Finding needle in haystack
Finding needle in haystack (Photo credit: Bindaas Madhavi)

A former colleague of mine at an institution I no longer work at has admitted to being a science fraudster.*

I participated in their experiments, I read their papers, I respected their work. I felt a very personal outrage when I heard what they had done with their data. But the revelation went some way to answering questions I ask myself when reading about those who engage in scientific misconduct. What are they like? How would I spot a science fraudster?

Here are the qualities of the fraudster that stick with me.

  • relatively well-dressed.
  • OK (not great, not awful) at presenting their data.
  • doing well (but not spectacularly so) at an early stage of their career.
  • socially awkward but with a somewhat overwhelming projection of self-confidence.

And that’s the problem. I satisfy three of the four criteria above. So do most of my colleagues. If you were to start suspecting every socially awkward academic of fabricating or manipulating their data, that wouldn’t leave you with many people to trust. Conversations with those who worked much more closely with the fraudster reveal more telling signs that something wasn’t right with their approach, but again, the vast majority of the people with similar character flaws don’t fudge their data. It’s only once you formally track every single operation that has been carried out on their original data that you can know for sure whether or not someone has perpetrated scientific misconduct. And that’s exactly how this individual’s misconduct was discovered – an eagle-eyed researcher working with the fraudster noticed some discrepancies in the data after one stage of the workflow. Is it all in the data?

Let’s move beyond the few bad apples argument. A more open scientific process (e.g. the inclusion of original data with the journal submission) would have flagged some of the misconduct being perpetrated here, but only after someone had gone to the (considerable) trouble of replicating the analyses in question.  Most worryingly, it would also have missed the misconduct that took place at an earlier stage of the workflow. It’s easy to modify original data files, especially if you have coded the script that writes them in the first place. It’s also easy to change ‘Date modified’ and ‘Date created’ timestamps within the data files.

Failed replication would have helped, but the file drawer problem, combined with the pressure on scientists to publish or perish typically stops this sort of endeavor (though there are notable exceptions such as the “Replications of Important Results in Cognition”special issue of Frontiers in Cognition ). I also worry that the publication process, in its current form, does nothing more constructive than start an unhelpful rumour-mill that never moves beyond gossip and hearsay. The pressure to publish or perish is also cited as motivation for scientists to cook their data. In this fraudster’s case, they weren’t at a stage of their career typically thought of as being under this sort of pressure (though that’s probably a weak argument when applied to anyone without a permanent position). All of which sends us back to trying to spot the fraudster and not the dodgy data. It’s a circular path that’s no more helpful than uncharitable whispers in conference centre corridors.

So how do we identify scientific misconduct? Certainly not with a personality assessment, and only partially with an open science revolution. If someone wants to diddle their data, they will. Like any form of misconduct, if they do it enough, they will probably get caught. Sadly, that’s probably the most reliable way of spotting it. Wait until they become comfortable enough that they get sloppy. It’s just a crying shame it wastes so much of everyone’s time, energy and trust in the meantime.

 

*I won’t mention their name in this post for two reasons: 1) to minimise collateral damage that this is having on the fraudster’s former collaborators,  former institution and their former (I hope) field; and 2) because this must be a horrible time for them, and whatever their reason for the fraud, it’s not going to help them rehabilitate themselves in ANY career if a Google search on their name returns a tonne of condemnation.

On Monday I gave a talk on how internet tools can be used to make the job of being an academic a little easier.  I had given a very short version of the talk to faculty in the department over a year ago, but this time I was given an hour in a forum for  early career researchers, PhD students and postdocs.  The subject of twitter, covered early on in the talk, aroused a lot of interest, probably because I got very animated about its benefits for those in the early stages of their careers.

To provide a little context for my enthusiasm, it probably helps to know a few things about me, about my situation, and about my recent experiences.

  1. I am an introvert.  Despite my best (and occasionally successful) efforts to project a different image, I do not find talking to people I don’t know very enjoyable.
  2. I am an early career cognitive neuroscientist keen to build my own research programme and develop links with other researchers.
  3. Last month I attended the Society for Neuroscience conference, at which I attended the best conference social I have ever attended.

Given the received wisdom that people in my position ought to be networking, I often drag myself kicking and screaming to conference socials. The result tends to be a lot of standing around on my own drinking beer, which gives me something to do, but which I could do much more comfortably with one or two people I know well.  The major problem at these events is not my nature, or my status as an early career researcher, but the fact that the people I have imagined myself talking to usually don’t know who I am.  Conversation is therefore awkward, one-sided and introductory.  Once the niceties have dried up, and the level of accumulated conversational silence edges into awkward territory I invariably finish my drink and bugger off to get another one, ending the misery for all involved.  This is probably a universal experience for those starting out in academia, though thankfully it is happening less and less to me as I build something of network of real friends who attend the same conferences as me.  But as a PhD student and postdoc, the experience was excruciating.

I had a totally different experience when I attended the SfN Banter tweetup*.  The event, organised by @doc_becca and @neuropolarbear, was a social for neuroscientists who use twitter and changed my view of conference socials.  They do not have to be endured, even by those doing PhDs and postdocs. They can be enjoyed.

I was excited about going and that excitement didn’t leave me feeling shortchanged by the time I left.  I spoke (actually spoke!) to everyone I wanted to speak to.  Moreover, I had good conversations with people to whom I was speaking for the first time. The reason is fairly obvious – twitter allowed us to build on a body of shared (or at least assumed) knowledge. I follow people, they follow me,  I reply to or retweet their tweets, they do the same – and this is all before we’ve introduced ourselves. When I finally meet someone with whom I have such a history of communication, introducing myself is the least awkward thing I can do. The barriers to conversation are removed**.

Sure, this pattern followed for most interactions at the tweetup because we were all there to do exactly that.  Would the experience be the same at the ‘fMRI social’? No.  But, I don’t think that matters.  If I could have had one of those conference social experience during my time as a PhD student, it would have given me an idea of what I might have to look forward to from conferences if I stuck at it.  Light at the end of the tunnel, a pot of gold at the end of the rainbow, a variable-ratio schedule-determined stimulation of the limbic system following an umpteenth lever press.

It will take a while (there’s no point joining in September 2013 and expecting great things at the SfN tweetup in San Diego), and it’s probably not the primary reason to join twitter (see  Dorothy Bishop’s blog and Tom Hartley’s blog for far more comprehensive discussions  of how and why you should join), but it’s another reason, and it’s one that could make you feel good about your role in academia.  It’s worth a shot.

 

* tw(itter) (m)eetup, see?

** What you do afterwards is up to you.  I still had some awkward interactions, but I think that’s probably down to me (see context point 1).