Preprint: a data-based guide to the N. American ecology faculty job market!

As regular readers of this blog know, I spent three years compiling a massive amount of data on the N. American ecology faculty job market. It covers everything from the fraction of ecology PhD recipients who get tenure-track faculty positions, to the gender balance of recent faculty hires, to the publication records and teaching experience of recent faculty hires, to how search committees want applicants to customize their applications, to the typical number of applicants per position, and much much more.

Now I’ve summarized all the results for the ESA Bulletin; the paper has just been accepted and hopefully will be out later this fall! But you don’t have to wait that long, because a preprint is up on bioRxiv. There are only minor differences between the preprint and the forthcoming final version in the Bulletin.

I hope this preprint and subsequent Bulletin paper will get these data to more of the people who need them, and will inform discussions about diversity and equity in ecology faculty hiring.

Good luck to everyone on the ecology faculty job market; I hope you find these data helpful. And if you’re advising or mentoring any ecology faculty job seekers, please point them towards this paper (and maybe even read it yourself!)

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10 thoughts on “Preprint: a data-based guide to the N. American ecology faculty job market!

  1. Apropos of nothing, my pop culture memes are hilariously out of date. Nobody currently on the ecology faculty job market will have the first clue what the meme in the post is referring to.

    “So kids, back in my day not all movies were about superheroes. I know, it sounds weird to me too now. Anyway, once there was a movie about a sports agent…”

  2. Beautiful work. I definitely think starting this conversation on blogs was great, and moving it to well-read journals will hopefully get a lot more people, ideally students and early-career folk, talking about it.

  3. Hi Jeremy, I’d like it if you could address some of the criticisms on privacy and the harm that your assumptions about gender binary could cause, which you have been tagged in on Twitter.

    Especially as pertains to you normalising these assumptions because they could (you assume) have a small effect size–which is a pretty weak argument against representation.

    Disappointed to see that you are engaging with positive/”constructive” feedback on Twitter, but not serious concerns about harming marginalised groups.

    • I took down the dataset a few days ago, I agree that posting it was problematic.

      Inferring gender from names and photos is an imperfect approach that’s nevertheless widely used, and that can provide valuable data on inequity and its sources (for example: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.4993). I believe that, on balance, those admittedly-imperfect data help make the world a better place. But different people will of course make different judgments on that.

      No one’s under any obligation to engage with someone else simply because that someone wants them to engage. I’m not obliged to engage on Twitter, a forum in which I’m not comfortable engaging for several reasons, any more than anyone else is obliged to comment on this blog.

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