Mapping dynamic events: popular contention in China over space and time

Students of popular contention have long observed that social unrest mimics the forces of nature, spreading rapidly across time and space, likening it to a “prairie-fire” or observing a “snowball effect” of strikes and work stoppages. Yet little is known or understood either about how unrest spreads across space over time, or regional susceptibility to unrest. In the attempt to test whether such metaphorical references may in fact be empirical grounded, this project links historical data on two documented waves of social unrest during the Republican (1911-1949) and reform (1978present) eras in Chinese history to static GIS maps, using ArcGIS Tracking Analyst—designed to track dynamic events over time and space— in order to create animated time-series layer capable of revealing the clustering and diffusion of protest events across geographic space over time. Building upon the hierarchical regional space model (HRS) and G.W. Skinner’s work on macroregions in China, we test three key hypotheses regarding the concentration and spread of contentious events within two macroregions during two three-year waves of unrest in modern Chinese history. My longer term goals are to develop broader model to explain the emergence and spread of large-scale collective protest events in Chinese history, and to determine whether certain locales may demonstrate a higher propensity to engage in unrest through the passage of time. The use of animated data layers to capture and record dynamic events over time and space can help to determine whether patterns of clustering and diffusion of protest events remain stable over time, and to test whether spatial knots of “ungovernability”—long a feature of Chinese bureaucratic lore-persist in the People’s Republic, despite changes in regime type, economic fluctuations, and the passage of time.