Statistics, lies, and damn lies.

Making It Count, Statisitics and Statecraft in the Early People’s Republic of China, Arunabh Ghosh, Princeton University Press, 2020.

A 300 page book about Chinese statistics in the early 1950s?!

Yup, that’s what I’m reading for fun. And it was a pretty good read too!

The value of this book, for those of us that are neither statisticians nor historians is in the detailed understanding of how ideology influences both the training and practice of statistics. This is especially important, not just for China, but anywhere today that we are reminded/reprimanded that “numbers don’t lie,” or that “numbers are neutral.” They are decidedly not. How they are collected, what ideology/methodology is used to interpret the data, and to what end they are presented are are immensely important to what the numbers say.

In the early 1950s statistics were about supporting the vision of the state/CCP, and not necessarily about “getting it right,” although accuracy was indeed needed. But accuracy was a byproduct of the cause and numbers were both reported and interpreted in ways that were acceptable first to the national office and second to accuracy. Even individual statistician’s own prior experience had to be politically “correct” or an individual was not considered valuable (meaning most statisticians working in China pre-1949 were not considered for jobs after Oct 1949 unless there were no other options).

At the start of the new government in China, when doubt or malaise or lack-of-motivation crept in, and after a long bloody revolution these things were common, the promotion of “model workers,” and ideological motivation was the (top down) answer. Red over expert was the call and individuals that were either critical or unmotivated were castigated as individualists, careerists, and capitalists and their concerns typically dismissed or used as (reverse) propaganda.

One thing that stood out to me was the use of model workers then (1950s China) and now (2021 USA). “Heroes” of the revolution were workers that put ideology first and performed their (normal) jobs with ideological vigor; often times desire/intent/motivation was inferred after the fact to create a Red story. I’m seeing the term “heroes” interpreted today in the CV era of our lives in a similar manner. Grocery and liquor store employees are considered “essential” and given hero status for working during the pandemic (My wife is a grocery store owner and my kids work for her and I can tell you that while they are awesome, they are decidedly not heroes. My military son on the other hand is much more so.). But regular work in the a time of (real or manufactured) crises is often considered patriotic and heroic—meaning, average Zhou can be used as a narrative to promote an ideology. But I digress. Back to the book.

The political traumas of the 50s in China served to derail any hopes of real sustained progress in statistic and so many other fields too. From reliance on and then the complete dismissal of the Soviet Union and their models to the GLF, and from the Anti-Rightists campaign to flirting with Indian statistical methods, and then the crushing of protests in Tibet and the subsequent fleeing of the Dali Lama to India, meant that by ‘59 China was likely worse off in most conceivable measures than it was in ‘53.

Side note: Despite the problems that the politicization of data and methods presents, the Chinese are open about their bias and their reasons for what they do (promotion of the CCP). This supports the popular notion (at least among some China scholars) that if you want to know what the CCP wants you have to actually read what the CCP actually says.

A couple of quality conclusions:

Data vs analysis

Regarding statistics specifically and the country in general, “The outcome was a Chinese state that, in spite of generating copious amounts of facts, remained poorly informed.” “…the CCP entered the 1950s with limited knowledge of experience about most of China. This lack of knowledge was compounded by a reliance on a system that generated copious amounts of data but not the capacity to make sense of them.” (P. 285 & 285)

To me this seems a very prescient point still today. Collecting and understanding data are two very different skill sets. Because of Mao data was either collected in mass quantities (count EVERYTHING) or via non-standardized ethnographic interviews. Neither very helpful for governing a nation didn’t really know much about.

Further to this point, “…the primary objects of knowledge of the Chinese socialist state were its own actions and their consequences. While potentially stymieing effective policy making, at a broader level this focus also suggests a certain logical circularity. The state was unable to see and measure society as anything other than a response to its own policies.” And further to this point, “In actively dismissing the usefulness of pre-1949 social scent research, the effectively denied themselves much useful information, especially about the Chinese countryside.” (P. 285) Their ideology clouded not only the interpretation but the gathering of statistical information, making already suspect data even worse as it was massaged to meet political ends.

Today the CCP collects and interprets data in terms of China’s historically predetermined return to power and the inevitable failure of western capitalism. This reading obscures information that could otherwise more robustly inform. Chinese society, as one of my interlocutors told me, has “no such thing as loyal opposition.” In a one party state there is no other point of view other than the CCP. This often means that data leads to predetermined conclusions. Top-down Confucian- or military-style organizations are similar.

The West though falls prey to this selective reading as well, but we have typically also had better corrective abilities. Regarding China specifically, the West spent more than 30 years of political, economic, and cultural efforts under the delusion (or the elite lie) that capitalism would open China to democracy. But in the last 5 years there has be a significant realization across government, business, and academia that this is just not happening. In fact, including China in global capitalist organizations has had the opposite effect—sustaining a totalitarian regime.

You don’t know what you don’t know

“Never having known the advantages (and, yes, the frustrations) of a good statistical base, they [the Chinese] don’t miss it nearly as much as do many of us who look at China from the outside.” This is another nugget relevant to today—the Chinese (and the mirror image Westerners) see what they want to see and miss other things out of out of ignorance that there could be something else going on. Like many specialists, the Chinese are not incompetent, rather they excel at what they have been taught to do and tend to both interpret through their preferred lease and discount all other alternatives.

Lies, damn lies

Lastly, “These battles, between large aggregations of data and in-depth contextual knowledge, remain fundamental to debates within the social sciences today. Much as in the case of statistics in China in the 1950s, they frequently generate partisan loyalties, often with telling consequences.” (p. 286) Regardless of where numbers are coming from, looking at them too narrowly and/or uncritically is problematic. For organizations it means inefficiencies. In the case of governments with large populations it can be murderously devastating.

Bonus bits

Every success or failure in China is somehow relative to another country.

One of the historical “problems” within China is the bifurcation of knowledge—it’s Western or Chinese, it’s socialist or capitalist, it’s reality or historical nihilism.

Historically the Chinese have asked “what’s wrong with China?” They still ask this and this line of thinking has infected much foreign scholarship on China.