Cliodynamics is a transdisciplinary area of research integrating historical macrosociology, cultural and social evolution, economic history/cliometrics, mathematical modeling of long-term social processes, and the construction and analysis of historical databases. Cliodynamics: The Journal of Quantitative History and Cultural Evolution is an international, peer-reviewed, open-access journal that publishes original articles advancing the state of theoretical knowledge in this transdisciplinary area. In the broadest sense, this theoretical knowledge includes general principles that explain the functioning, dynamics, and evolution of historical societies and specific models, usually formulated as mathematical equations or computer algorithms. Cliodynamics also has empirical content that deals with discovering general historical patterns, determining empirical adequacy of key assumptions made by models, and testing theoretical predictions with data from actual historical societies. A mature, or ‘developed theory’ thus integrates models with data; the main goal of Cliodynamics is to facilitate progress towards such theory in history and cultural evolution.
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Volume 9, Issue 2, 2018
The article suggests that the Great Divergence of the 19th century between “the West” and “the East” was preceded by the Great Divergence in the 18th century between the Global North and the Global South. This may be attributed to a new, much higher level of state efficiency in the Global North. The eastern and western regions of the Global North frequently used different methods to make their state apparatuses more efficient, but achieved strikingly similar results during the 18th century. The Great Divergence of the 19th century, remarkably, occurred within the Global North.
We adopt an imagined exchequer, the functionary responsible in an early polity for securing resources from its agrarian subjects, and we develop a feature-rich demographic and environmental model to explore the population ecology of agricultural production in the context of population growth, Malthusian constraints and economic exploitation. The model system allows us to (i) identify and characterize a peak of surplus production early in population growth, prior to density-dependent constraints and (ii) characterize the taxation potential of a population at its Malthusian equilibrium. For a fixed total level of taxation the exchequer has two options: a small population taxed at a high rate, unstable to small perturbations, or a larger population taxed at a lower rate, which is stable. In a small and growing population it is more effective to tax goods; as the population approaches its density-dependent equilibrium it becomes more effective to tax labor. We likewise show that early agrarian states afflicted by stochastic variation in agronomic output face an extinction risk dependent on the level of taxation and magnitude of yield variation. Successful agrarian states balanced resource exploitation against dynamic population ecology constraints; we propose that fiscal mismanagement should be among the hypotheses for polity failure.
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The Governance and Leadership of Prehispanic Mesoamerican Polities: New Perspectives and Comparative Implications
The principal conceptual axes for explaining variation in prehispanic Mesoamerican political organization (states and empires) have shifted over time. Current perspectives build on and extend beyond the important dimensions of scale and hierarchical complexity and have begun to probe the nature of leadership and governance, drawing on collective action theory and incorporating recent findings that challenge long-held statist vantages on preindustrial economies. Recent results from and archaeological correlates for the application of this approach are outlined, offering opportunities for more comparative analyses of variation and change in the practice of governance within prehispanic Mesoamerican world and more globally.
The Extended Evolutionary Synthesis (EES) is beginning to fulfill the whole promise of Darwinian insight through its extension of evolutionary understanding from the biological domain to include cultural information evolution. This constitutes the origins of an evolutionary study of culture change free of the social-darwinism and ecologically-deterministic baggage that characterized earlier such approaches.
Recent years have seen major political crises throughout the world, and foreign policy analysts nearly universally expect to see rising tensions within (and between) countries in the next 5–20 years. Being able to predict future crises and to assess the resilience of different countries to various shocks is of foremost importance in averting the potentially huge human costs of state collapse and civil war. The premise of this paper is that a transdisciplinary approach to forecasting social breakdown, recovery, and resilience is entirely feasible, as a result of recent breakthroughs in statistical analysis of large-scale historical data, the qualitative insights of historical and semiotic investigations, and agent-based models that translate between micro-dynamics of interacting individuals and the collective macro-level events emerging from these interactions. Our goal is to construct a series of probabilistic scenarios of social breakdown and recovery, based on historical crises and outcomes, which can aid the analysis of potential outcomes of future crises. We call this approach—similar in spirit to ensemble forecasting in weather prediction—multipath forecasting (MPF). This paper aims to set out the methodological premises and basic stages envisaged to realize this goal within a transdisciplinary research collaboration: first, the statistical analysis of a massive database of past instances of crisis to determine how actual outcomes (the severity of disruption and violence, the speed of resolution) depend on inputs (economic, political, and cultural factors); second, the encoding of these analytical insights into probabilistic, empirically informed computational models of societal breakdown and recovery—the MPF engine; third, testing the MPF engine to “predict” the trajectories and outcomes of another set of past social upheavals, which were not used in building the model. This “historical retrodiction” is an innovation that will allow us to further refine the MPF technology. Ultimately our vision is to use MPF to help write what we call “a history of possible futures,” in which the near- and medium-term paths of societies are probabilistically forecast.