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Read #5: Clash of Civilizations, Data Science, Welfare for Autocrats

Posted on Aug 9, 2020 by Chung-hong Chan


The World is still sick. Second wave is here in Germany. But many people are still traveling so they are not in Germany. I can’t understand this world. It is like the world is at war but you still need to travel for your vacation. Maybe I’ve switched on the “not normal” mode. Most people don’t.

Today’s temperature is 37 degree. The world can’t handle two crises at once. Well, even when the world were handling only the climate crisis at a time, I still don’t think the world will do anything about it.

I keep reading, albeit a bit slower. And here are my 3-sentence reviews.

The Clash of Civilizations and the Remaking of World Order

Samuel P. Huntington, Simon & Schuster, 2007

The book was published in 1996 actually and the most important conflict of the time was Bosnian War. Hungtington correctly predicted that the conflict between the Western World and Muslim World (9/11 etc.) and the rise of China. However, his view of eventual coopt of Eastern Asian states (e.g. Taiwan, Hong Kong, Japan, Singapore) with communist China missed the resentment of these states to CCP’s aggressiveness.

Build a Career in Data Science

Emily Robinson & Jacqueline Nolis, Manning, 2020

I got this book as a humble bundle and this book is quite different from other books I read this year. I couldn’t help but to skip a lot because I am not planning a career transition and the first few chapters are aimed at people with almost zero experience in the so-called data science. I think the gems in this book are the provision of a working definition of data science and the chapter on building your portfolio (blog, talks, open source contributions, etc).

Welfare for Autocrats: How Social Assistance in China Cares for its Rulers

Jennifer Pan, Oxford University Press, 2020

I am avoiding books about China but for this one I am reading it as a political science methods book (the author is so well-known and social scientists usually cite her Harvard-Stanford-UCSD super research group as “[Gary] King, [Jennifer] Pan, & [Margaret E.] Roberts”). The idea of Seepage is interesting (one government priority alters the allocation of resources and goals of unrelated policy areas) and I think it can also apply to the corona responses of many non-free governments too. But I can still drill holes in some minor methodological details: e.g. using linear regression for count data, etc.

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