In 1949, at the end of a long period of wars, one of the biggest challenges facing leaders of the new People’s Republic of China was how much they did not know. The government of one of the world’s largest nations was committed to fundamentally reengineering its society and economy via socialist planning while having almost no reliable statistical data about their own country. Making It Count is the history of efforts to resolve this “crisis in counting.” Drawing on a wealth of sources culled from China, India, and the United States, Arunabh Ghosh explores the choices made by political leaders, statisticians, academics, statistical workers, and even literary figures in attempts to know the nation through numbers.
Ghosh shows that early reliance on Soviet-inspired methods of exhaustive enumeration became increasingly untenable in China by the mid-1950s. Unprecedented and unexpected exchanges with Indian statisticians followed, as the Chinese sought to learn about the then-exciting new technology of random sampling. These developments were overtaken by the tumult of the Great Leap Forward (1958–61), when probabilistic and exhaustive methods were rejected and statistics was refashioned into an ethnographic enterprise. By acknowledging Soviet and Indian influences, Ghosh not only revises existing models of Cold War science but also globalizes wider developments in the history of statistics and data.
Anchored in debates about statistics and its relationship to state building, Making It Count offers fresh perspectives on China’s transition to socialism.
This essay offers commentary on the previous three articles regarding PRC-era science by Sarah Mellors, Chuan Xu, and Sigrid Schmalzer. It notes that by moving beyond older concerns that were centered on issues of state control or techno-nationalism, these articles exemplify new directions in the study of PRC-era science. Their focus on lived experience, local stories, and materiality provides rich and diverse perspectives on histories of science in the PRC by exposing the often contradictory ways in which the power and influence of science operated across society. The commentary concludes by identifying three pathways for future research.
Is there a correct way to ascertain social fact? As late as the 1950s, the scientific community remained divided over this question. Its resolution involved not just epistemological and theoretical debates on the unity or disunity of statistical science but also practical considerations surrounding state-capacity building. For scientists in places like the People’s Republic of China (PRC) and the Soviet Union, at stake was the very ability to realize the kind of planned economic growth that socialist countries idealized. The solution they chose reformulated statistics explicitly as a social science, salvaging it from what they then dismissed as the tainted, bourgeois, and socially unproductive pursuit of mathematical statistics. This distinction—most tangibly understood as the rejection of all probabilistic methods—had implications for both the ways in which data was collected and the ways in which it was analyzed.