Busy-o-Meter

I’ve posted before about some of my organizational approaches (and attempts at it) but it can sometimes be impossible not to get overwhelmed and busy. Being busy on multiple tasks, with multiple deadlines can be a killer, but sometimes it crystallizes a resolve to move some of those items off your todo list and you increase your overall effectiveness (you know, less Twitter and blogging and comic-making and stuff). I’ve also seen people who seem to make it a part of their academic persona to be perpetually too busy. This seems to be considered a status symbol (often times mostly by the person being so busy). The key to busy-ness and keeping your head above water (and the seals at bay) is balance. Make sure to keep perspective about what you’re doing and know that often (maybe always) banging your head against the same task for hours on end is counterproductive.

Anyway, here’s a handy tool to help you assess your level of busy-ness, fresh from the RedPen/BlackPen labs.

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AlternateScienceMetrics that might actually work

Last week an actual, real-life, if-pretty-satirical paper was published by Neil Hall in Genome Biology (really? really)  ‘The Kardashian index: a measure of discrepant social media profile for scientists’, in which he proposed a metric of impact that relates the number of Twitter followers to the number of citations of papers in scientific journals. The idea being that there are scientists who are “overvalued” because they Tweet more than they are cited- and drawing a parallel with the career of a Kardashian, who are famous, but not for having done anything truly important (you know like throwing a ball real good, or looking chiseled and handsome on a movie screen).

For those not in the sciences or not obsessed with publication metrics this is a reaction to the commonly used h-index, a measure of scientific productivity. Here ‘productivity’ is traditionally viewed as being publications in scientific journals, and the number of times your work gets cited (referenced) in other published papers is seen as a measure of your ‘impact’. The h-index is calculated as the number of papers you’ve published with citations equal to or greater than that number. So if I’ve published 10 papers I rank these by number of citations and find that only 5 of those papers have 5 or more citations and thus my h-index is 5. There is A LOT of debate about this metric and it’s uses which include making decisions for tenure/promotion and hiring.

Well, the paper itself has drawn quite a bit of well-placed criticism and prompted a brilliant correction from Red Ink. Though I sympathize with Neil Hall and think he actually did a good thing to prompt all the discussion and it was really satire (his paper is mostly a journal-based troll)- the criticism is really spot on. First off for the idea that Twitter activity is less impactful than publishing in scientific journals, a concept that seems positively quaint, outdated, and wrong-headed about scientific communication (a good post here about that). This idea also prompted a blog post from Keith Bradnam who suggested that we could look at the Kardashian Index much more productively if we flipped it on it’s head and proposed the Tesla index, or a measure of scientific isolation. Possibly this is what Dr. Hall had in mind when he wrote it. Second, that Kim Kardashian has “not achieved anything consequential in science, politics or the arts” and “is one of the most followed people on twitter” and this is a bad thing. Also that the joke “punches down” and thus isn’t really funny- as put here. I have numerous thoughts on this one from many aspects of pop culture but won’t go in to those here.

So the paper spawned a hashtag, #AlternateScienceMetrics#AlternateScienceMetrics, where scientists and others suggested other funny (and sometimes celebrity-named) metrics for evaluating scientific impact or other things. These are really funny and you can check out summaries here and here and a storify here. I tweeted one of these (see below) that has now become my most retweeted Tweet (quite modest by most standards, but hey over 100 RTs!). This got me thinking, how many of these ideas would actually work? That is, how many #AlternateScienceMetrics could be reasonably and objectively calculated and what useful information would these tell us? I combed through the suggestions to highlight some of these here- and I note that there is some sarcasm/satire hiding here and there too. You’ve been warned.

    • Name: The Kanye Index
    • What it is: Number of self citations/number of total citations
    • What it tells you: How much does an author cite their own work.
    • The good: High index means that the authors value their own work and are likely building on their previous work
    • The bad: The authors are blowing their own horn and trying to inflate their own h-indices.

    This is actually something that people think about seriously as pointed out in this discussion (h/t PLoS Labs). Essentially from this analysis it looks like self-citations in life science papers are low relative to other disciplines: 21% of all citations in life science papers are self-citations, but this is *double* in engineering where 42% of citations are self citations. The point is that self-citations aren’t a bad thing- they allow important promotion of visibility and artificially suppressing self-citation may not be a good thing. I use self citations since a lot of times my current work (that’s being described) builds on the previous work, which is the most relevant to cite (generally along with other papers that are not from my group too). Ironically, this the first entry in my list of potentially useful #AlternateScienceMetrics is a self reference.


    • Name: The Tesla Index
    • What it is: Number of Twitter followers/number of total citations
    • What it tells you: Balance of social media presence with traditional scientific publications.
    • The good: High index means you value social media for scientific outreach
    • The bad: The authors spend more time on the social media than doing ‘real’ scientific work.

    I personally like Keith Bradnam’s Tesla Index to measure scientific isolation (essentially the number of citations you have divided by the number of Twitter followers). I see that the importance of traditional scientific journals as THE way to disseminate your science is waning. They are still important and lend an air of confidence to the conclusions stated there, which may or may not be well-founded, but there is a lot of very important scientific discussion that is happening elsewhere. Even in terms of how we find out about scientific studies published in traditional journals outlets like Twitter are playing increasingly important roles. So, increasingly, a measure of scientific isolation might be important.


    • Name: The Bechdel Index
    • What it is: Number of papers with two or more women coauthors
    • High: You’re helping to effect a positive change.
    • Low: You’re not paying attention to the gender disparities in the sciences.

    The Bechdel Index is a great suggestion and has a body of work behind it. I’ve posted about some of these issues here and here. Essentially looking at issues of gender discrepancies in science and the scientific literature. There are some starter overviews of these problems here and here, but it’s a really big issue. As an example  one of these studies shows that the number of times a work is cited is correlated with the gender of its first author- which is pretty staggering if you think about it.


    • Name: The Similarity Index
    • What it is: Some kind of similarity measure in the papers you’ve published
    • What it tells you: How much you recycle very similar text and work.
    • The good: Low index would indicate a diversity and novelty in your work and writing.
    • The bad: High index indicates that you plagiarize from yourself and/or that you tend to try to milk a project for as much as it’s worth.

    Interestingly I actually found a great example of this and blogged about it here. The group I found (all sharing the surname of Katoh) have an h-index of over 50 achieved by publishing a whole bunch of essentially identical papers (which are essentially useless).


    • Name: The Never Ending Story Index
    • What it is: Time in review multiplied by number of resubmissions
    • What it tells you: How difficult it was to get this paper published.
    • The good: Small numbers might mean you’re really good at writing good papers the first time.
    • The bad: Large numbers would mean you spend a LOT of time revising your paper.

    This can be difficult information to get, though some journals do report these (PLoS Journals will give you time in review. I’ve also gathered that data for my own papers – I blogged about it here.


    • Name: Rejection Index
    • What it is: Percentage of papers you’ve had published relative to rejected. I would amend to make it published/all papers so it’d be a percentage (see second Tweet below).
    • What it tells you: How hard you’re trying?
    • High: You are rocking it and very rarely get papers rejected. Alternatively you are extremely cautious and probably don’t publish a lot. Could be an indication of a perfectionist.
    • Low: Trying really hard and getting shot down a lot. Or you have a lot of irons in the fire and not too concerned with how individual papers fare.

    Like the previous metric this one would be hard to track and would require self reporting from individual authors. Although you could probably get some of this information (at a broad level) from journals who report their percentage of accepted papers- that doesn’t tell you about individual authors though.


    • Name: The Teaching/Research Metric
    • What it is: Maybe hours spent teaching divided by hours in research
    • What it tells you: How much of your effort is devoted to activity that should result in papers.

    This is a good idea and points out something that I think a lot of professors with teaching duties have to balance (I’m not one of them, but pretty sure this is true). I’d bet they sometimes feel that their teaching load is something that is expected, but not taken into account when the publication metrics are looked evaluated.  


    • Name: The MENDEL Index
    • What it is: Score of your paper divided by the impact factor of the journal where it was published
    • What it tells you: If your papers are being targeted at appropriate journals.
    • High: Indicates that your paper is more impactful than the average paper published in the journal.
    • Low: Indicates your paper is less impactful than the average paper published in the journal.

    I’ve done this kind of analysis on my own publications (read about it here) and stratified my publications by career stage (graduate student, post-doc, PI). This showed that my impact (by this measure) has continued to increase- which is good!


    • Name: The Two-Body Factor
    • What it is: Number of citations you have versus number of citations your spouse has.
    • What it tells you: For two career scientists this could indicate who might be the ‘trailing’ spouse (though see below).
    • High: You’re more impactful than your spouse.
    • Low: Your spouse is more impactful than you.

    This is an interesting idea for a metric for an important problem. But it’s not likely that it would really address any specific problem- I mean if you’re in this relationship you probably already know what’s up, right? And if you’re not in the same sub-sub-sub discipline as your spouse it’s unlikely that the comparison would really be fair. If you’re looking for jobs it is perfectly reasonable that the spouse with a lower number of citations could be more highly sought after because they fit what the job is looking for very well. My wife, who is now a nurse, and I could calculate this factor, but the only papers she has her name on my name is on as well.


    • Name: The Clique Index
    • What it is: Your citations relative to your friend’s citations
    • What it tells you: Where you are in the pecking order of your close friends (with regard to publications).
    • High: You are a sciencing god among your friends. They all want to be coauthors with you to increase their citations.
    • Low: Maybe hoping that some of your friends’ success will rub off on you?

    Or maybe you just like your friends and don’t really care what their citation numbers are like (but still totally check on them regularly. You know, just for ‘fun’)


    • Name: The Monogamy Index
    • What it is: Percentage of papers published in a single journal.
    • What it tells you: Not sure. Could be an indicator that you are in such a specific sub-sub-sub-sub-field that you can only publish in that one journal. Or that you really like that one journal. Or that the chief editor of that one journal is your mom.

    • Name: The Atomic Index
    • What it is: Number of papers published relative to the total number of papers you should have published.
    • What it tells you: Are you parsing up your work appropriately.
    • High: You tend to take apart studies that should be one paper and break them into chunks. Probably to pad your CV.
    • Low: Maybe you should think about breaking up that 25 page, 15 figure, 12 experiment paper into a couple of smaller ones?

    This would be a very useful metric but I can’t see how you could really calculate it, aside from manually going through papers and evaluating.


    • Name: The Irrelevance Factor
    • What it is: Citations divided by number of years the paper has been published. I suggest adding in a weighting factor for years since publication to increase the utility of this metric.
    • What it tells you: How much long-term impact are you having on the field?
    • High: Your paper(s) has a long term impact and it’s still being cited even years later.
    • Low: Your paper was a flash in the pan or it never was very impactful (in terms of other people reading it and citing it). Or you’re an under-recognized genius. Spend more time self-citing and promoting your work on Twitter!

    My reformulation would look something like this: sum(Cy*(y*w)), where Cy is the citations for year y (where 1 is first year of publication) and w is a weighting factor. You could have w be a nonlinear function of some kind if you wanted to get fancy.

 

 

So if you’ve made it to this point here’s my summary. There are a lot of potentially useful metrics that evaluate different aspects of scientific productivity and/or weight for and against particular confounding factors. As humans we LOVE to have one single metric to look at and summarize everything. This is not how the world works. At all. But there we are. There are some very good efforts to try to change the ways that we, as scientists, evaluate our impact including ImpactStory and there’ve been many suggestions of much more complicated metrics than what I’ve described here if you’re interested. 

Have laptop, will travel

One of the great things about being a purely computational researcher is that, nowadays, my office is pretty much wherever I want it to be. I’ve got my laptop, WiFi is omnipresent, and I have noise-canceling headphones for the serious business. There are lots of reasons that I have to be at my office – meetings and increased ability to focus being primary. However, it’s not the case that you have to be purely computational to get a lot out of working in non-traditional locales. Writing is the place where we all (as researchers) can do this. Writing manuscripts and grants being the biggest time sucks. Some of you will have the ability to be flexible in your actual work time, others this might pertain mostly to the ‘extra’ work you do writing grants and papers.

So here is my random collection of thoughts on this topic.

Why take your work outside the standard work environment?

  1. Flexibility and efficient use of time. If you have your laptop with you you can fit in writing wherever you are (see list below). This allows you to use your time well instead of standing around checking Facebook on your phone. Not all writing work is  suited for the short bits of time (probably no less than about 20-30 minutes at a time) but if you plan what to work on you can get a lot done this way. If you don’t have your laptop a surprising amount of work can get done with just a pen and paper.
  2. Freedom from distraction. OK, a coffee shop can be a pretty distracting place, that’s a given. But sometimes being in your office can be pretty distracting too. People stop by to chat for a minute, phones ring, drawers need organizing, etc. If you can ignore the distractions outside your office (wherever you’re choosing to work) then this can be a productive way to go. Also, try working somewhere WITHOUT WiFi (it can be done)- and cut out the social media chatter.
  3. Creative stimulation. Changing your work environment drastically can give you a shot of creative energy. It can be refreshing wot work outside at a park, or while enjoying a glass of your favorite beverage at a cafe or bar.

What to work on?

  1. Grants
  2. Manuscripts
  3. Reviewing papers/grants
  4. Catching up on answering emails
  5. Reading papers- no laptop required
  6. Planning and outlining- also no laptop required, use a pen and notebook

Where can you do this?

  1. Coffee shop. Everyone pretty much knows about this one. Can be distracting, but find a quiet corner and bring headphones. Also, try not to drink 15 double espressos while you’re there (not that I would have ANY experience with that)
  2. The Mad Scientist enjoying a beer after a long day meeting and about to do some grant writing at a McMenamin's pub in Portland

    The Mad Scientist enjoying a beer after a long day meeting and about to do some grant writing at a McMenamin’s pub in Portland

    Bar/pub. These can be awesome places to work- probably not on a Friday or Saturday night, but other times. Many have WiFi and they have BEER! Also, try not to drink 8 beers while you’re there. Alcohol is actually a consideration since it can affect your motivation pretty severely. Ordering ONE beer and some food works OK for me, but certainly use your best judgement- and they will always have alternate non-alcoholic beverage options.

  3. Public library. This is really just a no-brainer. No cost (though many libraries have coffee shops attached and allow you to bring covered cups in), free WiFi, lots of sitting areas, quiet atmosphere, surrounded by the smell of knowledge.
  4. Park. Working outside is sometimes really nice in nice weather. If you’re lucky enough to have workable weather (not too hot, not too cold, not too windy or rainy) then find a table in the shade and settle in. I’ve never found this particularly effective myself, though the idea is wonderful, but I’m sure it could work for others.
  5. Doctor/dentist office, DMV, etc. This option is one I use quite a bit, but it only works for things that you can do a little bit on before being interrupted. I find that making todo lists and outlines work well here. Also reading background material can also work well.
  6. Car. Not while you’re driving! I mean if you’re sitting and waiting for something or someone this can be a good time too.
  7. Public transportation. When I was in Seattle I rode the commuter train in from Everett to work several times a week. A great place to work. An hour of uninterrupted time while beautiful countryside rolls by. Buses can work too, though not always for actual writing since often they bump and move too much for a laptop. Subways/metros also work well. Of course, this is pretty dependent on the density of people. It’s really hard to do anything productive when you have an elbow in your face and about 6 inches of standing room.
  8. *that's me in the seat behind Rex, by the way.

    *that’s me in the seat behind Rex, by the way.

    Airplane/airport. So much wasted time in airports- which are great places to work if you find the right spots. Airplanes can be a bit problematic in terms of an actual laptop (I find I can do it if I type like a T-rex) but I bring papers to read and a notebook to do planning and write ideas. In airports try to find places where there aren’t many people- away from your departing gate if you have time. More chance of getting a power outlet and fewer distractions. If you’re really in need of an outlet try looking in places where other people aren’t going to be sitting (hallways and walkways) and sit on the floor- it can be done.

  9. Hotel. Also in the traveling realm. Hotels can be excellent places to write. Free from a lot of the distractions and obligations of home and office. If you have extra time after a day at a conference or between sessions or before you catch your plane- use it. Many hotels are set up with desks, comfy chairs, outlets, coffee makers, and WiFi. When I travel to the east coast and my return flight is early I will frequently work through the night. Not for everyone, but I’m a night owl and I find it easier to do this (sometimes) than to sleep for a few hours then drag myself out of bed at 5 AM (3 AM my time) to get to the airport. Also, no danger of oversleeping – unless of course you accidentally crash. So if you do this make sure to arrange a wake up call and set an alarm for backup.
  10. Other locations. Be on the lookout for other opportunities. I have worked on a grant while pouring wine for a wine tasting at a friend’s house (not a wine-tasting party, mind you- this was a professional activity, so quite a bit of down time). That was pretty epic really but it still didn’t get my grant funded.

 

 

The Daily Quest for Productivity

Productivity. That elusive goal of any work day. But somehow the more you want to get done the more obstacles seem to get thrown into your path. Some are small and annoying but others can sink your entire day to the bottom of the ocean.

Here are some of the things that I do to improve my productivity:

  1. Keep a running todo list. I keep a list of things to do open all the time on my computer. I work at my computer, so that makes it a bit easier. I prioritize the list by importance and/or urgency. I make a note of deadlines if applicable. I mark things off when I’ve finished them and use a “+” mark for things that I’ve started to do (I’ve sent an email but haven’t yet received a reply, for example). This is from small stuff to big stuff, sometimes it’s organized in projects – with subheadings for subtasks – other times as individual items. I save a new file each week and update the list at the start of the week, removing those items that are finished and adding new items. I can visit the list when I can’t figure out what to do. It really gives me a sense of satisfaction to mark those things off. I’m being PRODUCTIVE!
  2. Keep longer term goals and achievements list. In the same todo document I also keep a list of my goals and achievements: papers I’ve started, submitted, or gotten published for the year, grants I’m planning or have submitted, conferences and talks I’m scheduled for or have attended, etc. This part really helps me keep me on task on a more career-oriented time scale and gives me a nice positive reinforcement for what I have done.
  3. Turn off social media. When I need to be productive I turn it off. No Facebook. No Twitter. No nothing. Of course, I get updates from my OS (Mac) and likely many people get updates from their phones. If you can turn these updates off (you can) then do that. Give yourself a goal and then reward with a defined amount of time that you can check your updates. This is really hard to do.
  4. Find your productivity soundtrack. I have writing music. I have grant music. I have programming music. Most of it is stuff that doesn’t require much thought and that I’ve listened to 1000s of times before. This works well for me.
  5. Take active breaks. I’ve been getting up to take walks for fitness reasons but I’ve found that this is an excellent way to improve productivity. A well-timed walk alone can prompt my mind to organize and brainstorm and plan. When I get back to my desk I’m waaaay more productive than when I left. I don’t know that it works for everyone- but certainly beating your head against a brick wall won’t help.
  6. Move between tasks. If you’re stalling at one task, take a “break” and work on another task for a bit. This can help get things moving and, like point 5, make sure you’re not butting up against a wall.
  7. Block out chunks of time. On the other hand, for many projects I find I need to block out pretty sizable chunks of time to be able to focus and actually move something forward. Working on something for 10 minutes every hour for a day does NOT generally equal 1.4 hours of solid work.
The Daily Quest For Productivity

The Daily Quest For Productivity