Friday links: a sobering story about publicizing scholarship on social media, polynomial cows, and more (UPDATED)

Also this week: Twitter vs. ducks, Stephen Heard vs. Charles Darwin, a crash course on causal inference, and more.

From Jeremy:

Former National Museum Wales social media person Sara Huws with a very interesting–and sobering–thread on what makes for viral content about Welsh history. Basically, say that whatever bit of history you’re relating was “suppressed” by some oppressor. Even if it wasn’t. Does this point generalize to social media content about science and academia rather than Welsh history? I have no idea, but I’m sure some of you do; curious to hear your comments. (ht @dsquareddigest)

I’m late to this, but here’s a crash course on Judea Pearl’s ideas about causal inference. Short blog post with a good figure; useful teaching tool. Includes an astute critical discussion of some ecologists’ tendency to just throw a bunch of predictor variables into a GLM and then try to interpret it causally.

It’s the end of the world theoretical physics as we know it. Because simulations (including physical simulations) are replacing math. Related old post from me musing about a similar trend in ecology. (ht @noahpinion)

Everybody in the world badly underestimates how many people are pretty happy. I link to this mainly because it reminded me that ecologists’ beliefs about many aspects of the ecology faculty job market are incorrect in the pessimistic direction. Now I want to know: in what contexts, if any, are most people’s beliefs incorrect in the optimistic direction? Maybe during economic booms? I’m sure there must be a literature on this (there’s a literature on everything), but I know nothing about it.

This week in dogs biting men: the news topics US adults read about most aren’t the topics they say they want covered. In particular, people say they want more coverage of science and climate change than they actually read. The obvious take here is to compare reading news coverage of science and climate change to eating broccoli or flossing: everybody thinks they should do it but nobody actually does it. The more thoughtful take is to ask how news coverage might have value even if it’s not widely read at the time it’s published. (ht @dsquareddigest)

The future of data science looks like the present of major league baseball. This brief post will be Greek to anyone who hasn’t read books like Moneyball or Big Data Baseball or The Only Rule Is It Has To Work, or websites like FanGraphs. But speaking as someone who has and does, I bet it’s right.

Is the division of research labor between universities (basic research) and corporations (development) good for US economic growth? Or would it be better to somehow bring bad the old Bell Labs model? (ht @noahpinion) (UPDATE: I linked to this mainly because I thought it raised an interesting possibility, but apparently it doesn’t establish its conclusions very well.)

Stephen Heard vs. Charles Darwin on whether one should routinely state the authority for a species’ Latin name.

Polynomial cows. ๐Ÿ™‚

Yup. ๐Ÿ™‚

14 thoughts on “Friday links: a sobering story about publicizing scholarship on social media, polynomial cows, and more (UPDATED)

  1. [physics] …And I Feel Fine.

    You just tee those up for me, hoping I’ll comment, right? Clearly we listened to the same radio station in 1989 or so.

  2. “Basically, say that whatever bit of history youโ€™re relating was โ€œsuppressedโ€ by some oppressor. ”

    It must work because everyone’s doing it! Take any controversy and you’ll find someone on one side or the other who says the other side “suppressed” the *real* story.

  3. Now on to other topics: “in what contexts, if any, are most peopleโ€™s beliefs incorrect in the optimistic direction”
    Election results in late October, 2016, in the USA and not long after regarding a referendum in the UK. Predictions were that logic and reason would win. That was overly optimistic.

    Data and Baseball. The Cubs illustrate this point well. When they shifted to a data-centric approach with the Theo Epstein era, they started winning, but it took a couple years to get the right players into the system. However, they over-relied on data for pitchers, so their minor league system has failed to develop much (any?) in terms of young pitching. So they changed their strategy last year when scouting young pitchers–relying more on *expert opinion.* Scouts matter.

    Wikipedia tells me that Calgary has had a fraught relationship with pro/semi-pro baseball.

    • “However, they over-relied on data for pitchers, so their minor league system has failed to develop much (any?) in terms of young pitching.”

      Hmm. My understanding is that the Cubs’ knew that pitching prospects are much more risky than position player prospects (hence the old saying that “there’s no such thing as a pitching prospect”). So the Cubs made a conscious decision to build their pitching staff through trades and free agency rather than the draft. Is my understanding of their approach incorrect? Would be very interested to read more about this if you have links you recommend.

      “Wikipedia tells me that Calgary has had a fraught relationship with pro/semi-pro baseball.”

      [takes Calgary Vipers hat down from shelf, uses it to cover sobbing face.]

      There is a very well-supported college summer league team in Okotoks, just south of the city.

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