Friday links: Meg read ALL the things and picked the best ones

This week: the secret to R’s success, the internet vs. Tim Hunt, career polygamy, satisficing vs. stress, the joys of chairing your department, the formula for getting an academic job (is that there isn’t one), ggplot2 cheat sheet, and more. Oh, and Jurassic World lacks a responsible waste diversion program. 🙂

From Meg:

I’m late in getting to read this, but this is a great post calling for acceptance of career polygamy in science. It’s a call for acknowledging and accepting that some people will want to pursue science and other pursuits (e.g., writing) at the same time, and that such people have a lot to contribute to science. (ht: Lenny Teytelman)

In a similar vein of redefining what constitutes success in science, academia, and life: at Tenure, She Wrote, a guest blogger wrote about her decision to turn down an offer for a tenure-track position. Her decision was largely based on deciding she wants to stay in the city where she’s set down roots and where she has a family support network. Without a doubt, the hardest part of academia for me has been moving away from great support networks multiple times. I completely understand deciding that it would be better to leave academia than to move away from a strong support network.

Lots has been written on Tim Hunt’s sexist comments, but I found two pieces especially illuminating. First, this piece from Michael Eisen, which puts Hunt’s comments in the context of a meeting of young Indian scientists that Hunt and Eisen both attended, and, in particular, in the context of a session where young women scientists talked about the sometimes horrifying stories about their experiences as women scientists. Second, this piece by journalist Deborah Blum, who was at the event in Korea where Hunt made his sexist remarks, also helps put the events in context. She writes,

I do have sympathy for anyone caught in the leading edge of a media storm. But if we are ever to effect change, sometimes we need the winds to howl, to blow us out of our comfort zones.  Because the real point here isn’t about individuals, isn’t about Tim Hunt or me.
The real point is our failure, so far, to make science a truly inclusive profession. The real point is that that telling a roomful of female scientists that they aren’t really welcome in a male-run laboratory is the sound of a slamming door. The real point is that to pry that door open means change. And change is hard, uncomfortable, and necessary.

That made me think of this series of tweets by Lindsay Waldrop, who offers her perspective as a young woman scientist on the reaction to Hunt’s comments. She points out, quite correctly, that NOT responding to these comments is damaging, because it seems to condone them. (ht for the Blum piece to Gina Baucom)

Here’s a ggplot2 cheat sheet that is searchable by task. It seems like it will be quite handy! (ht: @statsforbios)

I really enjoyed this post by Liz Haswell on how to deal with stress as an academic. (The post says it’s aimed at grad students and postdocs, but I think it applies to everyone.) One part I especially agree with is:

No matter how smart and competent you are, it is not possible to do an excellent and compelling job at everything that comes across your path. So you have to choose. First you must decide what you DO want to accomplish well (give a great talk, make substantial progress on an experiment, make industry connections). Then, you simplify your life and reduce stress by a) “satisficing” or b) jettisoning the rest.

As she says, it can be really hard for a perfectionist to accept when something is good enough but not perfect, but doing so is so important. (ht: Joan Strassmann)

From Jeremy:

Why has R been so successful, despite its quirks? The linked piece omits part of the answer: lots of people use it, which encourages others to do so. Nothing succeeds like success. (ht Brad DeLong)

Data-based debate on the risk factors for corrections and retractions of scientific papers. Haven’t read the papers in question myself so don’t have a view of my own. But given that the data in question are correlational, and given the many factors that affect whether or not a correction or retraction occurs (some of them unmeasurable), I doubt that you can say much about causality with any confidence no matter how you slice and dice the data.

How long are master’s theses and PhD dissertations? Here’s the answer, for the University of Minnesota. It’s broken down by field. I leave it to you to decide if “above average” is a good thing in this context. 🙂 I believe I’ve linked to an earlier version of this dataset that lacked data on master’s theses.

Princeton’s trustees approve 17 new faculty hires; Michael LaCour is not on the list. I assume that means he’s been unhired. (ht someone on Twitter; sorry, forgot who)

There’s no magic formula for success in academia. Echoes my own thoughts in various old posts. A further (wildly speculative) thought: does academia tend to attract people who want a magic formula for success? I ask because in some ways academia as a career path comprises a very well-defined series of steps. You go to college, then you go to grad school, then you get a postdoc, then you get a faculty position. And at the end of the path is tenure, which gives you more job security than in just about any other occupation. So does academia tend to attract uncertainty-averse people who want to walk a well-defined career path towards a secure destination? (a perfectly fine desire that I share, btw) Which then causes some of those people to get upset or frustrated when they discover that there is no magic formula–that is, that the path to career success in academia isn’t nearly as well-defined as they thought?

Stephen Heard on all the reasons you might actually want to be chair of your department one day.

And finally, a public assembly facilities manager critiques Jurassic World:

While it is never wise to carelessly damage or destroy capital assets, the stated cost of park attractions is substantially less than the potential tort exposure in the event of an attraction-guest consumption event.

🙂 (ht Marginal Revolution)

8 thoughts on “Friday links: Meg read ALL the things and picked the best ones

  1. “does academia tend to attract people who want a magic formula for success? I ask because in some ways academia as a career path comprises a very well-defined series of steps. You go to college, then you go to grad school, then you get a postdoc, then you get a faculty position.”

    I can only speak for myself, giving us n=2, but for me the answer would be “no”. I had no idea what I wanted to do when I started university, and even when I began my PhD I did not imagine that I’d become a scientist; in fact I was fairly sure I didn’t want to become one, but I did like the idea of doing a PhD and spending 3 or 4 years asking some interesting ecological questions. In hindsight of course I was clearly destined to become an ecologist 🙂

      • Publishing highly cited papers in top journals seems a decent formula for success in academia. As a baseline it works very well. How to do that is a different story.

      • Yes, as you say that *seems* like a “formula” but it’s actually not. Because “doing really good science that a leading journal will want to publish” is not the sort of thing that can be reduced to a recipe anyone can follow.

      • Actually, I disagree. There are several things that can be done. If you want a R2 = 1, it is not going to happen, but selecting research projects, labs etc. that can substantially increase your odds. All other things being equal, those things make a big difference.

      • Oh, absolutely! I’m not denying that. But while those things make a difference, they’re very far from a step-by-step recipe for success.

  2. When I was in grad school I was student rep on three hiring committees. These were mid-tier universities.

    For a pub list alone to make a difference, it would have to be so good that a mid-tier univ wouldn’t have a real chance at hiring the candidate. There were about 150 apps for the jobs, and many candidates with strong pub records.

    IMO whats more important is to have built good working relationships with several respectable scientists and a record of obtaining funding, so it looks like you have a network of colleagues and are ready to hit the ground running on research funding.

  3. The problem with arguing about how R’s crazy scoping rules helped R become successful with things like Shiny is the survivorship bias. It does not take into account all the great things that might have been done but were given up on because the scoping rules made it too hard to bother with.

    Also, while I agree that R’s built in support for missing data is crucial to its success, it might be worth mentioning that the way R implements its missing data is with exactly a kind of dangerous hack where R considers a certain floating point value to represent missing. It is just that R is implemented so as to hide this hack from the user.

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