER, A., J. F. Harrison and M. Revelle (2011). Growing Social Structure: An Empirical Multiagent Excursion into Kinship in Rural North-West Frontier Province. Structure and Dynamics: eJournal of Anthropological and Related Sciences, 5(1): http://www.escholarship.org/uc/item/4ww6x6gm.
GELLER, A., M. M. Latek and Seyed M. Mussavi Rizi (2012). Contexts as reasoning and action frames for multiagent societies. Paper presented at the 8th annual conference of the European Social Simulation Conference, 10-14 September 2012, Salzburg, Austria.
HOFFER, L. (2006). Junkie Business: The Evolution and Operation of a Heroin Dealing Network. Belmont, CA, Thomson/Wadsworth.
LANSING, J. S. (2009). A robust budding model of Balinese water temple networks. World Archeology 41(1): 110-131.
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