Making science products Open: an informal guide to copyright and licensing

I grew up a hacker (in the original sense) and thus a True Believer in open knowledge. And so, when it came time to start publishing science, I figured I’d make all my products Open. But it turns out that there’s a bewildering array of things to think about if you want to do so. More recently, I’ve been wanting to incorporate other people’s creations in my own, and have encountered various difficulties in using Open products. I’m writing this post, in part, so I have notes I can easily reference in the future. But I figure if it helps me, it can help others, so here you go.

I have to put a note here that I am not a lawyer, and so this is not legal advice. This is just my good faith understanding of the intersection of U.S. copyright law, licensing, and academic products.

What is copyright, and why do I care?

When you make a Thing, you get to decide how to it’s used and how to distribute it to other people. That’s copyright. The sorts of Things we’re concerned with here are scientific writing (journal papers, reports, dissertations, etc.) and other media (photos, video, audio, etc.), scientific data, and software. You’ll see these Things referred to as “creative works” if you read a lot about copyright. Copyright is a type of intellectual property, and is different from patents, which cover inventions [1] specifically a physical thing or a process, and trademarks, which distinguish products and services from similar ones. And most likely, if you make a scientific Thing, you are automatically granted copyright. [2] There are exceptions, though. If you work for the U.S. government, your Things will automatically be in the public domain. And if you are the employee of a University or other institute, you may have signed away your rights in that flurry of paperwork you got when you were hired; in other words, your institution may own the copyright on Things you make, not you.

What do I do with my copyright?

Whatever you want.

The historical use of copyright goes something like this… I wrote a scientific paper and now Journal of Things (JoT) wants to publish it. I assign a license to JoT saying that they can use my writing to make a new Thing — a journal article — and that this journal article can be disseminated as JoT sees fit. Note that I retain the copyright to my actual writing, but JoT has copyright to the formatted, spiffed-up, published version. Now, let’s say someone else wants to use a figure from the published article, they now need JoT to assign a license to them for the use of that figure.

This model of assignment can work fine if the Thing you make is just used once or twice by others, or if you feel strongly about how your Thing is used and distributed. But otherwise, it can get cumbersome. Instead of (or in addition to) assigning licenses on a case-by-case basis, you can assign a general non-exclusive license that automatically allows people to use and disseminate your Things.

How do I assign one of these general non-exclusive licenses?

The first thing you have to do is pick one. And sadly, there are a lot of options for you out there. I really like the Choose A License site to get a sense of what the possibilities are. But if you just have time for a single blog post, here’s a quick run-down. Answer these questions:

  • Are you willing to let your Thing be distributed to anyone who wants it, free of charge?
  • Are you willing to let your Thing be modified into some other Thing by others? (e.g. If you take a picture that someone else wants to use, is it okay if they crop it differently or change the lighting or include it in a collage?)
  • Are you willing to let your Thing and its modifications be distributed by someone else for commercial purposes? (i.e. They might make money off of it.)
  • Do you require attribution? (i.e. You require that your name be attached to your Thing.)
  • Do you want to make sure everyone who uses or distributes your Thing (or modifications of it) uses the same set of answers to these questions as you do?

This seems straightforward enough until you realize that your answers to these questions might have complicated ramifications. For example, if you decide you do not want your beautiful photo of a rail to be used for commercial purposes without your explicit permission, I would totally understand that. But what that means is that when I want to use it in my Ecology article, I probably still need to contact your for explicit permission. That’s because Ecology, although a publication of the non-profit Ecological Society of America, is published by Wiley, a for-profit publisher. This is, of course, a murky area, but none of us are lawyers, right? So I should ask permission. Now, if you had put an open license on that image that didn’t curtail commercial use, then I could have used it in my article without asking. Even within the Open Source community, there are arguments about which are the best licenses to use. (That’s why there are so many of them.)

Ugh, this all sounds like a lot of effort. What if I just don’t do anything?

If you don’t do anything, you retain the strictest copyright allowable under law. In other words, if you don’t assign a general license to your Thing, then legally, it can’t be used, modified, or disseminated by anyone else without getting explicit permission from you.

Well, huh. I’d like to be more Open than that. What do you suggest?

Here’s where I’m at in my thinking of open licenses, though my thoughts may continue to evolve. For creative things I write, such as blog posts, scientific articles, and so forth, I usually retain full copyright, and don’t assign an open license.

For other media, such as photos, videos, and audio, I typically assign Creative Commons license CC BY. I used to care more about commercial use and so some of my stuff is licensed CC BY-NC. But as someone who’s been stymied by the NC (“non-commercial”) designation when trying to use something for not-for-profit purposes because there’s an awful gray area, I’ve given it up. If there is something that I think might have actual commercial value (such as our Snapshot Serengeti photos), I am more conservative with licensing and will slap on an NC. If anyone does wants to use it for a commercial purpose, they can ask and I can issue a separate non-exclusive commercial license that provides me with some slice of the income (as royalties or a one-time payment).

I also used to be a fan of Creative Commons’ “share alike” (SA) restriction, e.g. CC BY-NC-SA, which forces people who use your Thing to use the same license as you. But I’ve found that such “copylefts” are severely limiting for reuse of material. For example, I am never going to be able to persuade a publisher — even a clearly non-profit one — to make a journal article CC BY-NC-SA, so if you give that license to your rail photo, I’m going to have to ask you for explicit permission if I want to use it in an article. Every. Single. Time. So for me, CC BY is where it’s at, unless I think my Thing has actual commercial value. It essentially mirrors what we do in academia already: reuse and distribute work with attribution.

For data, I make it truly Open. I assign it to the public domain, meaning that anyone can use it for any purpose, without attribution. I do this both because it aligns with standard academic practice and because I don’t want anything to get in the way of anyone using my data. [3] Note: please use my data! (Of course, there are potential ramifications of doing so.)

I divide code into two types: code that I consider “end code” that is very specific to particular scientific study and “general code” that might reasonably be expected to be built upon by others. An example of the former is the specific agent-based model I used for a paper on disease dynamics. And for this sort of code, I tend towards a CC BY license because it’s simple and easy and I don’t have much expectation of reuse. An example of the latter is an R package. For this sort of code, I lean towards GPL-compatible licenses to make sure that my code license meshes easily with the code licenses of others. And since I’m no longer a fan of copyleft, the MIT license works just fine most of the time. It essentially says, “go ahead and use my code as you like, but I’m not providing any guarantees that it’s any good.”

Still seems complicated. Any other thoughts?

I have read a convincing argument [4] that I can’t find now, despite lots of searching. If you know it, can you send me the link? that as academics we might reasonably put everything under a public domain or MIT license (which limits liability). The reasoning is essentially that (1) academic culture already provides for attribution by default; (2) there are lots of murky gray waters in the copyright code such that definitions may vary between people (e.g. my definition of “commercial” may be different than yours), meaning that it’s hard to know what people’s real intentions are when they choose an Open license; and (3) we aren’t prone to go around suing each other over copyright infringement. After all, copyright only really matters if you’re willing to enforce it. And that takes time and money and effort.

I’m still chewing on this argument.

And I’m happy to hear others. How do you license your scientific Things?

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Demands for 48-hour proof turnarounds are unacceptable

Perhaps this sounds familiar… You wrote a manuscript and it got sent out for review. It got generally good reviews, and so you revised the manuscript once or twice. Then it was accepted. Hurrah! Break out the milkshakes. [1] or other beverage of choice Then … crickets … nothing. After a few months, you email the editor, who says, yes, it’s in the queue, just going to be a bit longer. Then one day, out of nowhere, whack! An email appears in your inbox. It’s final edits or proofs and the editor wants it back immediately. Forty-eight hours. Or in one business day.

My immediate reaction to this is always, “I’m sorry, your lack of planning is not my emergency,” and I push back. I really, really don’t get this behavior. It has now happened to me for 3 out of 3 first-author papers. [2] Case 1: proofs sent on a Sunday morning demanding 48-hour turnaround; Case 2: proofs sent on a Wednesday while I was on vacation and without Internet demanding a 48-hour turnaround; Case 3: final edits sent on a Thursday evening, demanding turnaround by end of day on Monday, a holiday. And I find it really, really rude.

I freely admit that I am not an editor nor do I understand the inner workings of academic publishing. But I see no reason for such a short deadline. Academic journals are published on regular schedules with regularly formatted content and with each manuscript on independent pages. It’s not like my article relies on the layout of the article before mine. Proofs and final edits can be prepared weeks in advance of submission to the printer (or posting online).

Dear editors, please understand that my job is busy and that I have a life outside of my job. I cannot just drop everything to attend to the task you want me to do. I have childcare responsibilities and so do not work evenings, weekends, or holidays. Do not expect me to. I have previously scheduled deadlines and meetings that I am not willing to cancel. Do not expect me to. Sometimes I am traveling or on vacation and sometimes I encounter emergencies. If I am away from the Internet for a few days, if my schedule is packed, if I am in the hospital caring for a loved one, you are going to have to wait. And you need to plan for such things, because they are a normal part of life.

Dear editors, I see us as partners in this publishing game. I create content. You publish it. I receive prestige from the deal. You fulfill your organization’s mission and/or receive money from the deal. So let’s treat one another as partners when it comes to final edits and proofs. If possible, please prepare final edits and proofs and send them to me several weeks before you need them. If that’s not possible, then please send me a heads-up email a week or two ahead of time telling me when you expect to need my time. I will put you on my schedule. I value our partnership.

I imagine that by creating this false sense of urgency, editors do tend to get fast turnarounds. But I want to suggest to early career academics that you think about something before you cancel that date to work on proofs, before you stay up all night to do edits, before you stick your kids in front of a screen so you can focus on your work and not them. By the time your paper gets to proof stage, the journal has already invested a lot of time and effort in your manuscript. They’ve even scheduled it for a particular issue. It may be more challenging for them to move articles around than wait a few extra days for you. So do what I do and prioritize the edits or proof, but not to the extent it upends your life. And say so, very politely: [3] Feel free to use my words.

Thank you for sending proofs. Unfortunately, I am unable to return them by [date], but I am prioritizing them, and will get them back to you no later than [date]. Thank you for your understanding.

Then absolutely and without fail, return your proofs or edits by your self-imposed deadline.

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Advice for new postdocs

In case you missed it, last week was National Postdoc Appreciation Week. I almost missed it, but Harvard conveniently put up a huge banner and offered us a bit of free food (Super yummy Mexican food this year!) Good food = appreciation? Sure, why not.


September seems to be a common time for new postdocs to start. “So I’m a postdoc now,” tweeted Allison Barner [1] who is a top contender in the “best personal research website ever”. Seriously. Click through. at the beginning of this month, asking for advice on being a postdoc. Her tweets were quickly rebroadcast as other new postdocs waited for replies.

soimapostdocnowAnd I realized, wow, I’ve been a postdoc for more than 2.5 years. I have advice! So too do many others. Here’s a quick run-down on all the advice offered (with credit to , , , , , , , , , and , for all their advice).

Figure out your relationship with your mentor/boss

If you are on an independent postdoc fellowship, this might be the first time you are truly independent. Talk with your mentor to figure out how they can best assist you to achieve your goals.

If you are a hired postdoc, this might be the first time you really have a boss. Talk with your boss frequently in the first few months. In particular, you want to establish (1) what your boss’s goals for you are; (2) what you have to do to be considered “successful” in your boss’s eyes; (3) your boss’s views on what postdocs are for (which could be anything from “primarily advanced trainee” to “paid worker to get lab research done.”) Put down in writing what your boss’s goals for you are and revisit them periodically. Plan on scheduling 3-month or 6-month check-in meetings with your mentor/boss. DLM said that he found this resource to be useful in guiding those discussions.

Understand your pay and benefits

There are three different points here. The first is related to the points about your boss. If you are on fellowship of more than a year and are a paid postdoc, establish with your boss how your pay will rise. Will there be a simple cost-of-living adjustment once per year? Or will you have to meet certain goal in order to get merit raises? Both? Neither? Talking about this feels uncomfortable, but it’s best to do it early.

The second point is that you may be paid on a different schedule than when you were a grad student. I am paid monthly and so is my husband and it is a royal pain in the neck. We have to be very careful with our boom-and-bust household budget, as we live close to our means. If your payment schedule or your living expenses are changing, keep an eye on your personal finances.

Third, make sure you understand your benefits. They may be very different from what they were when you were a grad student. If your institution offers a ‘new employee orientation,’ go to it, even if it seems very boring. If that sort of thing isn’t offered, schedule an hour to sit down with the appropriate administrator to go over your benefits in detail. Understanding it all at the beginning will save time and headaches and money later on.

Set long-term goals

The postdoc is ideally a transitory job, so figure out where you’re going. What type of job do you want after your postdoc? If you were to apply for that position right now, where would you be lacking? Here are some possibilities:

  • If you aspire to a teaching-oriented academic position, do you have actual teaching experience beyond teaching assistant? Have you taught your own course? Have you done any course design?
  • If you aspire to a research-oriented academic position, do you have a solid set of first-author and collaborative papers? Do you have a (small) reputation beyond the institutions where you’ve done your graduate work? Do you have a “niche”? Do you have a “brand”? If you were to give an elevator speech or put together a tagline on your professional online presence, what would it say?
  • If you aspire to career outside of academia, what additional skills do you want to learn or practice? What sort of people could you connect with during your postdoc to help you find jobs? What experiences could you gain that would make you stand out on a resume or in an interview?

Other long-term goals might be more personal. For example, you may want to publish your dissertation chapters even if you don’t aspire to a research-oriented academic job.

Your goals may not perfectly align with your boss’s. That’s okay and very normal! You need to figure out how to meet your own goals while also meeting your boss’s.

And your goals may change over time. That is also okay and very normal. Revisit your goals regularly, with the help of a mentor if possible.

Realize that the postdoc years can be wonderful or awful and prepare

The other day someone asked me what I thought about my job. Without hesitation, I exclaimed, “I love it!” I surprised myself, as I’ve been doing a lot of thinking about “what next.” On the other hand, these years can be very difficult, lonely, stressful, or heart-wrenching. Learn early on about what sorts of services your university or institution offers for mental health, conflict resolution, and social network development. Some recommendations for maintaining your physical and mental health: [2] If you tend to put these sorts of things off, remember that they will help you achieve your goals.

  • Are you in a new place? Make an effort to meet new people. Develop a social network, preferably one that doesn’t completely overlap your work network.
  • Figure out an exercise regime that works for you. If you can make it a social exercise activity, you’re more likely to stick with it and likely to make new friends.
  • Pay attention to when, what, and where you eat. Try to eat healthily. Try to eat meals with other people. Try not to eat while staring at a screen.
  • Prioritize sleep. When you are in a new place with a new job and new people, life can seem overwhelming. Make sure you get a solid chance to recharge each night. Protip: keeping a regular bedtime makes getting a good night’s sleep easier.

Meet people and collaborate…

As a postdoc, it’s often harder to casually meet people than when you were a grad student. You’re probably going to have to make a bit of an effort. But it’s not all that hard. People love meeting postdocs. Grad students aren’t typically intimidated by you. Professors tend to see you as junior scientists bringing new ideas and approaches to their department. Other postdocs are happy to network. So, attend social functions. Ask your mentor/boss to introduce you around. Invite other postdocs to lunch. Gab with grad students in the hall or lounge. (Grad students know All The Things. Make sure you befriend a few!) Schedule an afternoon coffee with faculty who share your interests. Volunteer to give a department or sub-department talk. Join your university’s postdoc association, if there is one.

SS had several tweets on building a foundation of mentors for career advancement: “Look beyond your immediate advisor for career/research mentors to help get to next stage. Set up meetings with researchers at your university or at conferences to talk science and get career advice. It helps to collaborate and development good working relationships outside of your main lab.”

If you’re an ecologist, consider joining the ESA Early Career Section. This section is made up mostly of postdocs, assistant professors, and non-academic equivalents. The section advocates for early career researchers within ESA, providing a voice for those in this tricky career stage.

… But also say ‘no’ …

One thing that can be challenging about being a postdoc is that you seem to have So Much Time. You’re not taking classes. You typically don’t have teaching responsibilities. You don’t have committee responsibilities. And so you have very little to structure your day at the outset. The trouble with So Much Time is the tendency to fill it up — and to fill it up with requests from other people rather than with the things that will move you towards your goals. So think very carefully before starting new collaborations or agreeing to take on a new responsibility. Think about what things will move you towards your ultimate goal most and what you might have to put off if you take on the new task. Prioritize, prioritize. Because soon you will find that you have Too Little Time.

… But also take some risks

Serendipity can play a large part in life and in careers. [3] e.g. My fun side project as a grad student ended up getting me my postdoc, not my dissertation research. If something sounds fun and exciting, you don’t necessarily have to say ‘no’ just because it doesn’t seem to be working towards one of your career goals. Life is not a flowchart. Experiment.

Invest in skills

Invest time in learning the skills you will want later, whether it’s teaching or coding or taking tree core samples. If you feel you want skills in case academia doesn’t work out, computer skills and communication skills are your best bets for re-use in industry. If you want a research job in academia, consider writing or co-writing a major grant from start to end, including the budget and all the minutia.

Live life and have fun

You may be in a new country, or a new part of a country, or a new institution. There are likely many cool and new things to explore both on-campus and off-campus. Check out the campus museums. See what sort of places are affiliated with your institution and visit them. Explore area restaurants. Be a tourist in your new town or country. Make a bucket list of things you’d like to see/do/experience, because if you’re like me, you’ll put them off if you don’t. Then commit to doing one thing per week or month. Your adventures are the things you’ll remember most about your time as a postdoc, not the many hours you sit at your desk.

A few final nuggets of wisdom

  • “Don’t be afraid of not knowing something. You have a PhD now: you are an expert learner!” – SS
  • “Find a comfortable way of asserting yourself – get credit where it’s due for research & teaching.” – FI

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Avoid using the words “student” and “school” outside of academia

Many, if not most, ecology PhD graduates will go on to jobs outside of academia. One particular area needing improvement in most (all?) graduate departments is on teaching trainees how to market themselves outside of academia. CVs are non-starters outside of academia and resumes are very different beasts. In crafting a resume, you need to show what you’re good for in the future much more so than a CV, which is focused on your past.

Killers in resumes are the words “student” and “school,” which are words people outside of academia use when they think of an 18-year-old undergrad.

I came at academia all backwards, having worked multiple jobs outside of it first, and having crafted a handful of resumes for those jobs. My longest job – and the one I had right out of college – was actually very similar to graduate school: I took classes. I worked on various team and individual projects that spanned many months each. I even developed a class to teach, and co-taught it. All that was seen as professional experience by my employer, and that’s how it appeared on my subsequent resumes.

I mention this because often job ads will be looking for someone with, say, 5 or 10 years of professional experience. If you apply for such a position thinking that your experience as a graduate student should count towards that, you’re right! But you’ve got to frame it that way on your resume and in your cover letter. If you just mention that “as a graduate student,” you created conservation plans for local watersheds, it may not count. As a “student,” you are not considered a professional by those outside of academia.

A PhD friend recently failed to be even considered for a position for which he was well-qualified. The position attracted many resumes, and as a first step, an administrative person scanned resumes to winnow out those who did not have basic qualifications. These included – you guessed it – some number of years of professional experience. Unfortunately, my friend’s resume failed to make it clear that he was doing professional work as part of his dissertation, and so his resume failed this first hurdle. His application wasn’t even seen by the scientists doing the hiring.

This administrative winnowing step is super common, and you don’t want your application tossed out before it’s even considered! So here’s what you do on your resume:

  1. List your PhD in your education section. That’s all the mention of “school” you need.
  2. Where you list your work experience, describe your research projects, and in particular describe your role, the skills you used, and how the experience relates to the job in question. Keep it all short. Do not mention that this research was done as part of your dissertation and do not describe yourself as a “student” anywhere.

As fodder for future blog posts, I’ve been scanning the CVs of ESA Early Career Fellows. The CV of ecosystem ecologist Ariana Sutton-Grier actually incorporates a resume style part-way through. (She’s worked for NOAA, so she’s probably needed a resume at various times.) Her resume-style section on her dissertation research is brilliant. It’s listed under “Professional Experience” and reads:

Wetland Ecology and Biogeochemistry Research Assistant, Instructor, and Mentor, Duke University (2002-2008)

Duties: I designed and conducted interdisciplinary research examining how wetland restoration techniques, including organic matter amendments and plant species diversity, affect the restoration of wetland ecosystem functions.

Major Accomplishments:

  • My research resulted in four first-authored and four co-authored publications.
  • I successfully obtained research grants and fellowships to fund my research and studies including the prestigious National Science Foundation (NSF) Graduate Research Fellowship, the NSF Doctoral Dissertation Improvement Grant, and the American Association of University Women Graduate Fellowship.
  • I supervised over a dozen Masters students as well as one high school student and one undergrad in the lab.
  • I mentored one independent research Master’s project which resulted in a peer-reviewed first-authored publication for the student.
  • I co-designed and co-taught an undergraduate class “Feminism and Ecology” as well as guest lecturing and TAing several courses; received very good teaching evaluations.
  • I mentored three middle school girls for a PBS DragonflyTV “SciGirls” Episode.

What do we learn from this statement? Not only that Dr. Sutton-Grier was a kick-ass grad student (the academic interpretation), but also that she’s gained considerable professional experience in wetland restoration, that she can design and conduct research and produce written reports about it, that she can write grants, and that she has teaching and mentoring skills (the industry interpretation). Importantly, none of these achievements are diluted by calling attention to the fact she was a student in graduate school. Instead, she was a “Research Assistant, Instructor, and Mentor.” [1] If I had written this, I probably would have written “Researcher” instead of “Research Assistant”. Designing, carrying out, and writing up your own research means that you’re not actually an “assistant” in the colloquial meaning of the term.

If you’re a graduate student or recent PhD graduate – and especially if you don’t aspire to an academic career – I encourage you to start practicing seeing yourself as and speaking about yourself as a professional instead of a student right away. When you meet someone at a party or holiday gathering, and they ask you what you do, don’t start off with, “I’m an ecology graduate student,” or “I study ecology in graduate school,” or “I’m a postdoc.” [2] Nobody outside of academia has any real idea what a postdoc is, so it’s best to avoid the term anyway. Instead, whether you’re a grad student or postdoc, say “I’m a researcher at University of State. I study how plants are affected by climate warming,” or “I teach at University of State. I teach a lab on evolution,” or “I’m at University of State. I’m working out ways to avoid roadkill in conservation zones.”

If you get in the habit of viewing yourself as the professional that you are, it will be easier for others to see you that way, too, including in interviews and during networking opportunities. And it will be easier to make it clear in your resume that you have many years of professional experience, regardless of the fact you were a graduate student.

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The thing that pushed me to post a preprint

I have mixed feelings about preprints. On one hand, I like the fact that they allow for the exchange of ideas on pace with the rate that science happens. On the other hand, in ecology, the concept is preprints is all muddled. In the fields where preprints originated and are now standard practice (physics, math, astronomy, computer science), it is typical for authors to post preprint manuscripts to a public site (such as arXiv) as they’re finishing up a final draft or when they submit it to a peer-reviewed journal. Historically, the reason to do so was to have a nicely formatted version of the paper [1] since these fields use the lightweight TeX for writing and formatting that you could then point your colleagues to, enabling rapid dissemination of ideas within your research community. These days, it’s just as easy to email a PDF to colleagues who might be interested in your not-yet-published paper — and I suspect that this is the norm in ecology.

For fields like ecology where preprints are not the cultural norm, the idea of the preprint is getting swept up in the broader Open Science movement. Preprints are billed as a way to get early feedback and a step towards transparency. I rather doubt that the former happens a lot, even in fields where preprints are the norm, and I’m not sure that preprints help that much with transparency. In ecology, where being scooped is usually not a concern, preprints don’t even have the value of establishing first rights to a particular discovery. The only real benefits I see to preprints in ecology are for spreading science more quickly (everyone) and establishing yourself during the long waits while your first papers go through the publishing process (grad students, postdocs).

For me, preprints have always been one of those “I should probably do that because Open Science” things that I never get around to. When I finally finish a manuscript and submit it to a journal, the last thing I feel like doing is spending time on yet another online submission system to post a preprint. So I haven’t.

What has finally pushed me submit a preprint is the ridiculous amount of time it takes for some journals to go from “accept” to “publish.” I am all for peer-review and willing to take the time to do that properly. But it drives me crazy when a paper is accepted, but not actually published until nine months later.

I’m hopeful that as time goes on, all journals will make their way into the 21st century and post manuscripts as soon as they’re accepted. That will help speed up science dissemination. But right now, we’re far from that point. For papers I’ve been on (all in the past couple years), I’ve seen all of the following:

  1. Nothing happens until the paper “goes to press”. When it is published, it appears in print and on the website at about the same time. This can take many months.
  2. The paper is posted as a “preprint” to the journal’s website, but it isn’t considered “published” until a later date, often when it comes out in print.
  3. The paper is quickly posted online as an “online early view” and is considered “published,” but without a journal issue number or page numbers. Later, the paper is put out in print and gets these identifying numbers.
  4. The paper is quickly published online. There is no print version of the journal.

This medley of publishing practices is really confusing, and I very much hope it is just a transitional phase until all manuscripts are posted online shortly after acceptance and considered published right then.

Last week, I pinged the editor of Frontiers in Ecology and the Environment. The journal had accepted a paper of mine [2]with Andrea Wiggins, Ali Swanson, and Brooke Simmons in May, and I wanted to know when it might be published. I was told that it wasn’t even scheduled yet and we were looking at sometime in early 2017. Another nine-month wait! In a journal that is supposed to be at the “frontier.” Ugh. This paper was written in late 2015 and revised in the spring of 2016 (during which time some additional references were added). It will be somewhat out-of-date when it is finally published, as it won’t include literature from 2016.

This paper is on data quality in citizen science, so the content itself won’t be out-of-date, thankfully. But at the same time, I wrote this is paper because the field has needed such a paper for several years. This is a paper that after I spent two years immersing myself in finishing my dissertation, moving cross-country, and having a baby, I was surprised that no one else had written yet. I’ve promised this paper to colleagues to have something to cite — something to point to — to demonstrate due diligence for volunteer-provided data for proposals and in papers.

And so I posted a preprint. Now I can easily send it around to colleagues and they can easily cite it. Just like was done in mathematics back in the 1990’s.

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The Modern Grad Student Paradox

I was sitting in the audience during the discussion of the Hacking Ecology 2.0 Ignite session at ESA this year and Josie Simonis, who was on the panel, said something that really resonated with the grad students in the audience and on Twitter. They said that graduate students face a real paradox: grad students need to learn a lot of modern skills to succeed as scientists, but those who are their teachers (the faculty) don’t have the skills and knowledge to teach them.

What is the purpose of graduate school? It seems like a straightforward question at first, but for those pursuing graduate degrees in the sciences, at least, I think the answer is a lot more complex than it used to be. Because the words “school” and “student” are used, it’s reasonable to suppose the purpose of a graduate education is to learn. For a good chunk of an American PhD program – and for full programs in some other countries – that education doesn’t come in the form of classes, as it does for undergraduate education. Instead, the education is more of an apprenticeship – more like the residency that medical doctors undertake after all their classes are complete.

Let’s pretend that the sole purpose of graduate school in ecology is to create scientists who can fill the shoes of their advisors. [1] This is obviously false, as there are far more PhDs created than R1 faculty jobs that can absorb them. But for the purpose of the post, I want to focus on just the academic path. A newly minted assistant professor today probably spent about 10 years as a graduate student and postdoc. That puts the beginning of their professional training around 2005 (give or take), which is just shortly after the Internet took off as a ubiquitous agent of change. So only the very newest advisors came of (professional) age in what I’m going to call the modern research world. And all the rest – the great majority of tenured and tenure-track faculty – learned how to be scientists during a time when the Internet didn’t exist. (Think about that for a moment…)

I use the Internet as a yardstick, as well as an important driver of research culture. There are a lot of other technologies that have undergone enormous change in the past decade, too. Whatever your particular study system is, it’s likely that there are technological devices, tools, or machines that affect how research in that system has changed over the past decade. And even if your research is bare-bones basic – taxonomy, for example – you have still been affected. The plunging price of computer memory and processing power means that how scientific data is recorded, managed, curated, and accessed has changed.

What all this means is that today’s graduate students need to learn all sorts of things that their advisors can’t teach them. Most advisors haven’t had the time (and in some cases the inclination) to keep up with advances in hardware technology, data standards, software, statistics, and communication. I don’t see this as a shortcoming on the part of the advisors, by the way. Instead I see it as a manifestation of the 12 Hats Problem. But it is a very real conundrum for grad students.

What to do about this paradox? I think the first thing to do is to really assess whether graduate programs are meeting the needs of their students. [2] In this, of course, they need to consider not just those aiming for R1 faculty positions, but also students who will take other types of jobs. My whole time as a grad student – and ever since – I’ve heard a yearning from graduate students for more courses in coding and data management and ecologically relevant statistics. Even if there are teachers for these types of courses (and there often aren’t), there’s always the question of what part of the formal education to drop. My suggestion is to drop or condense requirements that focus on memorization. These days, with the Internet, one can look up a factual piece of information in moments. It simply isn’t worth it for most people to learn how many teeth different mammal skulls hold or to memorize plant families. [3] My emphasis here is on “most people.” There will always be niches of science in which it’s much more useful to have these facts in one’s head than at one’s fingertips. But those niches are quite small – not enough for entire courses. And those who need to memorize this information can do so in the apprentice part of the PhD, rather than the classroom part. I think objections to this come mostly from those who like teaching these sort of (sorry to say it) outdated courses.

One possible solution to the lack of teachers is peer training – that is, grad students (and others) training grad students. The Software Carpentry model is one to consider, in which grad students are trained as teachers and then team teach other students coding skills. Short courses and workshops also fill this gap, but have the downsides of typically being expensive to attend and requiring travel (which disenfranchises some groups of students). Another possibility is to leverage online cross-institution training. Perhaps, for example, there’s a faculty member who is perfect at teaching Needed Skill X. Instead of a class just for students at that teacher’s university, that teacher could open up the class online, allowing participation from students at multiple universities. [4] There exists technology to do this, but I’m relatively unfamiliar with it. For cross-university courses to catch on widely, such technology needs to be rather glitch-free and easy to use. Administrative matters, such as course credits and tuition, need to be addressed too. Perhaps one thing that departments should do is to assign faculty to learn specific skills so they can teach them to students subsequently. As in: “Hey, we’re eliminating your course load this year, but in exchange, we expect you to learn the latest in hierarchical Bayesian Statistics (or R coding or database creation and administration or…) and develop a graduate-level course (or workshop or whatever). You will be teaching it for the next five years, and you will be considered the department expert during that time.”

The apprenticeship part of the PhD still confers many important skills. Being able to read the literature critically, being able to ask a good research question, being able to think logically, being able to write – these are all timeless skills. But for the hard skills, we need a new paradigm – one that doesn’t leave graduate students flailing in a research environment that looks very different from the one their advisors grew up in.

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Online book club forming for “The Theory of Ecological Communities”

If you follow me on Twitter or obsessively read the comments of the Dynamic Ecology blog, you’ll know that I’ve been excited about the publication of Mark Vellend’s new book, The Theory of Ecological Communities, for many months. The book happened to come out just around the time of the ESA meeting, so the publishers rushed a half-dozen copies to the conference, one of which ended up in my suitcase. This year, my summer vacation follows ESA, and so this new book has become my vacation reading. Although I try to avoid working while on vacation [1] and with young children, a vacation is really just a “vacation” in name only – going into an office is way less exhausting than taking care of young ‘uns, I have not done well this time around. [2] A paper got through review faster than I was expecting, so I’ve worked on proofs; I got an unexpected and well-paid very-short-term contract job that I didn’t want to turn down; and I got excited about Mark’s book. Of course, what counts as “work” is a gray area, when you like your job, like most of us do. That’s not to say we like all parts of our jobs, though. So this vacation, I’m trying to not do the parts I don’t like, and allow myself to do some of the parts I do like. Like reading. (And, apparently, organizing a book club.)

Anyway, pre-child, I’d be done with The Theory of Ecological Communities by now. But I’m not because, well, I have little kids. Instead, I’m through the first of three sections of the book. And I’ve been enjoying it. A big fan of Vellend 2010, I found these first chapters went by quickly, mostly reviewing and fleshing out a bit the main tenets of the 2010 paper. They are quite clearly laying the groundwork for the next two sections, which I am very much looking forward to.

One big reason why I have been and continue to be excited about this book is that as a student I hungered for a way to organize my thinking about community ecology, and never felt satisfied. Coming into ecology with a strong math and computer background, but little ecological knowledge, I looked for how to conceptually organize the field. Where do I start? What classes should I take? What are the big questions of our time? I think I even asked my advisors directly about these things in the first couple years. The only organizing structure that I felt was compelling was the distinction among organismal biology, population ecology, community ecology, and ecosystem ecology. (I was unfamiliar with macrosystem ecology back then.) And that didn’t help me think about all the stuff within community ecology.

In the Tilman lab, everything was about competition. But in the Packer lab, behavior mattered. I took on a disease project, and found disease ecology to be almost its own field. When I spent time as a visiting grad student in the Leibold lab, suddenly dispersal was a much bigger deal than competition. I then got interested in food webs and predation. But I couldn’t figure out how to fit everything together into a coherent whole. I took an ecological theory class, but I couldn’t figure out where the forefront of the field was in order to try to contribute. I turned away from theory and did experimental and modeling work. And – to be very frank – my pure community ecology chapters from my dissertation are as yet unpublished because I can’t figure out how to frame them well within the general context of community ecology. The number of ideas and papers and models in community ecology have seemed so numerous and so vaguely connected that I feel like I can’t wrap my mind around them to see where my research fits.

As a result, Mark’s framework for fitting all of community ecology onto a simple scaffold is very appealing. I am actually reading the book with an eye to publishing one community ecology dissertation chapter, and it’s already helping to clarify my thinking. This book is also awesome for its references list. I seriously wish I could have read this book as a second-year grad student. The history chapter is brief, but cites most – if not all – of the big papers in community ecology that you should read as a community ecology grad student. I’ve put a few cited papers that I’ve overlooked on my must-read list. [3] The references list even includes a citation to a blog post, which makes me unreasonably happy. Maybe this is the first blog post citation in a Princeton Press monograph? Jeremy will have to buy the book to find out which post of his it is…

It turns out that I’m not the only one excited about The Theory of Ecological Communities. I handful of us who grabbed the book at ESA and others who ordered it directly decided via Twitter to start a “book club” – a discussion group where we read the book chapter-by-chapter and discuss it. Since we’re all over the place geographically, we decided to do video calls for our discussions. So I set up a sign-up sheet, figuring we might get 6 or 8 or 10 people who were interested – a group or two. But as of now, there are 28 people signed up, ranging from grad students to tenured profs and spanning three continents.

I totally was not planning to organize a large international book club on my vacation, but life is full of surprises. If you want to get in on the crazy experiment that is this book club, sign up and get the book. (You can order from Princeton Press or buy on Amazon. Interlibrary Loan takes longer, but is cheaper.) The first discussion groups will begin next week, but I’m pretty sure there are going to be more groups starting mid-to-late September, as there are several people who haven’t been able to get the book yet who want to talk about it. The idea is to read a chapter per week and meet for an hour to discuss. That’s about it.

I’ve really enjoyed the two book discussion groups I’ve been part of as an ecologist (reading this and this). Those have been in-person, though, so we’ll see how online groups work out. If you’ve got any experience with online book discussion groups – or any pointers in general – please do leave a comment below.

Sign up for The Theory of Ecological Communities Book Club

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Seasons of the Scientific Conference

Maybe one or more of these sound familiar?

Newbie. You’re an undergrad or a brand new grad student or something in between. There’s a big regional or national conference nearby and it costs relatively little for you to go. So you go! You spend hours poring over the program, looking for the talks that seem awesome. Except they all do. You write out a complicated schedule of talks you Must Not Miss and fill every minute of every day. You know no one — or maybe one other person, also a newbie. You dress casually because you don’t want to attract attention. Or you over-dress because you don”t want to attract attention, and then realize too late what ecologists wear to conferences. You keep busy keeping to your schedule, head down in the halls, bee-lining for the next talk on your list. The talks themselves leave you amazed and awed. Everyone is doing amazing work. Every Single Talk inspires you, as you expected them to. Ecology research is so cool and you can’t wait to dive in to do your own.

Missed chance. You finally have research to present at a national or international meeting! But you can’t go unless you find funding. And you can’t find funding. OR… there is funding, but it requires that you present at the conference. No problem, except you weren’t able to submit an abstract because life interfered. You gave birth just before the abstract-submission window and could barely function, never mind write an abstract. Or your closest friend died and you could barely function, never mind write an abstract. Or your chronic health condition flared up and you could barely function, never mind write an abstract. OR… you submitted an abstract, but you can’t actually attend the conference because you’re pregnant and on bed rest. Or you need to take care of your aging father who has taken a turn for the worse. Or you can’t afford to take your infant and you can’t afford to leave your infant behind. In the end, you don’t really mind missing the conference. After all, there were more important things to take care of. Except you really do.

First-time talk. You’re a few years into your PhD or finishing up your Masters (or maybe earlier in your degree if you did substantial undergraduate research). You’ve submitted an abstract, found funds to attend the conference, and are all ready to go. You know a bunch of people now, mostly people at your own institution, and it’s nice to run into them in the halls and to hang out at dinner. But you still spend most of your time attending talks and worrying about your own. Your own first conference talk feels weirdly anti-climactic. You’ve spent a lot of time prepping it and you’ve been worried about the follow-up questions. But in the end, the three questions are all polite and cover angles you’ve thought about. You field them without a problem. After the talk is over, no one approaches you to talk about it. It’s over and done. All the other talks you go to are good. But they’re not amazing, like you remember them being when you were a newbie. As you watch one, you’re horrified at the methods or statistics. “No, no, no,” you silently say to yourself. “You can’t do that!” You calculate that about 80% of the talks are good, but not amazing, and you include your own in that group. About 10% have serious flaws. And the other 10% you find inspiring. You wonder why ecology research has really stagnated in the past few years. And then you have a revelation: it’s not ecology research that’s changed; it’s you! You’re finally getting the hang of it, and are starting to recognize the merit and limitations of others’ research.

Unintentional networking. You’ve been to a couple conferences now and don’t feel quite so intimidated as the first times. You know what to wear. You know how things go. You prep your talk, but are more interested in what you’ll see and learn than presenting your own material. You still spend a lot of time looking through the program to find the talks you’ll like the most, but you’re starting to get a bit picky. When you arrive, you realize that your network has expanded, and that you know people from other institutions. You meet someone face-to-face who you’ve only known online. For the first time, you go out to dinner with a group that include people you haven’t yet met. You start to expand your network. On the way to a talk you really want to see, you run into someone you haven’t seen for a couple years. You’re torn, but end up skipping the talk and chatting with your friend for a half-hour. It’s a great chat. Other people pass by and you end up talking with friends of your friend, and before you know it, you’ve missed all the talks you wanted to see that afternoon, but have run into several old friends and met a dozen new ones. You go out to dinner and outline a novel research paper with one of these new friends. By the end of the conference you’ve had another revelation. This time: conferences aren’t about talks, they’re about people.

Intensive intentional networking. You’re a year or less away from defending your dissertation and you need a job! Your goal at this conference is to meet as many people as possible who might be interested in hiring you or writing a grant proposal with you. You prepped for this conference by making lists of people you want to meet and then cold-emailing them to see if you can chat with them at the conference. Every Single One who is attending says yes, because ecologists are super nice. Your schedule is packed with one-on-one meetings, and you only just start looking at the program on the flight to the conference. You’re more nervous about your meetings than your talk. Oh, man, your talk! You put down the program and write your talk on the plane. You spend the days meeting with more senior folks, trying to impress them, trying to figure out the place your research interests best overlap, and trying to figure out if they have any money. You spend your evenings catching up with friends and colleagues and trying to relax before the next day’s one-on-one meetings. When the conferences is over, you’re exhausted, but have a bunch of leads on possible jobs and grants. Plus you’ve met some great people and talked about some exciting research.

Conference regular. You’ve got your PhD in hand and a job, even if it’s temporary. You’ve been to conferences for a while now, and have a good sense of what you like best about them. You balance seeing talks you think will be inspiring with networking with old and new friends and colleagues. You’ve developed a method for picking talks that you’ll like and it works pretty well. You’ve got a talk or two to present this time, and you even organized a session. You plan ahead to meet a few new folks, and you take time to bring uncomfortable-looking students into conversations. One of them even stops you to chat about your talk in the hallways. Somehow, the same topic keeps coming up when talking with different groups of people, and you decide that a paper needs to be written on it. The conference is exciting and invigorating, and you leave with ideas for future research directions.

Do you have any to add? The “Conference gone terribly wrong”? “Selling your first book”? “Conference as an old hand”? Add your own in the comments.

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The postdoc pay cut

One beneficial thing about working out in the “real world” before starting a PhD is that you have the perspective of academia within the larger world, rather than academia as the only thing you’ve ever known. If you’ve gone from grade school to college directly on to grad school, you may not realize what a bizarre world academia is. Academia is the only place I know of where an organization makes substantial investments in its employees’ [1] I mean grad students here training and education and then as soon as they’ve shown mastery, casts them away. After graduating from college, I worked for the government. There, I was in a 3-year training program. I had classes and hands-on learning experiences. I did rotations through different offices to learn about the organization, its mission, and to develop my skills. I was paid like a regular employee, because I was seen as an investment; once I was through training, I was quite valuable to the organization.

Contrast that with graduate school. The good people of Minnesota spent more than $50,000 on my graduate education. The U.S. government upwards of $100,000. I consumed countless hours of time of senior faculty, whose time could otherwise have been spent doing research. When I defended (i.e. showed mastery), I was essentially fired, just as everyone is. My husband and I loved living in Minnesota. We would have been glad to give back to our adopted state by doing our research there, bringing in grants and using our newly developed skills to bring whatever honors to the state we could. But that was never an option. Weirdly, many states spend a lot of effort to keep their college graduates in-state. But they kick their newly minted PhDs out the door – and out of the state – as quickly as possible.

I think the most perverse part of the academic system is that postdocs actually take a pay cut compared to their pay as graduate students. Ecology graduate students frequently support themselves on teaching or research assistantships (TAs and RAs). The usual TA and RA arrangement is a “half-time” appointment; that is, an expectation of about 20 hours per week. For this work, they are typically paid from about $8,000 to $13,000 per semester, depending on location, cost of living, and institutional resources. Assuming grad students can find additional money to cover the summer months, they live on $20,000 to $34,000 per year. [2] NSF’s graduate research fellowship stipend is $34,000, matching the highest-paid TA/RAs This isn’t a lot – especially for areas with a high cost of living – but it’s usually (just) enough to live on for people with no dependents. And because the pay is for half-time work, the actual pay rate is $40,000 to $68,000 per year, which is quite reasonable for high-quality workers in their early-to-mid twenties.

What happens when ecology grad students become postdocs is something of a cruel joke. They take a huge pay cut. Now, they’re expected to work full-time. But they only get paid $40,000 to $45,000 per year with their advanced skills, knowledge, and qualifications. That’s a 33% pay cut for those with the highest grad student earnings. [3] As an example, I went from a $30,000/year grad fellowship (which substitutes for a half-time appointment, so has an actual pay rate of $60,000/year) to a $50,000/year postdoc – an excellent rate for ecology, but nevertheless a pay cut of $10,000.

Why do we as a community put up with it? I think the pay cut happens, in part, because of complacency on the part of people in power – “this is how it’s always been, so this is the way it has to be.” And in part, because economic forces: there are many people who are willing to work for low pay. And in part, because of a lack of awareness. Many new postdocs are so glad to have “more money” in absolute terms, they don’t stop to realize that they’re being cheated. Many (most?) academic ecologists (and likely scientists in some other fields) have no concept of their market value. [4] By the way, this is nothing unique to ecology; it’s just easier for me to find numbers in the field I’m most familiar with. NIH has a schedule for how much its postdocs should be paid. You can see that low pay relative to qualifications is institutionalized with this schedule. Initial postdoc stipend set around $50,000? The types of academic high-achievers who go to grad school could make this much salary immediately out of college in many urban areas.

Here’s a quick-and-easy way to figure out your own minimum value outside academia with a PhD: Go to the U.S. government’s salary schedules, choose your location, open the PDF or webpage under “Annual Rate,” and look at the value in the chart for Grade 11, Step 1.

These tables are the pay rates for U.S. government employees worldwide and they’re based on competitive rates with industry. In other words, they’re a reasonable estimate of what you should be paid based on your credentials, location, and experience. Grade 11, Step 1 is the absolute minimum you could be hired by the government with a PhD in hand. If you’ve got any additional work experience or specialized skills (e.g. statistics, coding, discipline-specific skills), you could expect higher steps and/or grades. [5] Assume a minimum of one step per year of experience. On top of that, the government has a bunch of special rates for individuals with specific specialized skills. If you could classify yourself as a “biological scientist,” “natural resource specialist,” “plant protection technician,” “soil conservationist,” “forestry technician,” “soil scientist,” “geologist,” or “oceanographer,” there’s a special (higher) rate for you.

According to these charts, my worth as a PhD-holding resident of the Boston area with 2.5 years of postdoctoral experience means that I’m worth about $15,000 more than I’m being paid. At minimum. [6] Please note that I am not complaining about my personal situation. I make the choice voluntarily to stay in this job – with my eyes wide open – for a multitude of complex reasons. My goal with this post is raise awareness of the job worth and market value of postdocs, as I believe academia as a system purposefully shrouds this information to enable exploitation of highly skilled labor.

How about you?

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Most ESA Early Career Fellows are almost mid-career

The Ecological Society of America recently announced its call for nominations for awards for 2017. I encourage you to get out there and nominate people. In particular, consider nominating folks that are historically underrepresented. [1] For the Early Career Fellows, consider nominating someone at a comprehensive university, primarily undergraduate university, or in the private sector. As an early career researcher, I feel a bit intimidated by the idea of nominating folks for the heavy-weight awards such as the Eminent Ecologist Award and MacArthur Award. But there are plenty of other ones to choose from, if you are an early career research like me.

Last year, I nominated someone as an Early Career Fellow. While that person was not named a Fellow, those who were are quite impressive. In looking over the list, I began to think that maybe I had misjudged my nomination. It’s not that the person I nominated hasn’t done awesome things, but rather those who were named as Fellows were quite a bit more senior than my nominee. If true generally, this would be a big deal for nominators. Putting together a nomination for any of the ESA awards is fairly time consuming, and so it doesn’t make a lot of sense to try to nominate someone who is almost certainly going to be out of the running.

So I dug into the data. [2] Specifically, I scoured the web for data on Early Career Fellows. Most have professional web pages. Many have CVs online. The rest have information on social media sites like LinkedIn. And my initial hunch was right. ESA states that Early Career Fellows must be non-students who are no more than eight years past their PhD degree date when they are selected. But all 27 existing Early Career Fellows were at least four years past their PhD degree date when selected, and 70% were at least seven years past their PhD degree date. [3] I am not sure why 3 Fellows were 9 years past a PhD. My guess is that the time between nomination and award announcement (6-9 months) accounts for it. Either that, or 8 years isn’t a hard cut-off. Or the awards committee doesn’t bother to verify that nominees adhere to the 8 year limit. My nominee, by contrast, had received a PhD fewer than four years earlier.


I interpret this to mean that the awards committee for Early Career Fellows looks at all nominees on an even playing field, without accounting for career length. An alternative way potential fellows might be judged is to account for time since PhD. For example, NSF committees judging applicants for the NSF Graduate Research Fellowship are supposed to take into consideration whether applicants are not yet in graduate school, are first year grad students, or are second year grad students. This is because we would expect differing levels of proposal sophistication among these groups, and it wouldn’t be fair to judge the best second year grad students against the best not-yet-grad-school applicants.

Likewise, a great researcher with just dissertation work and a year or two of postdoc experience isn’t going to be competitive with a great researcher who has an additional six years of experience. I’m not necessarily advocating that the selection committee for Early Career Fellows should take into account time since PhD. There are pros and cons of doing so. I do hope, however, that ESA leadership understands how nominees are being judged and that it feels comfortable that the judging methods align with the goals of this honor.

One thing that is clear, though, is that most Early Career Fellows are spending a sizable chunk of their 5-year honorific fellowship as mid-career ecologists. Here are the professional titles that Fellows held at the time the award was conferred:


Of the 17 Assistant Professors, I was able to calculate the number of years each Fellow had been an Assistant Professor for 16 of them. On average, Fellows had been Assistant Professors for four years when they were named Early Career Fellows (mean = 3.8, median = 4):


What this means for you as a nominator is that you should probably not bother nominating postdocs or other researchers in early temporary positions for this award. The most competitive nominees are going to be those six to eight years out from their PhD who have been in permanent positions for at least three years at the time of nomination.

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