Reviews for Both Sides Now: The Story of School Desegregation's Graduates

The average rating for Both Sides Now: The Story of School Desegregation's Graduates based on 2 reviews is 4 stars.

Review # 1 was written on 2017-07-19 00:00:00 Christopher Benavidez This series is really hit or miss, but I felt like this one taught me a lot about what dewey was all about. Good little intro to his ideas.

Review # 2 was written on 2018-09-07 00:00:00 Walter Seward I have heard Dewey's name floating around a lot: Ben Sasse and conservatives hate him for education, but others seem to really like him. I became a little more interested when I talked to Rob Kass about "instrumentalism", which I guess is the same concept as "pragmatism", which Kass said was a philosophical underpinning to his proposed "Statistical Pragmatism". The book wasn't a crystal clear introduction to "instumentalism", but the gist is that the world should be viewed functionally, and nothing is "true" in and of itself, removed from context. The truth should be viewed in how well the thing should be used in order to solve a practical question of interest. There were several counters to this in the book, most ardently by Bertrand Russell. For example, he stated historians looked to record historical facts, not use them for practical purposes. Dewey had no real response here. A modern version of this debate is being played out by Sam Harris and Jordan Peterson, especially on the "What is True" podcast. All in all, I didn't really understand what made Dewey so famous, other than that he popularized Pragmatism. It did feel like Charles Peirce, not Dewey, was the more unique thinker. But everyone needs a cheerleader. Interestingly, Peirce was mentioned a lot in Ian Hacking's book: The taming of chance, and his idea of abductive reasoning has started coming back into modern conciousness. So does instumentalism work with statistics? For data analysis, in the client relationship, I think so. If you think about these situations, the *best* analysis are always grounded in an externally defined goal. For example, we want to "put soccer players in groups", "estimate the number of Trump voters", or "predict internet traffic based on an add". In each case, the analysts want to execute statistical methods on the data, in order to serve an externally defined goal. The best statistical methods *work* in reaching this goal. So, we would say that statistics doesn't exist until there's a dataset, and something someone wants to do with the dataset. One question: is it consistent to believe in statistical pragmatism, and not pragmatism more broadly?