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A Complex Systems Study of Social Hierarchies and Jurisprudence
Abstract
Humanity's understanding of complex societal phenomena is still in its infancy, and there is much to discover about the organizing principles governing social life on Earth. How do societal structures such as social hierarchies form, and under what conditions do these structures remain stable versus become unstable and collapse? What is the structure of the jurisprudence that regulates modern human societies and how does it evolve in time? In this thesis, I apply quantitative analysis and modeling approaches from physics and network science to investigate these questions.
In Part I, I develop simple models of the formation and stability of social hierarchies and compare their results to interaction data from animal societies and proxy data from human societies. The models are based on pairwise interactions between randomly-selected individuals that result in exchanges of societal "status." Following many interactions, a distribution of status forms, the shape of which ranges from egalitarian (many individuals with near average status) to very unequal (many low status individuals and a few high status individuals), depending on the model parameters. An Arrhenius relationship between a characteristic time controlling the evolution of the status distribution and the model parameters quantifies "long-lived" status distributions which appear to be stable in time, but in fact are not.
In Part II, I analyze citation networks of court decisions (judgments) in the areas of family, bankruptcy, and defamation law, using unique datasets covering all levels of the Canadian court hierarchy (trial, appellate, and Supreme Court of Canada). In each network, judgments are "nodes" and judges' citations of past decisions are directed "links" between nodes. Despite the legal differences between the three areas of law, many large-scale network properties are similar. However, one can use refined network tools (clustering methods) to draw out differences in the datasets and interpret them in relation to legal developments (landmark judgments and important legislation) in the specific areas of law. This leads to an in-depth examination of the influence of landmark judgments and statutory changes on the explosion in family litigation that occurred in Canada in the 1990s.
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We introduce the revised version of the KOF Globalisation Index, a composite index measuring globalization for every country in the world along the economic, social and political dimension. The original index was introduced by Dreher (Applied Economics, 38(10):1091–1110, 2006) and updated in Dreher et al. (2008). This second revision of the index distinguishes between de facto and de jure measures along the different dimensions of globalization. We also disentangle trade and financial globalization within the economic dimension of globalization and use time-varying weighting of the variables. The new index is based on 43 instead of 23 variables in the previous version. Following Dreher (Applied Economics, 38(10):1091–1110, 2006), we use the new index to examine the effect of globalization on economic growth. The results suggest that de facto and de jure globalization influence economic growth differently. Future research should use the new KOF Globalisation Index to re-examine other important consequences of globalization and why globalization was proceeding rapidly in some countries, such as South Korea, but less so in others. The KOF Globalisation Index can be downloaded from http://www.kof.ethz.ch/globalisation/.
A central claim in modern network science is that real-world networks are typically "scale free," meaning that the fraction of nodes with degree k follows a power law, decaying like , often with . However, empirical evidence for this belief derives from a relatively small number of real-world networks. We test the universality of scale-free structure by applying state-of-the-art statistical tools to a large corpus of nearly 1000 network data sets drawn from social, biological, technological, and informational sources. We fit the power-law model to each degree distribution, test its statistical plausibility, and compare it via a likelihood ratio test to alternative, non-scale-free models, e.g., the log-normal. Across domains, we find that scale-free networks are rare, with only 4% exhibiting the strongest-possible evidence of scale-free structure and 52% exhibiting the weakest-possible evidence. Furthermore, evidence of scale-free structure is not uniformly distributed across sources: social networks are at best weakly scale free, while a handful of technological and biological networks can be called strongly scale free. These results undermine the universality of scale-free networks and reveal that real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain.
One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.
The formation and stability of social hierarchies is a question of general relevance. Here, we propose a simple generalized theoretical model for establishing social hierarchy via pair-wise interactions between individuals and investigate its stability. In each interaction or fight, the probability of “winning” depends solely on the relative societal status of the participants, and the winner has a gain of status whereas there is an equal loss to the loser. The interactions are characterized by two parameters. The first parameter represents how much can be lost, and the second parameter represents the degree to which even a small difference of status can guarantee a win for the higher-status individual. Depending on the parameters, the resulting status distributions reach either a continuous unimodal form or lead to a totalitarian end state with one high-status individual and all other individuals having status approaching zero. However, we find that in the latter case long-lived intermediary distributions often exist, which can give the illusion of a stable society. As we show, our model allows us to make predictions consistent with animal interaction data and their evolution over a number of years. Moreover, by implementing a simple, but realistic rule that restricts interactions to sufficiently similar-status individuals, the stable or long-lived distributions acquire high-status structure corresponding to a distinct high-status class. Using household income as a proxy for societal status in human societies, we find agreement over their entire range from the low-to-middle-status parts to the characteristic high-status “tail”. We discuss how the model provides a conceptual framework for understanding the origin of social hierarchy and the factors which lead to the preservation or deterioration of the societal structure.
We study the effect of a 2006 reform to Italian family law that made joint custody the default for separating couples. The reform boosted joint legal custody by about 75 percentage points. Our research design uses difference‐in‐differences to estimate reform effects on the likelihood of a contested settlement, length of trial, and transfers between separating parents. The analysis is based on Italian individual‐level administrative data, which cover the entire population. The joint custody default appears to have increased dispute rates and length of trial markedly, without affecting transfers. There is no evidence that mothers buy custody rights back through reduced support. Our findings are consistent with the excessive discretion given to judges on some aspects of law implementation, which resulted in a partial application of the reform.
Why are some opinions widely discussed while others remain obscure? We theorize that opinions that can be understood efficiently are discussed, expanded, and contracted more frequently. Additionally, more persuasive precedents tend to be discussed and expanded more regularly, while less persuasive precedents are narrowed more often. These effects should also depend on institutional context. We compile an original dataset of 7,485 search and seizure opinions written by federal circuit and state high court judges and 567,062 judicial citations to those cases. The evidence demonstrates that efficiency, persuasiveness, and institutional context together determine how much an opinion affects legal development.
Inequality and the concentration of wealth is a worsening problem in the world. In this paper, we will derive a system of equations that describes the evolution of wealth in large-scale economies. This model leads to the formation of two classes: a normal population and the extremely wealthy, called the oligarchy. The mathematical object representing oligarchy is strange, and appears to exist most naturally as a nonstandard function. After describing the model we define the oligarchy mathematically, showing how its existence fundamentally alters the dynamics of the economy, diminishing the wealth available to the normal population and promoting inequality.