By now you have heard of the mess that is following the study by LaCour and Green. No, this isn’t another one of the 204 articles talking about this, so please come back. What I want to talk about in this post is the tense relationship young scientists such as myself have with academic fraud.
Every time I come across instances of academic fraud in science (usually via Retraction Watch) I feel a deep sense of paranoia over my own data and run the statistical analysis again and again to check if I am not accidentally committing fraud or p-hacking (read more about that in this paper by Head and colleagues, 2015). The thing is this paranoia is good in some ways, especially if it stops me from publishing fraudulent data and reaching erroneous conclusions that could tie up some poor sod somewhere else trying to disprove it. No one deserves to be stuck in this-doesn’t-work-times-100-oh-wait-this-is-fabricated hell.
So other than feeling like scrambling against a wall at the back of your brain every time you hear the phrase “academic fraud” what can you do as a young scientist*?
Repeat. Well repeat within acceptable limits that is. Unless you have severe time constraints repeat everything that tells you on the first run “Hey here’s something”. Show your raw data to your PI/Supervisor. All my raw and the analysis went through my PI first. It also made for some simple adjustments in my hands on technique and some great learning experiences.
Also, ask others in the lab. I may or not may not have been accidentally resizing my fluorescence images the wrong way. Turns out you crop it first, lock the aspect and then resize… Oops? And I would have gone my merry way and continued doing it if senior PhD students didn’t correct me because I didn’t know any better. I know how flimsy that sounds even to my own ears. But that’s the truth, knowledge, especially in this case, IS power. So ask. Yes, you may get “Are you an actual idiot?” stares but ask. I would rather be thought of as an idiot than a liar.
You may also want to check out Retraction Watch because I swear half the things in there will make you pay a lot more attention in how you handle and report your data. Especially if it involves a lot of figures and what not. I feel like that site is a handy list of things you shouldn’t be doing as a scientist.
So go forth and science young one, just be cautious.
*By young scientist I mean Bambi fresh out of Undergrad with starry eyes and an anxious heart.