Reading of a 1950s pamphlet. There is also a pdf link available in the vid description. I found this to be an interesting pamphlet regarding the relationships of capitalists in war time, helpful for concrete examples of the mindset of capitalists in war.
Also contains information about West Germany’s preferential appointments of Nazis in positions of power, which is the pamphlet’s main focus, although I’m posting it here for its information about industry.
From the video description:
This text masterfully exposes the preferential attitude of American finance capital towards N*zi fascists in post-WWII Germany.
A segment of the text I wanted to share here:
Since the main aim of the bombing was supposed to be to put German industrial production out of commission, Americans expected to hear that German industry had been knocked for a loop. Strangely enough, however, it turned out that while over 20 per cent of all German housing was destroyed, most of the factories were left untouched. U.S. News, for example, reported on June 3, 1949 that a survey of Germany showed “productive capacity still intact.”
How come?
Part of the answer was supplied, perhaps unknowingly, by the late, General Hap Arnold, war-time Air Force chief:
“There have been many criticisms,” wrote the General in the New York Times on December 6, 1949, “of our strategic bombing in Germany and Japan. […] As far as we knew, we were using the best available information for target selection. We were using as advisers men who had been in Germany and Japan; who had helped build their industries, loaned them money, studied their industrial problems, sold them their factory equipment and visited their factories. What better source of advice could we have obtained.”
What better source, indeed!
Can’t you just see the big guns of General Motors and Dillon Read, of Standard Oil and U.S. Steel marching into the Pentagon, stepping up to a map and saying—Here are the plants we’ve got a couple of million bucks sunk in. Bombs away, General. Knock them to smithereens.
This shouldn’t be an unfamiliar concept in a ML community of course but I found the pamphlet interesting with its many specific examples and naming of names on this subject.