Speaker 1: There is a scientific fraud epidemic. Every week there seems to be so many retractions, there seems to be so many scandals. Fraudulent behaviour can even happen against your will, which we'll talk about a little bit later on in this video. It's just crazy out there. And it all starts with this article. There is a scientific fraud epidemic and we are ignoring the cure. I was so interested to see what that cure was. Essentially it starts with a dossier that was so unsettling because essentially it was hiding data that patients were dying because of a certain intervention. And this person from the University of Southern California pressured colleagues into altering their notebooks and co-authored papers containing doctored data. Now, in my field, no one dies if you do that. This is crazy. So why are all these scientists and researchers creating fraudulent data? Well, there was this article which was published a while ago. It's just called The Scientific Ponzi Scheme. If you go to page 6, essentially it says down here, there are several commonly discussed motivations for fraud. First one is desperation. Scientists facing imminent up or out decision like hiring or tenure. So, it's clearly a high pressure situation where these people are like, oh God, I need powerful, impactful data. Let's just make something up. I'll work it out later on. The second thing, insufficient punishment. We've seen this time and time again. If you want to be successful in academia, you can just sort of like make stuff up and people just go, oh, slap on the wrist. Naughty, naughty boy. Don't do it again. And you're like, oh, OK, no worries. Another thing is you're very unlikely to be caught. There is a huge, huge amount of data out there that no one ever looks at again. But also, there's a huge amount of data that is just fabricated and we only catch the tip of the iceberg. It relies on people donating their time to essentially find fraudulent data. There's a whole sort of like group, a underground of seedy scientists who are just always looking for fraudulent data. And really, like surely there should be something more sufficient, more sustainable to find fraud. Noble lies. I love this. I've actually seen this in action. Someone says, well, just sort of like make up this data because, you know, I think we'll work it out a little bit later, but we just need to get this grant. We just need to get this paper, whatever it is. But this lie will essentially become truth a little bit later on. So, don't worry about it. I've seen that play out. And the rush to publish. Scientists engaging in sloppy research to publish faster. Yeah, we're always gaming the metric, the H index metric. We are always, always gaming it to better our careers. These are sort of like the key cornerstones of why fraud happens. But what can we do about it? In fact, this article, the one we talked about before, suggests that instead of like all of these ad hoc vigilantism where you have these people just doing it off the back of their own sort of goodwill, people argue that there should be a proper police force with an army of scientists specially trained, perhaps through a master's degree, to protect research integrity. Yes, I love the idea that there's going to be this army of disgruntled scientists just sort of like telling on people. That's something scientists love doing is finding faults in other people's work. I imagine that this would be a very popular career course. Clearly, it needs a leader and I vote for Elizabeth Bick. Here she is. Let's stand. We're in the presence of royalty. Our queen, Elizabeth Bick. This is royalty in the sleuthing scientific world. I think we put her in charge of this army and it's a coup. It's a takeover. Let's go, Elizabeth. I'm right behind you. Every year, academics like to meet up and pat themselves on the back. Well done us. We're the best with this highly cited researchers list. It's published every year and essentially, it's the most cited researchers that is just in a list or as I like to call it, the people who managed to game the academic system the best list. Yes, I like that one. Okay. And here it is. It's a list of 7,125 highly cited researchers. But the thing about this year is they've had to exclude a load of researchers over 1,000 because they have sort of like gamed the system and now we're saying enough is enough. Just game the system a little bit, not too much because then we have to expel you from our list. Essentially, we had more than 1,000 researchers excluded and that's up from 550 in 2022. But essentially, they put filters which looked at extreme levels of hyper-authorship. You know, some of these people are pumping out so many papers that it is impossible for them to look over everything and give them their sort of thumbs up. They shouldn't be included in the author list if they haven't contributed significantly to the paper. Excessive self-citation? No. I like a little bit of self-citation when it makes sense. But these guys were taking it far too far. Or unusual patterns of group citation activity. I've seen it. I've seen people just sort of like, I'll cite you, you cite me. It's all part of the academic game. But these people did it too much. So when you have a list like that, clearly there's going to be people that want to be on that list because you want to be a highly influential researcher. So publish, publish, publish. And that's why so much fraud happens. It is about gaming the system. And the problem is is that if everyone's gaming the system, the system is inherently gamed by everyone. If you say these things to academics right now, they will say, of course I self-cite. Of course I publish with friends. Of course I try to sort of get on as many papers that I didn't contribute to as possible. It's part of the academic system. No one will admit it. But fraud happens so much that unfortunately it can even happen when you have nothing to do with it. Check out this next story. I found this article, which was really interesting to me. Noah van Dongen from Amsterdam University was essentially put on a paper that they didn't write. And the paper is just amazingly bad. It's a true story where essentially they ended up being on this paper. And phenomena can be characterized as general patterns in observations of psychological theories. It is a word salad. And one thing I love about this, like we'll go through this article in a minute, but I love all of the ways that he's described this paper because clearly he hates it so much. It's a word soup essay. It's an academic train wreck. It's a word vomit. I like that one. It is a literary disaster. It is a terrible textural trifle. It is a linguistic barf. Oh yeah. Oh, I let that one sink in. It is senseless drivel. It is verbal catastrophe. It is a linguistic salad. It is a textual horror. It is a horrendous word swirl. He loved it. I had to read it. This is great advertisement for this paper. But you can just sort of, let's just choose a random bit. The way that this pivotal connection must be fully explored by surveying the specialist uncovers an Achilles heel in the hypothesis. It is muddled what precisely the hypothesis predicts. Differentiating this solution with hypothesis in different spaces of science is helpful. For instance, no one at any point needed to ask Einstein what might before direction of starlight in the popular in light of the fact that Einstein's perspective was superfluous. This is, oh God, it's nightmare. It's a nightmare to read. And I think this is an absolute word orgy with no hard limits. I love it. So old Noah boy here ended up on this paper unknowingly in this weird ass journal, which was called Acta Psychopathologica. Acta Psychopathologica. There we are. That's good, isn't it? But essentially it's just this weird journal that has loads and loads of dead authors. So now we're in this weird situation where you've got people who are actively defrauding research. And then you've got journals, predatory journals who are putting people's names on papers. They didn't write creating this word orgy, but then not taking down the papers. The only reason I think I can see them doing this is because they want to increase the impact factor of their journal by increasing sort of like the number of papers that get published and therefore sort of like hoping that they get cited or maybe even sort of like faking the sites to increase that impact factor as well. It's just crazy. So it just goes to show that you can be part of this fraud without even trying. So where does this leave us? Essentially, there are things that we need to be aware of. And I think as new principal investigators and new academics coming into academia, we need to be on the front foot of this and just say enough is enough. Here is something that I read from It Could Happen in Your Backyard, which is by Mario, my little Mario bro over here. And essentially he's just saying as a PR, you should never think that you are safe and it may never happen to you. On the contrary, you should always expect the unexpected and meticulously implement mechanisms to prevent scientific misconduct. And he offers some solutions here. Openly discuss in your lab about scientific integrity and the plague of scientific misconduct. Teach your lab members that unexpected results are those that are the most interesting. Teach them that in a well-designed experiment, a negative result is indeed a result. Teach them to be critical of their own data. Pay constant attention to your collaborators' well-being and make sure they feel your empathy. In collaborations, do not be afraid to ask to see raw data. I think that's probably one of the most important ones in this list. I've seen so many people publish data and then when they get caught, go, oh, well, it was my postdoc. So yeah, it wasn't me. Whatever. No, if your name is on the paper, you have every right to see the raw data. Tell your lab members not to rush for results. The fun in science is the search. Ding. Do a ding. Ding. Teach them to be comfortable with temporary failures and drawbacks. Maintain a digital log of all of the data and lab meetings. And even if the journal you are submitting to does not require, submit all of the raw data, including original Western blots. I don't know what Western blots are. Ah, DNA stuff. Western blots. There we are. That's for all the rest of you that didn't know what that was about. Those things can absolutely help us going forward, but ultimately talking about it, being open and also AI tools. I love AI tools. You know that. But AI tools are going to be the thing that really help us sort of like speed up identifying fraud in science. So I'm all for the image twin. I'm all for using AI to catch tortured phrases and that sort of stuff. But let me know in the comments what you think about how we can actually deal with scientific fraud considering that there are so many papers published every single year. If you like this video, remember to go check out this one where I talk about how academia is broken and the scientific scandal happening right now. It's a great watch and it's a real eye opener into the real world of academic publishing. Check it out. So there we have it. There's the academic fraud epidemic that's going on right now. As always, I want to know what you think. Let me know in the comments. And also remember there are more ways you can engage with me. 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