10 books like Epistemological Problems of Economics. Ludwig Von Mises

The British historian of the Soviet Union wrote a number of extra-ordinary books about the horrors of the Soviet Union but this was the best one. It pulls together the story of the second great man-made famine in the Soviet Union when Stalin pushed through the second collectivisation campaign. It was the first book to bring together why and how Stalin’s policies deliberately killed so many people.

He also describes how many people in the West chose to ignore the evidence and the eye-witness accounts of the suffering. Reading it inspired me to research the Great Leap Forward famine. The parallels are astonishing. Did Mao know what happened under Stalin, or did he know but not care when he followed the same path?

This was the first real effort to bring together a picture of the whole story of the global Communist movement and the many famines it created. It covers the whole-scale of the misery in regimes in Africa, the Middle East, Latin America, Europe, Russia, India, China, and southeast Asia. It’s a lot of ground to cover but the narrative does not flag. Although the opening of the archives had produced more information, this is still a very impressive book however sobering it might be.

I once saw the 10th Panchen Lama give a very rare press conference in Beijing. This remarkable Tibetan endured years of imprisonment for writing a report describing mass arrests, political executions, and man-made starvation in Tibet in the early 1960s. The report makes it clear that the famine and the eradication of religion was a deliberate policy. It was quite likely that more than any other group the Tibetans suffered more than any other group in China. Although he was at times criticised as a collaborator, compared to the Dalai Lama, who escaped to India, the report reveals that there was no escape from this genocide for any Tibetan.

Yang Jisheng is a Chinese journalist who worked for the state news agency, Xinhua reporter, but diligently spent many years researching the archives to pull together a detailed story of the Great Leap Forward famine, on a province-by-province basis. It is extremely rare for anyone in China who works for the state to paint such an unflinching look at the Chinese Communist Party’s actions. It gives the account unassailable credibility. However, Yang struggles to place the story in the context of the full global history of communism, and attributes the folly to China’s culture and Mao’s shortcomings.

So, what, exactly is this ‘world’ or ‘global history’? Authors slap the two words on their books, universities offer new courses in it, and government officials across the planet now speak of ‘global this’ and ‘global that’. One could be forgiven for throwing up one’s hands in exasperation for failing to understand what exactly these two words mean. That is until Sebastian Conrad published this gem of a book aptly entitled: What is Global History? Yes, it’s a bit academic, but it’s also clearly written, logically organized, and succeeds brilliantly in explaining what global history is and is not without losing the reader in theoretical jargon. If you want to try something beyond the ‘nation’ and ‘empire’, Conrad’s global history is a great place to start.

If you fancy yourself an expert in many fields but want to view those through the lens of statistics, this book is for you. From banking to baseball via climate change and poker, this book gives an insight into predictions and how they can go wrong. While Silver is rather dismissive of the frequentist approach in favour of Bayesian predictions, there is still much to admire in this book. It is a well-written, accessible, light read by a master of forecasting. 

Science has revolutionized the way we live and the way we understand reality, but what accounts for its success? What method sets science apart from other forms of inquiry and ensures that it yields ever-more accurate theories of the world? Strevens argues that the scientific method is not a special kind of logic, like deriving hypotheses from first principles or narrowing hypotheses through falsification, but a simple commitment to arguing with evidence. Strevens shows, with historical case studies, how this commitment is seemingly irrational, as it provides no constraints on what counts as evidence or how evidence should be interpreted, but also incredibly powerful, fostering ingenuity and discovery.

Stuart Ritchie is a cognitive psychologist, a Lecturer at the University of London’s King’s College. A few years ago, he had an experience that seems to have been the impetus for this lively and important book.

A famous social psychologist published a paper in a respected scientific journal purporting to demonstrate extra-sensory perception. The method was conventional—he tested a group of subjects and averaged the results, even though the claimed ability should have been demonstrable by individuals. Averaging across a group made no sense.

The results turned out to be unreplicable (no surprise!), but the paper (by Ritchie and others) showing so was refused publication. Houston, we have a problem! And so does science as Ritchie shows in this thoughtful, well-researched, and surprisingly readable book on a difficult but hugely important topic.

Science, and the freedom of inquiry on which it depends, is at the heart of Western civilization. Science… show more.

Still the best book to diagnose the problems and explain why we need Open Science. Chris Chambers tells of his disillusionment with so many aspects of what researchers were doing, in psychology, but also in medicine and many other fields. That rang true to me—I travelled that same road. He goes on from explaining the problems to describing solutions. Many of these, including openness, better statistics, replication, and increased scrutiny, are now being advocated or required by funders and journal editors, and adopted by researchers. That’s Open Science, hooray!

If you’ve never thought of “intersectional feminism” or “the gender binary” as essentially data-scientific terms, please allow this book to correct that. Data science is a locus of power, and that power can be wielded in the service of oppression or liberation. This book raises essential questions about the predominantly white, male, technocratic interests served by the traditional narratives of data analysis and what feminism and data science have to offer each other. Bottom line: the data doesn’t speak for itself, never has, and never will.