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Emergence of complex institutions in a large population of self-governing communities


Frey, Seth (2019), Emergence of complex institutions in a large population of self-governing communities, UC Davis, Dataset,


Most aspects of our lives are governed by large, highly developed institutions that integrate several governance tasks under one authority structure. But theorists differ as to the mechanisms that drive the development of such concentrated governance systems from rudimentary beginnings. Is the emergence of regime consolidation a symptom of the runaway capture by opportunists? Or does integration occur because a consolidated institution is better adapted to a complex environment? Here we examine the emergence of complex governance regimes in 5,000 sovereign, resource-constrained, self-governing online communities, ranging in scale from zero to thousands of users. Each community begins with zero population and no governance infrastructure, and faces challenging resource problems as it grows. Consequently, they are subject to selection pressures that make it possible to test the hypothesis that governance complexity can enhance community fitness. We find that a successful community's rules are more numerous, broader in scope, and more varied in type for communities that aspire to be large, relative to those that aspire to remain small. Large communities also tend to rely more on rules that concentrate power in administrators, and on rules that manage bad behavior. Overall, these measures of complexity increase with size among successful communities, suggesting that complexity can make institutions more effective at mobilizing large-scale collective responses to resource constraints.


(5216, 41)


"srv_addr" --- IP
"y" --- success (core group size)
"ylog" --- log thereof
"success_dummy0" --- indicatesy = 0
"success_dummy1" --- indicatesy = 1
"srv_max" --- server's max simultaneous population
"srv_max_log" --- log thereof
"srv_details" --- the extent of the transparency of server's API (ordinal)
"dataset_reddit" --- server came from reddit dataset
"dataset_mcs_org" --- server came from dataset
"date_ping_int" --- beginning of the month window selected for this server,
over which y is calculated.
"weeks_up_todate" --- # weeks since this server was first identified
"governance_intensity" --- # plugins installed
"plugin_specialization" --- median over plugins for # of other servers that have it
"rule_diversity" --- ecological variety over rule types (count of types)
"governance_scope" --- ecological variety over resource types (count of types)
"dataset_source" --- where server came from (can determine value of srv_details)
"perf_factor" --- discretization of y for plots
"pop_size_factor" --- discretization of srv_max_log for plots
"cat_chat" --- number of chat plugins
"cat_informational" --- number of information plugins
"cat_economy" --- number of economy plugins
"cat_admin" --- number of admin plugins
"plugin_count" --- number of plugins
"nuvisits12" --- # unique visits over year
"nvisitsobs12" --- # visits over year (observed users)
"nvisitsunobs" --- # visits (unobserved users lacking ID)
"res_grief" --- number of plugins managing grief
"res_ingame" --- number of plugins managing ingame resources
"res_realworld" --- number of plugins managing compute resources

Feel free to contact Frey for additional information and resources.


See ms supplement