Friday links: cell biology vs. Brexit, the human rights of nature (?), and more (UPDATED)

Also this week: the world’s luckiest ecologist, why you should move to Tulsa, R package vs. researcher degrees of freedom, app vs. LaTeX, when x>x, the Good Place Class, and more. Lots of good stuff this week!

From Jeremy:

UPDATE: Of all the links to be late to:

Apparently there’s now an app that can take a screenshot of an equation and automatically convert it to LaTeX. Even if the equation is handwritten. If only it worked with MS Equation Editor too, lamented this non-LaTeX user. (ht @noahpinion)

Queen’s University is running a 2-day summer workshop on modeling structured populations. Looks like they have plenty of good speakers lined up (Cherie Briggs, Ottar Bjørnstad, Aaron King, Helen Wearing…) Follow the link for information on how to attend and present a poster.

An R package that attempts to count and visualize “researcher degrees of freedom”, exhaustively and automatically. Certainly useful as a teaching tool, potentially useful in research as well. Though there are surely aspects of researcher degrees of freedom that resist enumeration, aren’t there? (ht Andrew Gelman)

A statistical profile of Twitter-using economists and how they use Twitter. Interesting. I’d be curious to see a similar analysis for ecology Twitter.

Anna Grear vs. John Quiggin on whether we should extend human rights to apply to nature as a way to protect and conserve nature. I think I disagree with both of them, but I don’t know much about the topic.

Data on what predicts undergraduate major choice in the US. Depending on your temperament, you will be either amused or disturbed to learn the extent to which random happenstance (e.g., the times of day at which classes are scheduled) apparently predicts choice of major. Note that I haven’t read the studies underlying the linked news article, so can’t vouch for them. Possibly, some of the results are p-hacked or type M errors or etc. FWIW (maybe not much), some of the results ring very true to me, such as that biology is among the majors most often dropped. But I’m mostly just passing this along so you can follow up yourself if you’re interested.

An argument that highly educated people and “creatives” should consider moving to mid-sized US cities, even those that are perceived as “uncool” and located in rural and politically-conservative states. (ht @noahpinion) Basically: if you’d consider living and working in (say) Austin, Portland OR, or Asheville, you should consider (say) Tulsa, Des Moines, and Boise too. Because you’ll get similar amenities and “vibe”, only much cheaper. I link to this because I wonder if the same argument applies to some ecology faculty job seekers. Ecology faculty jobs in rural states tend to get relatively few applicants (though still many in an absolute sense). No doubt there are good reasons for that–I’m sure many ecology faculty job seekers who pass on applying for jobs in places like Tulsa and Des Moines really wouldn’t be happy living and working in those places. But is that true for everybody who chooses not to apply to ecology faculty jobs in such places? I dunno, what do you think? Maybe a different way to ask the same question (or a similar question) is: how common do you think it is for ecology faculty job seekers (or anyone really) to move someplace and then be surprised at how much or how little they like it? As a postdoc, I had the experience of moving somewhere I hadn’t ever visited, that was very different from any place I’d ever lived before and very far from family, and being pleasantly surprised how much I liked it. That is, I didn’t know enough about either the place or my own preferences to accurately predict how well I’d like it. Does that make me unusual?

An admirably clear and accessible overview of new work debunking recent high profile attempts to detect geographic variation in selection on genetic variation for human height across Europe. I link to this mainly because it got me thinking back to our old post on “small effects” and when they can matter. Here, very slight biases in effect size estimates end up mattering a lot because they’re consistent biases across many, many genetic loci.

Turns out that huge piles of research associating smartphone and social media use with bad health outcomes are unreliable because they all depend on self-reports of smartphone and social media use. Self-reported use turns out to be only very loosely correlated with actual use. I link to this mainly because it got me thinking back to Meghan’s old post on the 80 hour academic work week myth. People’s self-reports of how much time they spend doing anything are basically rubbish, except maybe for scheduled tasks.

Continuing with the theme of “linking to stuff that got me thinking back to old posts”: there’s no such thing as being on the wrong side of history. Which got me thinking back to this old post asking if there are any currently widely-accepted scientific practices that will someday be seen as unethical.

It’s very hard to apply basic choice theory to Brexit. I leave it to others better-qualified than me to decide if this illustrates something about choice theory, something about Brexit, both, or neither.

The cell biology of Brexit. 🙂

Be careful out there Meghan. 🙂 (ht @dandrezner)

“You know the way you feel when you see a picture of two otters holding hands? That’s how you’re gonna feel every day [in this class]”. 🙂 (ht @dandrezner)

From Meghan:

This makes me feel like I should order more used books from Amazon:

 

 

17 thoughts on “Friday links: cell biology vs. Brexit, the human rights of nature (?), and more (UPDATED)

  1. I went to a seminar yesterday that noted that nationally (meaning: US nationally), only about 40% of students intending to major in science graduate with that degree. It’s even worse (~15%) for students from underrepresented groups.

    • Does that just include people who switch to another major and graduate? Or does it also include people who enter college intending to major in science but then fail to graduate at all?

      If it’s the latter, I’m not at all surprised. IIRC (and I may not), something like 50% of students who enter 4 year colleges in the US fail to graduate within 6 years, and the non-graduation rate is higher for students who don’t identify as white or Asian.

      • ….and the non-graduation rate is higher for students who don’t identify as white or Asian

        How about non-graduation rate for immigrant kids who don’t identify as white or Asian?

    • “about 40% of students intending to major in science graduate with that degree. ”

      My undergrad institution, NM Tech, had 50% drop rate for first year students, even though many were recruited from community colleges and already had a year or more of classes (as I did).

      Science degrees are just plain harder. You can BS your way through a Jazz History exam. But not calc III.

      Its not necessarily bad that disadvantaged groups dont complete at the same rate. If you come from a poor background it might be more appealing to get a degree that has a strong market so you can get to work sooner and make more. Pure science undergrad degrees aren’t that great in the job market.

    • The more I think about it the more it seems obvious why disadvantage – and likely poor – students would avoid the pure sciences. Pure science undergraduate degrees offer unappealing careers with low salaries.

      Most common jobs for people with science undergrad degree only:

      Biology: lab assistant at pharma / field assistant / NGO
      Geology: park ranger / asbestos / NGO
      Chem: lab assistant
      Physics: ?? don’t know.
      Environmental Science: asbestos tester / NGO

      None of these positions pay well or offer good advancement opportunities because advancement is blocked by the PhD. If money is a significant consideration, pure science is a terrible degree.

      It would be interesting to do an experience / salary comparison for various STEM fields. Does the extra time in grad school pay off for science students? Suppose two students start their undergrad on the same day, one in computer science and one in biology. Both students complete in four years. The CS student starts working. The biology student continues for MS & lands a job with Nature Conservancy. After the biology student has been working for five years, how does her salary and total earnings compare with her friend in computer science? Possibly the salaries will be comparable, but likely the biology student will be almost certainly be far behind in total earnings as well as have fewer opportunities to increase her earnings in the future.

  2. “how common do you think it is for ecology faculty job seekers (or anyone really) to move someplace and then be surprised at how much or how little they like it?” – If only there were an ecology blog with a history of making interesting polls and getting interesting responses… Oh wait, there is! 😛 (Which is to say, I’d love to see a poll like this on Dynamic Ecology!)

    I always thought of myself as a small to medium town person, and never thought of applying to large cities like São Paulo or Rio de Janeiro. But then there appeared this position in Spatial Ecology, and I just had to apply, and I was selected, so now I live in Salvador, with its 2.6 million people and its pure-chaos traffic, and I’m surprisingly happy here – yet just one year ago I wouldn’t have thought I could ever like living in a city like this.

    I think it might be surpisingly common if we take into account that what matters most can be the job conditions, and not the location. So if the work place is good, the town might not matter so much, especially for people who really like what they’re doing.

    • “I think it might be surpisingly common if we take into account that what matters most can be the job conditions, and not the location.”

      Hmm. I wonder if it commonly works the other way as well–someone moves somewhere and really likes the area (or really likes it for reasons unrelated to their job, such as that it’s close to family), despite finding their job just ok. Had I not gotten hired into my current position, that’s likely the path I’d have taken. My wife and I would’ve stayed in London, a city we surprised ourselves by coming to love (and she’d have stayed at a job she loved). And I’d have found work doing something I liked well enough, that paid the bills.

  3. As a current resident of Fresno, California, I couldn’t agree more. It’s far easier to get by here than my previous city of Denver. The cost of living is MUCH lower. The underdog nature of the city makes me really want to root for it. The pollution and the crime do get old, though.
    An early boss told me once that you should prioritize good positions over location in selecting jobs, as there are great things about nearly every place. Over the years I’ve lived in Boise ID, Laramie WY, and Reno NV but also in Seattle and Portland. They’ve all had a lot to offer in surprising ways.

    • The other thing I’d say is that, as a faculty job seeker, you can always withdraw from the search process after the interview, or even turn down an offer, if it turns out you really don’t like the area. I had the experience of interviewing someplace that I discovered I didn’t like at all once I visited for the interview. Had I gotten the offer, I’d have turned it down. But I had to visit in order to learn that I didn’t like the area at all. There’s no way I could’ve figured that out just by googling or whatever.

  4. It should be noted that the authors likely chose a military academy because all students take the same subjects in the first year(s), and get class times assigned by superiors. Thus from the student’s point of view, class selection is in some sense “random”. So it’s a natural experiment. However, in other universities, students often choose their class times, so it’s unclear how much this study translates.

    One fascinating result from the paper (I may have this wrong only skimmed the figures) is that it appears that course evaluations have a strong effect. We all know that student evaluations are a poor predictor of how well the teacher made students learn the material*, and are influenced by a large number of seemingly trivial factors, but I’d guess that if you saw a signal anywhere, student evaluations might be correlated with “inspiration to stay or switch into a major.” This seems to play out. But, perhaps not, there seems to be a classification in their regression that I don’t fully understand “within-student course evaluation” is a really strong predictor, but instructor course evaluations don’t. Not fully understanding their classification, perhaps this means that a given students evaluation is important for determining their major but not the average evaluation from a student. I couldn’t find much detail on what the difference between these two factors mean, but Fig 7 and Fig 8 of the paper seems to suggest they have quite different effects.

    *although so is almost anything quantitative metric related to the teacher’s actual teaching

    • “However, in other universities, students often choose their class times, so it’s unclear how much this study translates.”

      Good point.

      An anecdotal illustration of this point: back when I was an undergrad at Williams College, the student newspaper published data on the mean GPA in classes from every department in the college. One of the highest GPAs was in Japanese–even though some of those classes met at 8 am, 5 days a week rather than the more typical 2 or 3, and even though they were infamously difficult. Which is precisely why the average GPA in those classes was so high: you don’t take a hard class at 8 am, 5 days a week, unless you *really* want to take it. And you probably don’t *really* want to take it unless you’re *really* committed and so likely to do quite well.

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