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Science Moneyball: The Secret to a Successful Academic Career
sciencehabit (1205606) writes "For biomedical researchers who aspire to run their own labs, the secret is to publish frequently, as first author, and in top journals. That career advice may seem obvious, but this time it's backed up by a new analysis of data scraped from PubMed, the massive public repository of biological abstracts. The study, reported today in Current Biology, uses the status of last author as a proxy for academic success. Those corresponding authors are likely to be running their own labs, the brass ring that young researchers are trying to grab. See what your chances are using Science's PI Predictor graph."
It turns out that the secret for success in the stock market is to buy low and sell high. Get to it, folks.
Correlation is not causation.
Really publishing quality results is what will get you that and being the guy behind the projects will more often than not get you the lead author spot.
... low hanging scientific fruit it appears. Since any serious science problem is going to be non-trivial. No doubt this 'success' is all about chasing low hanging fruit to get money.
That article is so full of fail it's not even funny.
I'm well beyond the limits of that graph, with something like 15 or 20 articles as a first author. Still looking for a PI job.
And I've seen first hand that some grad students are promised a PI job long before they even finish theire Ph.D. or publish anything significant.
For tennis players who aspire to be successful (e.g. get lots of endorsements, etc), the secret is to win lots of tennis tournaments and preferably grand slams. That career advice may seem obvious, but this time it's backed up by a new analysis of tournament data.
So now the question becomes whether the tennis players became successful because they employed the strategy of winning lots of tournaments, or whether some 3rd factor (like raw talent and/or work ethic) somehow caused both the winning of tournaments *and* the success. Looking at tournament data is not going to tell you this.
In order to get to the bottom of this, you need to do something like simple random sampling. You might randomly select players to win tennis tournaments, independently of their skill. Lets say we declare the winner of Wimbledon based on a lottery for a few years rather than by having a skill based tournament, and see how many tennis endorsements the winners get, compared with the winners of other grand slams that are based on skill.
If the winners of the Wimbledon lottery get just as many tennis endorsements as the US/French/Australian open winners, then we might conclude that winning tournaments is what causes a players success.
As a PI, I would normally get a kick out of these replies, but I'm too busy writing a grant and have to get back to work . . .
That I'll get the job I have now.
I'm not at a major university, I'm at a large agricultural NGO with my own lab of 11 researchers and a PhD student who is hosted at the uni down the street. However, according to their model there's less than 80% chance that I'll become a PI.
I'd be interested to know what's different. I realise that it's a model, thus it's wrong. Still, I guess ~80% is a pretty strong relationship for something like this. It was fun to try.
... found that athletes that win almost all their events at a national level tend to make it to the olympics. Further, if they win or are close to winning in each event at the olympics, they often medal. Fascinating research.
I found this part interesting, as it is a question I've been wondering about. It may directly affect my career - soon.
TFA said:
> a large number of publications in low-ranking journals can be just as good as a few in the big ones. That’s “perhaps the most interesting finding,”
That is indeed interesting. I work on the fringes of academia, where most people don't publish at all, but the boss certainly wants people to. So I'm just starting to learn about how to get my work out there. Number if citations matters, I've read, so now I need to find out how one goes about getting exposure so that people might cite my work.
I guess it IS worthwhile for me to submit lower-impact journals related to my field, information security.
There must be more to it than just publishing:
http://grantome.com/blog/wasted-potential
So many talented postdocs without any lab funding. To get F32 fellowship you do need few publications.
Their exclusive, breakthrough theory on the Brontosaurus.
Where is the evidence for any success the last 30 years? What has been cured? Are cancer researchers still studying every possible mutation rather than looking at aneuploidy? Are the people doing translational research still avoiding characterizing their models correctly (use more than 20 animals, publish the distribution of results seen for control only under various conditions, then investigate why these individual differences exist)? Are a few pictures of some stained tissue still accepted as justifying some claim? Are they still dismissing unexplained bands on western blots as "breakdown products" and multimers without ever actually checking this?
It's quite surprising to see that females still have it worse even in a field (bio/med) where they are usually outnumbering their male colleagues.
And you know what's worse? Being a guy from math/eng/CS in that field. According to their predictor, taking only my 11 papers that appear on PubMed, I would have a 95% chance of landing a PI job. Yet, since I'm not a biologist by training, I can't even get an interview.
It's really just a volume question: The volume being pushed through is what has caused the explosion in scientific knowledge. If you don't believe me, look at the explosion of patent applications on "every single imaginable variation of a theme" so that they can then brute force the research to see if any work.
But what about other disciplines? It has been my observation that each discipline has a unique culture, esp. when you throw engineering into the mix. And the juries for the proposals are usually people from the same or related disciplines.
putting the 'B' in LGBTQ+
I can't believe no one has pointed out that the authors don't seem to understand the difference between correlation and causality...
Of course predictors of "success" are publishing in top journals as first author and running a lab. Obviously they are correlated, but which one causes which? Or is there a third cause? (like being a hard worker, or being smart).
But the comments are right. Going for many publications instead of quality publications seems to be a better strategy if all you want is "academic success".
In mathematics, where there are no "first authors" (always in alphabetical order), many papers contain only marginal contributions by some of the authors, who share full credit.