The problem of popular, collectively organized political action has long had a grip on the attention of historians, sociologists and political scientists. The British campaign for the abolition of the slave trade (1788-1807) is perhaps the first of such cases. Across social science disciplines that engage with this problem, there is now a consensus that the patterning of social relations has a bearing on the level of mobilization. This dissertation examines this case, using archival data to model the social networks of individuals and settlements through which the movement was organized and diffused. Novel graph models will be used to estimate these structures and investigate which features contributed to movement success. The insights that this research provides will help inform the historical narrative of the period and the movement itself, and, moreover, this research will contribute to a more complete understanding of the type of network structures that enable or constrain collective mobilization in other social and historical contexts.
This research introduces an innovative methodology - exponential random graph modeling (ERGM) for ego-centrically sampled data - as a solution to move empirical investigations grounded in data and simulation closer. These models have been developed to study the spread of infectious diseases, and thus they lend themselves well for the study of British abolition because (1) it is easy to see the parallel (though not equivalence) between the diffusion of diseases and ideas; and (2) the data problems of hard to find contemporary populations that often confront infectious disease modelers are strikingly similar to those that historical sociologists face. Primary source documents for a case study of Manchester which then is embedded at the national scale in England provide the data for these models to: (1) answer the question of why abolitionist mobilization was successful at these different scales, (2) provide a framework to study other mobilization events in similar historical con- texts, and (3) bring ERGMs, a new analytic tool, into the mainstream sociological research on mobilization.
This work is a combination of highly technical network analysis and the meticulous compilation of datasets from digital archives. These data sources are not yet widely exploited in historical research, and thus this research will provide a template for conducting similar work by interdisciplinary scholars from history, the social and computer sciences. In addition, this work will point to some of the determinants of social movement success. The data produced by this project will be useful to researchers for continued investigation of methodological techniques, theory building, and the study of this particular case.
