Abstract
Since laws describe and theories explain, this chapter introduces the reader to generative theories of social complexity in CSS. The emphasis is on formal and empirically referenced theories, in some cases amenable to validation with real-world data, consistent with a computational approach. The chapter has three thrusts. The first is to provide the reader with proper foundations in elements of process analysis, Boolean logic, and elementary probability for compound events, as these ideas are applied to the statement and development of social complexity theories. This is done by highlighting useful parallels across formalisms and making use of mathematical isomorphisms. The second thrust of this chapter is to use these ideas as building blocks to examine theories of origins of social complexity. This is done by taking a closer look at how and why chiefdoms—and, later, states and empires—formed in the first cradles of civilization. Detailed analysis of these primary systems and processes is essential for understanding social complexity. The third thrust of the chapter is on general theories of social complexity, which encompass universal explanations of original, current, and future social complexity. The theoretical concepts, principles, and methods covered in this chapter constitute one of the most dynamic frontiers of CSS.
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Notes
- 1.
Charles A. Lave and James G. March explain the character of theories as causal “stories” in their social science classic, An Introduction to Models in the Social Sciences (1993).
- 2.
By convention, events are written in uppercase hollow letters (e.g., \(\mathbb {C}\)); variables are in uppercase italics (e.g., C). Event \(\mathbb {C}\) is defined on the sample space \(\varOmega \), variable C is defined on the set of values. Each realization of a variable constitutes an event; a variable is a set of realizations. These conceptual distinctions are critical for developing a unified theory linking macro and micro levels of analysis.
- 3.
The popular idiom according to which “nothing simply comes out of the blue” provides an apt description of so-called forward logic.
- 4.
Note the dichotomous taxonomy of events as either “decisional outcomes” or “states of nature.” The former are generated by human decisions, whereas the latter are produced by lotteries. “Inflation increases by 1.2 percent” is a state of nature, because it is not an event that is decided by anyone; so, its generative mechanism is called a lottery. “Humanitarian assistance will be provided to Kenya” is a decisional outcome generated by a human choice, not a product of any lottery.
- 5.
Hypoprobability has nothing to do with incomplete information. The effect emerges from the fundamental character of uncertainty as expressed by the sequential probability theorem. No amount of additional information or intelligence can narrow the gap between the probability of prior events and the sequential probability of a compound outcome.
- 6.
Advanced polities, such as democracies, also include intermediary structures (e.g., political parties, lobbying groups, labor unions) located between society and government. These are not required for explaining initial social complexity, so we examine them later.
- 7.
The term energetics is used in archaeology to demote the caloric budget of a community in terms of energy produced and consumed. For example, a community of a given size, producing so many surplus tons of barley per year, is able to build during so many days of the year. Conversely, when archaeological excavation reveals a given number of structures, the total energy necessary to construct them must be accounted for in terms of population available and food to sustain the required labor force.
- 8.
Hence the significance of the invention of agriculture and related technologies (e.g., official seals, measures, laws).
- 9.
A polity is said to be circumscribed when surrounding territories prevent migration in time of crisis. Circumscription may be caused by neighboring mountains (Peru’s Andean coastal region), deserts (Near East west of the Tigris–Euphrates basin), and similar obstacles.
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Cioffi-Revilla, C. (2017). Social Complexity III: Theories. In: Introduction to Computational Social Science. Texts in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-50131-4_7
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DOI: https://doi.org/10.1007/978-3-319-50131-4_7
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