Liberal arts

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Victor Davis Hanson:

The tragedy, then, is not just that a campus of the University of Wisconsin would drop the history major but that the custodians of history in the 21st century lost the ability to teach and write about history in a way that sustains a hallowed 2,500-year tradition. In other words, what is being jettisoned is likely not just history as we once understood it but rather de facto poorly taught “-studies” courses — which sadly become snapshots of particular (and often small) eras of history — designed to offer enough historical proof of preconceived theories about contemporary modern society. The students then are assumed by the course’s end to be outraged, persuaded, galvanized, and shocked in politically acceptable ways. Usually they are just bored, as supposedly with-it professors endlessly regurgitate the esoterica picked up in graduate schools.

Hanson overstates his case at times, but the core argument is quite interesting. History is pitched as a way to understand and “fix” the present. However, most history courses are “snapshots of particular (and often small) eras of history — designed to offer enough historical proof of preconceived theories about contemporary modern society… Usually [students] are just bored, as supposedly with-it professors endlessly regurgitate the esoterica picked up in graduate schools”

The piece that I thought was most interesting–one of the most common justifications for teaching history is avoiding the mistakes of the 1940s (“at a time when Nazism is resurgent society needs for people to know history, even if the economy might not”), but:

Unfortunately, few universities offer courses in World War II, which might most effectively offer a variety of explanations of why Nazi Germany was able to absorb most of Europe and trigger what would become a global conflict that cost 65 million lives.

But when one looks at the Wisconsin campus catalogue, one seems to find few if any classes in World War II. The closest might be “Women, War and Peace,” “Dilemmas of War and Peace: An Introduction to Peace Studies,” or “War and Propaganda in the 20th Century.” No doubt such offerings might be great courses, but I don’t think they would cover fully the Nazi aggrandizement of the late 1930s, particularly the role of Soviet collaboration, British and French appeasement, and American isolationism, or the tragic circumstance of the Munich Agreement — in other words, the likely best way for students “to know history” of any purported contemporary Nazi ascendance.

Of course, liberal arts education is much more than utilitarian concerns about the present day. But I found compelling Hanson’s claim that liberal arts themselves deserve some of the blame for their own death.

Scientific fraud

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Alex Berezow:

A stunning report published in the Annals of Internal Medicine concludes that researchers often make “inappropriate requests” to statisticians. And by “inappropriate,” the authors aren’t referring to accidental requests for incorrect statistical analyses; instead, they’re referring to requests for unscrupulous data manipulation or even fraud.

Full report in the Annals of Internal Medicine here.

This seems… not as surprising nor shocking as I expected?

Some of the results are somewhat open to interpretation. 24% reported that they had been asked to “remove or alter some data records (observations) to better support the research hypothesis.” 30% had been asked to “interpret the statistical findings on the basis of expectations, not the actual results.” On the one hand–yes, this runs the risk of confirmation bias. But on the other hand, don’t you have to be somewhat hypothesis-driven when doing scientific research?

There is a real, active debate with measurable results in quantitative trading. Basically, there are two schools of thought. One school (e.g., AQR) basically replaced its traditional, frat-bro/swim-team human traders that traded by drawing hypotheses out of the data with economics and computer science PhDs that could manipulate this data faster and better. The other school (e.g., Renaissance, Winton) do the same thing but let computers make all the decisions. The difference is that the latter will often trade on counter-intuitive signals (“if there were signals that made a lot of sense that were very strong, they would have long ago been traded out”), while the former will generally only trade on signals that they can intuitively understand, even if they could not have gotten to the signals on first principles. Matt Levine has more here and here.

At first glance, this would imply that the news in Annals is terrible. After all, Renaissance and Winton are purported to outperform the market, so it must work. Should we not force our scientists to be data-driven and lay aside ingoing hypotheses?

But the problem is that there are very few Renaissances and Wintons in the world. The reason for this is that there are very few people in the world who are good enough at data science to be able to differentiate between random statistical significance and counter-intuitive hypotheses that generate alpha. And the intuitive quant firms have not done badly! (At least, until the last few years–and that may be driven more by an uber-bull market, which makes it hard for any firm to generate alpha.)Maybe scientific research should be “good enough.” This is super controversial, since scientists almost universally believe that changing data to fit hypotheses is wrong–but then again, this data show that scientists are doing that anyway. Think about it. You’re a budding associate professor, trying to make tenure, and you discover a result that implies that the world is flat, or pirates are inversely correlated with global warming, or green jelly beans cause cancer. What do you do? Do you just uncritically hit “publish”? Or do you assume that your data were wrong and “interpret the statistical findings on the basis of expectations, not the actual results”?

Identity politics and graduate economics

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Identity politics and graduate economics

Why we fall for bogus academic research

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Why we fall for bogus academic research

~35% of psychology studies surveyed were reproducible

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~35% of psychology studies surveyed were reproducible

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If there’s one thing I learned at Princeton, it’s to be skeptical of everything published in an academic journal.

via xkcd

How academia’s liberal bias is killing social science

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How academia’s liberal bias is killing social science