“Everything They Ever Wanted”: A NetLogo Case Study of a Model of Rebellion in the Tobacco Dark Patch ofTennessee and Kentucky

Agent based modelling appears to be gaining traction as a methodology in historical investigation. Good!

Just seen:

http://www.allacademic.com/meta/p_mla_apa_research_citation/0/8/2/3/2/p82320_index.html

“Everything They Ever Wanted”: ANetLogo Case Study of a Model of Rebellion in the Tobacco Dark Patch ofTennessee and Kentucky

Abstract

The Night Rider Tobacco War during the period 1904-1909
in Kentucky and Tennessee provides a model case study of rebellion/revolution/ social banditry. The use of platoon- and company-size unit operations, guerilla warfare, boycotts and sabotage by the Dark TobaccoGrowers Association against the Duke Tobacco Trust followed the trajectory of a revolution, from inception through success in overturning the power relations in the traditional small tobacco farm country. Success in gaining the aims of the movement was followed by a
melting away of the footsoldiers despite strenuous attempts by the leadership of the Association to continue activities after victory in the original aims of the group—destruction of the economic and political stranglehold the Duke interests had achieved. As the factual background of the events in the Dark Patch are known and—in most instances—well documented, it is possible to use NetLogo programming to test the validity of causational theories of revolution. NetLogo is a computer modeling environment in which agents are programmed to carry out specific, simple rules of behavior and allowed to interact—a “virtual laboratory” in which the behavioral rules can be altered to test different hypotheses and the result permitted to emerge based solely upon the operation of those rules. For each posited causative factor (Goldstone’s triad of inflation, heightened elite competition and strain on governmental finances, for example) the original position
and dominant motivation(s) can be set up and the situation allowed to play itself out to see how closely the predictions of the theory mirror the historic record. The further a theory’s predictions deviate from reality, the greater the doubt cast upon its validity.