ANN: "Making it Count: Statistics and Statecraft in the Early People’s Republic of China, 1949-1959." ARI Talk by Arunabh Ghosh (Harvard University).
The talk will take place through Zoom at the Asia Research Institute (ARI) of the National University of Singapore (NUS). For registration please see the following details:
Thursday, 8 October 2020
10.00 – 11.00am (SGT) Time Converter
Among the biggest challenges facing leaders of the newly established People’s Republic of China (PRC) was how much they did not know. In 1949, the government of one of the largest states in the world, committed to fundamentally re-engineering its society and economy via socialist planning, had almost no hard, reliable statistical data about their own country. Making it Count is the story of attempts made to resolve this ‘crisis in counting.’ The book shows that at the heart of the varied solutions attempted was a contentious debate about the very nature of social reality and the place of probability theory in ascertaining that reality. It explores the choices made and the effects they engendered through a series of vivid encounters with political leaders, professional statisticians, academics, ordinary statistical workers, and even literary figures. Readers discover how an early reliance on Soviet-inspired methods of complete enumeration became increasingly untenable by the middle of the decade. A series of unprecedented and unexpected exchanges with Indian statisticians followed, as the Chinese sought to learn about the exciting new technology of random sampling. These developments were, in turn, overtaken by the tumult of the Great Leap Forward (1958-1961), when both probabilistic and exhaustive methods were rejected and statistics was refashioned into an essentially ethnographic enterprise. Written in a balance of narrative and analytic styles and grounded in a wealth of official, institutional, and private sources culled from China, India, and the United States, Making it Count offers a compelling new history of state-building in the early PRC. That this mid-century history cannot be understood without acknowledging Soviet and Indian influences not only revises existing models of Cold War science but also globalizes the history of statistics and data, demonstrating wide-ranging developments in what has often been narrowly construed as a universal (if European) history.