It's crazy how my view has changed over the entirety of my education; in my undergrad, I automatically assumed that anyone who was "smart enough" to publish a paper was deemed to be a pillar of the industry, only to enter grad school and find out that scumbags exist in every field :)
The two people I know who got published in undergrad did jack shit to get on the paper. It was "thanks for cleaning the dishes and attending meetings, here's a pub".
Frauds can also be detected if the following points are all true to some extent: a) fails to keep MS/phd students in their lab, b) has lots of collaboration, getting idea from collaborators, making students do everything with 0% help, securing corresponding author position doing simply nothing. c) hiring too many post docs. d) reaching out to great professors and doing their side works with the help of high-paid post-doc. As a result, being able to get Co-PI position in next grant. e) Being Co-PI in many grants and have no PI of any grants.
This is a good list, though your point (e) can be wrong depending on the person's specialization. For example, someone who's a technical specialist, e.g., a statistician or specialist in certain data gathering methods, is quite frequently a co-PI but quite rarely a PI.
@@samsonsoturian6013 Sure is. I was a co-PI with someone who was a PI like that. Terrible. There was massive turnover that definitely affected the work. Bleh. What a shitshow.
They won't even check. Essentially, if a news blurb comes out: "Dark chocolate now proven to make you wealthier", you can *GUARANTEE* that dark choco sales will increase. Guaranteed.
A lot of people WANT fraud to go unnoticed. It's like the Olympics, we want to entertain power fantasies about what is possible, also fraud is the only way to change demographic trends in academia
They have literally been trained and coerced, with the threat of social ostracism, to listen to The Experts and trust The Science, no matter what. Acknowledging that scientists may be not only wrong, but *willfully* corrupt and serving a non-scientific agenda - is basically sacrilege of The Science, the modern church that has little to do with the scientific method.
Be careful of what you wish for because lawsuits can and are used by bullies who want to cause problems. Most scientists don't have deep enough pockets to ward that off.
We are seeing how people that lack integrity and honesty can easily game the system. And that's just not in publishing scientific papers. It's epidemic throughout our society. Great video!
I think it's time to treat scientific papers like we treat open source code: Something that EVERYONE can audit and analyze, without any paywalls or any other impediment. Also, I think that each university should host its own server for provisioning data about the publications and have them authenticated through a decentralized blockchain method.
For my data analysis, I've preselected 1 TB real and simulated data. There's no way my university is going to keep this data longer than I stay working on this data, after that it will be removed, because the cost of storing such big data for decades without any further use is just ridiculously expensive.
Universities do increasingly have long term storage for research data. You can always reach out to the researchers and ask if they'd share their data with you or if its being hosted somewhere. Of course lots of data can't actually be shared even when it is stored, for reasons related to privacy laws, ethics policies or commerical agreements.
what do you mean primary author? if you only mean author I don't think so... because sometimesnyou need collaboration on fields for a research, example biologists and physicians, then, if it is the work of students, you need to include the supervisors and PI. if you need a technology only available in another lab, you'll have to include whoever conducted the experiment in the other lab... I understand that a max of 8-10 authors if sufficient for most of research
this type of mindset is what excluded me from 2 papers in which I had significantly contributed on. They thought there were too many authors listed so they excluded the undergrad students
It depends a lot on the area. In some areas like particle physics, you'll see A LOT of authors. In other areas, like math or philosophy, multiple authors is rare. That said, I do agree with your wife that author lists have gotten pretty out of hand in some areas... social psychology, I'm talking about you.
Governmental conflicts of interest definitely deserve more attention. When most people talk about conflicts of interest, they often only talk about corporate conflicts of interest. Governmental grants are often seen as a public expense and represent the interest of taxpayers, in other words, you and me. But in reality, the ruling class often holds the ultimate decision of who gets the fund, which can go against the public interest in a lot of ways. While it is not strictly academic, are you interested in fraud in healthcare reviews from governmental institutions (e.g. the notorious Cass Review and others)? Speaking of corporate conflicts of interest, I think another neglected area is weight loss research, which almost always makes their results more appealing than they actually are.
The survey you did could have benefited from lower response options. 70% of respondents choosing a single option is absurdly high. It is possible that many of your viewers consider more than 5 papers a year to be too many, but there wasn't an option for that so they choose the nearest one: 10+. However, this does not contradict your conclusions in any way. I just felt it important to comment on it, given that the video is about scientific accuracy. Keep fighting the good fight.
The ones with this amount of papers published per year could be working in large physics collaborations, like those at CERN: ATLAS, CMS and even the progressively smaller ones such as LHCb, Alice and so forth. For example, last year, the ATLAS collaboration published 111 papers, each one having an author list of about 3000 people. Up to now, in 2024, there have been 69 ATLAS papers published. Of course, these large physics experiments are a bit funny that way because they couldn't even happen if they wouldn't be run this way. But I don't doubt that there are a lot of fraudsters claiming to publish hundreds of papers per year in small teams or on their own. That's a completely different story.
@@Anton-tf9iw did you miss the part where I said that this is the only way to run this type of physics experiment? In high-energy physics experiments aren't tabletop stuff. They are giant apparatuses that are some of the most complex devices ever created. You think people would contribute to building them without any recognition? Out of those 3000 ATLAS authors, a few dozens are actual physics theoreticians, a few hundred do physics data analysis, which could be any other type of data analysis in most cases, and then, the vast majority, are doing engineering research, development, manufacturing, logistics etc. And all of this is done by people working in research institutes, where publications are essential for career advancement. So nobody would contribute if their contributions were not recognized. And without all those contributions, nothing would be accomplished. So you criticizing the way things are done only show you don't understand how things are done.
@@jeffersondaviszombie2734 Engineers, developers, machinists, and warehouse operators do not need career advancements in physics. They may have other ways to advance their careers or they could also be happy to continue to work in their positions as professionals. I think it is ludicrous to include them as authors in physics publications even if they all work in an institution.
Peer review is a scam more or less. It is an invention to publishers to raise the perceived status of their journals but it all depends on the "peers" who are unpaid, busy with their own work and are motivated not to piss off peers that might block their own papers. To see how bad peer review can get look for the greivence studies affair. Admittedly not science but illustrative of the problems with peer review. Before peer review there was adversarial review where competing scientific minds would tear at each other's theories, but that functioned in a very different system where scientists were fighting for glory rather than grants for their institutions.
So, I'm not a scientist or a scientist. Heck, I spent the first 44 years of my life without a bachelor's degree. It was while I was wrapping up my undergrad that a psychology professor covered a thing or two about spotting not only bad study design, but also fraudulent study design. What alarmed me was the sheer quantities of examples she could cite. Naive me just assumed that peer review worked, but if that professor and the TH-cams-these-days are correct, it's absolutely broken. It must be done cheaply, if at all. I do think you're raising the right point. Peer review is supposed to be a knowledgeable, human safeguard. We have to be missing incentives to do it and do it well, no?
@chrisumbel3132 Peer review does somewhat work, but it has some significant issues. It is completely unpaid, which limits the time that people can justify spending on it for a start. For the issues in this video, peer review is often blinded, so they couldn't look up to see if the author is publishing a suspicious amount, or consistently finding surprising results. Any individual can also only expect to find so much- if the data is faked but the interpretation of that faked data is consistent then the peer reviewer may not be in a good position to raise much of an issue
Peer review is just getting somebody else to look over some work, tell the editor if it's worth publishing and maybe make some suggestions to the authors. Detecting fraud is outside what it's meant to do and very few peer reviewers would be on the lookout for it. Even if they were on the lookout for it detecting likely data manipulation is generally going to be much more time consuming than can resonably be expected for what is basically volunteered time that actively takes away from their actual jobs. On top of all that you have to remember that a lot of fraud isn't going to be detectable based on the paper itself, if they're making up data you may need to actually look into their research process to discover this.
Pete, you should do a statistical analysis on all types of scientific fraud to establish a general understanding on the extent and magnitude of this problem.
That would be something that would require a pretty massive research grant to do and would be field-specific as he said, but I think the basic signals are there: Unbelievable sustained publication rate is, in my view, the sine qua non. Unfortunately, universities and granting agencies really do like their rock stars, not us more ordinary working faculty who are the ones who make the university run and publish at a more reasonable rate. Some years we have a lot of articles (my best year had 7 articles) and other years are more down years (uh... 0, or 1).
@@DrJTPhysio - start with a pilot study. Sample of N papers selected at random from all published original studies within X field (or from c search term), with primary authors university faculty, between Jan. Xxxx and dec. Xxxx Or N number of primary research papers selected from total pubs new pharmaceutical agents in 1989 versus 2024 that demonstrate conflict of interest as defined by yada yada
@@ColdHawk there's a bit more to it, but I get where you're going. I'm working on a study that implements a similar research design. Doing this alone would be pure pain.
Not a red but orange flag is someone getting too many successful grant applications from fields other than their own, for example, AI to address some topic in the humanities.
Data availability. One paper i wanted to look at the data myself. It was apparently a PDF. However the data was protected by a password. I was able to copy the results by hand but this was a nasty trick
It's funny when they say "Upon reasonable request," as if there is such a thing as a request to see data (personally identifying information notwithstanding) that isn't reasonable.
The number really depends a lot on authorship level, field, and subfield. For example, Erik Demaine, who is in my field, and overlapping with some subfields of mine, publishes around 20 papers a year, and is well respected. Since it is CS theory (AKA, math stuff), there is no data to be faked, and I haven't ready any flawed proofs of his. But certainly, the more papers that is published by someone, the more I'm suspicious. For social sciences and physical sciences, I would be very suspicious of even matching Erik's publication rate.
The solution is to make it irrelevant to have large numbers of papers. Use a logarithmic metric, with a maximum at --say-- log(12 papers/year) and decreasing for larger number pf papers per year down to zero if you publish --say-- 24 papers or more per year. Actually I think the numbers should be closer to half of those above.
The question depends not only on field but on what “publication” is. There’s a “tradition” of putting as authors people who have contributed to the paper, so if you built some machine that say 30 grad students are using, and they each publish 2 papers, it wouldn’t be rare to have 60 publications without you having to do pretty much anything. I hate how academics trade and game publications, but I wouldn’t jump to conclusions based solely on the number of publications.
I think the number one way to catch bad science ought be replication. Requiring independent replication of results will be a much more reliable way of finding bad science and bad scientist than counting publications, auditing for conflicts of interest or investigating images. Theories built on bad data will not stand up under replication regardless or whether the data were fraudulently made up, the result of unintentional methodical problems or bad luck.
I publish dozen or more papers a year, though only a few are first/sole author. In planetary science we often work in broad flat teams of individual 'independent' scientists associated with space missions (without the more feudal lab head/minion hierarchy associated with a lab). The mission data are contractually obliged to be publicly available.
About people with an impossible number of publications: what is pretty common is for an influential academic (typically a prof) to be systematically named as a co-author by his faithful graduate students (and other junior academics); the influential academic boosts his h-index, while the lowly graduate students and junior academics increase their odds of being published, being awarded grants, progressing in their career, etc. wink wink nod nod, it's practically a right of passage at this point.
The first thing that should be done is to pay reviewers for their time and have a grading system for reviewers. Reviewers are incentivied to spend as little time as possible on reviewing a paper. Reviewing time should be mandated on an institutional level and paid for by the cost to publish fee by the for-profit publishing industry. Yes, this may lead to higher cost of publishing and slower publishing, but also fewer fraud cases and less retraction rate of papers.
Regarding the scientists publishing a ridiculously high number of papers. Is that really a sign of fraud or does it just mean that the scientist is running a huge lab and all the junior researchers are putting his name on their work?
Even with a big group, 200 papers is way out of reasonable. There is no way that person has seriously contributed to those papers. I’d be surprised if they had even read them all.
@@danielschein6845 indeed, but seems to be conflated in a lot of comments on this type of video. Also, it inflates the risk of errors or fraud by the main author or contributor not getting spotted.
Great video like always, thanks! I wonder, though, if you could also look into the darker fallacies of science? The ones that are done more on an unconscious level. The obvious examples are (and I think you already touched upon those in past videos): - Statistical correction for multiple testing. In biology, p>0.05 is widely accepted as "significant", after Bonferroni (etc.) correction for multiple testing. All that means that, on average, 1 in 20 studies will yield a "significant" result. Well, in certain fields, hundreds of papers are published every year - so we end up with all the false positives, while the negative results are much less likely to see the eye of the reader. - Statistics in general (I won't go into cohorts here, that's a topic all by itself). Statistics is based on a random distribution, whatever that distribution might be. Especially biologists, who are not experts in statistics, working with statisticians, who are not experts in biology, can easily produce way to optimistic p-values, without being aware. In my experience, reviewers only rarely catch that, because they are either biologists or statisticians. - Reproducibility. This is particularly apparent in GWAS studies, only a tiny fraction can ever be reproduced by anyone else, and even if, never exactly. Yet, the claims of GWAS ("you have a 14% higher chance of getting this or that disease if...") are often widely reported by the media, hence the incentive to do these studies. Even if the statistics used is sound, this comes down to case vs. control selection, sampling bias, etc., which invalidates the underlying assumptions. I think there is a need to also publish negative results wrt reproducibility, as well as positive ones. Because the proof is ultimately in the pudding. All in all, yes, there are the obvious bad apples in the scientific community, the ones who willfully falsify results. I think these are in the minority though, and that most false results are published out of (tolerated) ignorance.
Very good discussion. I think point 5 can be a problem in some areas of research, where privacy requirements pull against data sharing. For example, getting permission to release data from actual patients or minors can be quite onerous. That said, bad faith researchers can and do make use of these requirements as a shield. One of the worst examples I've encountered in my professional existence---won't name names but I'm talking B grade horrid, not A grade like the ones that have been getting outed to substantial publicity, such as that real peach Francesca Gino---loved to hide behind the IRB. In my time working with that team, I didn't see any data made up, but I did see quite a lot of really shady data practices.
@@user-vb3ly7ib4r I'm not naming names on TH-cam, but I filed complaints to the relevant authorities, including the grant agency. As to the practices, basically the PI would state that data would not be released due to FERPA (educational data privacy law) but then was perfectly happy to do things that pretty clearly violated FERPA, such as give out datasets to people on the team who had no business having things like participant names. Simply put, she didn't want to have anyone else seeing the data. I wasn't convinced she understood the difference between research and data analysis done for course improvement, quite honestly. She's one of those people who's charismatic and clever, not actually smart.
Regarding the "10 Papers a year" thing. The reason why I am stating this, is because I assume to be an author you need to at least have "read" and "understood" it. Both of these need time. if you are publishing a paper a day, when are you actually doing the data generation part?
There is a problem in scientific culture. Many treat science merely as a career or a game, where getting ahead is much more important than the often directly competing concern to do good work that will stand the test of time. Publishing is just a box to check. At the fringes of this are the frauds but in the middle is occupied by people who forget the actual purpose of doing science.
Beware of generalizations ..... "data available upon request" or "data available at http...." in many cases is a move in the good direction you state (and which I support) and the only means of telling your potential readers that you're willing to share your data.
Single authorship on all or most papers someone publishes is another red flag. Another eye should be kept on journal editors, as they can help their buddies publish their research before someone else via simply rejecting a paper that tested that hypothesis first. Also, journal editors who gatekeep new directions in the field as a favour to their buddies is a form of scientific misconduct. As someone else pointed out, a search of how many harassment complaints are against a researcher is an indication that they have also gotten engaged in scientific misconduct.
Do you "first author"? I find it very surprising you didn't specify this. Last authors, for example, are typically lab/science area heads who will appear on every paper authored by their team.
Do you consider results that are very socially popular as falling in the "conflicts of interest" category? Maybe affecting the works of the likes of Roland Fryer and others who research such touchy topics?
If a pseudo-scientist hits on results which the general public WANT to see as being valid and true, you can bet that the P-hacking will commence, baby! 💪😎✌️ There's HUUUGE money in telling billions of people what they already hoped was "true". 😂
you should cover what the scientific community is proposing doing about this (fake data, but also p-hacking, replicability, publication bias etc), i think its a known problem to many scientists also the history of how and reasons why we got such ridiculous seeming systems like not having to publish the data along side your paper
How do you get the scientific community and journals change their baseline practices? Is there a committee/professional organization that defines these?
7:40 I think this is unfair. Sometimes the dataset is just very large to host online. Sometimes the data is confidential. As for the codes, the ideal is indeed to release them. From experience though, well-documented working code that reproduce all the results with graphs is sometimes almost as much work as writing the manuscript itself. But most of the time when I wrote to an authors for their codes, they were kind enough to share them with me.
What is the point of academic journals if they don’t already do all of this??!! All this time, effort and resources that could be used to do ACTUAL RESEARCH but has to be wasted on this - not to mention all the funding that they take from honest academics!! For just the autism article ALONE The Lancet and everyone involved should go “straight to jail!” 😡
can you please make a video on how to spot ai generated text in papers? My professors are saying "it's so obvious by the way ut is formated" but i can't really see it. Can you please share your thoughts on how to spot it?
How are people Who watch your TH-cam video justified or educated enough to determine how many publications per year are too many? If one person publishes 10 papers in one year and then Publishers only one paper for the next two years how can and essentially uneducated populous, decide that this person has committed fraud? Initially your channel was wonderful and brought about many feelings of the system. Since that time it appears that you have become extremely enamored by yourself and are putting out information that is Clickbait and dubious at best..
I don't agree with you on the Data Availability Statement (below a suggestion). Data in biochemistry etc is typically very simple, there it can be standard practice. However, often the raw data impossible to handle, if you're not an expert in the field - typically there are maybe 100-1000 true experts in each specific subfield. Therefore, first, randomly upload data for the community won't really benefit anyone. The chance ppl will wrongly treat the data out of missing expertise is just really high. Second, making everything available we will just feed AI to know better, how to make raw data, which then will be used by asshole scientists to create fake raw data and deposit it. Therefore, another suggestion: First, here over in Germany, the German Research Foundation requires universities to store ALL data. If you don't do that, you won't get funding. Second, nowadays every journal provides paper statistics. Just add one for "Requests / Data shared / Not shared". Thats even better because honest scientist (who the majority) love it if somebody shows interest AND uses their data and has to cite them! In this way data is available, support is provided by the authors, the community communicate, and we will easily spot assholes.
I woud not say that "data available upon request" qualifies automatically as a lie. My university demands by contract that our data and code is uploaded onto a university server (its their property not mine). If I would not respond to other scientists asking for the data, they could ask the university which hands it out to ensure reproducibility of the results. I hope more universities start implementing such standards. Of course this does not help if the data itself is subject to misconduct.
@@samsonsoturian6013 I get constantly e-mails from other scientists. I never experienced this issue. Notice also that you can contact the university or department directly if I do not respond. I mean what is the claim here, that emails dont work?
Historian here: We don't have an incentive to publish surprising results. For instance, one submission I sent was rejected unread because I refused to say that a particular battle was part of a wider conflict between "white men" against "indigenous peoples" because it was simply not so (the battle was between US cavalrymen and unidentified Indians in Mexican service).
These are all reasonable ideas to catch basic frauds. We should remember though that this is an adversarial system and fraudsters will get better at beating basic automated checks, so we'll really need to go deeper over time and maybe even change the way science is done if we really want to root out fraud.
@@robertharper3754 It's a sad fact of reality here in W-S, with many unfortunate down-&-upstream effects. Thanks for the neighborly show of solidarity; your reply gave me a much-needed boost of optimism in these otherwise dark & unpleasant times!! Perhaps W-S isn't an entirely blasted toxic wasteland, after all!🤷♂️ 😁💞✌️
We're all way too careful. Don't be afraid to hurt feelings of 0.1% if the upside is removing the filth of bad research. We just need to require more evidence from suspicious actors. >10 papers a year? You must supply all of the raw data, with very specific requirements for details. I think the requirement should be "An external non-field related person should be able to deduce the details of the experiment: how the participants were contacted, what they were given at what time. If this was a mechanical/chemical experiment, there has to be equipment specs, settings details." So that replication is no longer a guesswork, and there aren't "obvious" things that field-related scientist like to omit. For instance I know every detail Maxdiff study. I may just say RLH was X and expect the reader to understand. Such expectations should no longer be allowed. Specify the formula, and how you obtained it. Was it individual scores, aggregate scores, etc
Data should be made available to readers definitely because how else will we verify results? 200 papers a year by 22 academics is crazy. Must be AI generated.
I'm aware of Wakefield's conflict of interest and the problems with his work but I am perpetually amused by all the bleating labeling him AntiVax when he was actually trying to hawk a competing vaccine all along.
I think the rise of AI tools is going to make faking a paper much, much easier. Your list is a very good start, but, ultimately -- in about five years! -- I think most work, especially by limited groups, will need to be independently validated to be trustworthy. (And that will require serious funding.) That sounds like a huge waste, but I wonder if it will cost more than the hidden costs that we're already suffering from junk science leading researchers astray. (And let's not talk about the huge societal costs of faulty public programs based on bogus research!)
I just finished reading another Carl Elliott book, his latest: The Occasional Human Sacrifice. Fraud isn't the half of it. Look into studies with many deaths.
The problem is that with the recent climate, if you dispute anything - whether it be conflict of interest, rate of publication, or any of the five ways you described, you'd be labelled anti-science, conspiracy-theorist, right-wing (as if science were exclusive to one political affiliation), etc. And if you speak with a scientist about it, the first thing they do is ask for your credentials as if it's the degree that enables someone to use critical thought and discern bad science.
(1:42) ..."they" aren't writing shit😂 ....there are plenty of sites out there that have freelance writers, editors, artists, proofreaders and the whole publication market for hire...potentials put their experience and rates up for grabs and do the writing or whatever is needed without question....follow the scientist's names to these sites and I promise you'll end up with a Bingo! or three.... ...as per the end question, the answer varies from a real net to a sting operation and subpoena....
3:00 Note that Wakefield's critics also were paid for by people that owned vac patents. UC Davis was give labs and tons of money. The biggest criticism was that he used a small sample size. That is what they do to! Thats what everyone starts with and then goes to larges size.
Viewing your presentations creates in me a desire more and more fraud to be committed so that you have ever more content to present..but then there is already more fraud than you can cover.
Issue #1, publication rate. I suspect you're forgetting that junior scientists (grad students) publish a paper, it takes a year or more, but our supervisor(s) automatically get attached to the paper. Automatic. So, if a prof has 10 students, he/she easily has 10 per year papers, without doing any hands-on personal work themselves, with e.g., other colleagues. (Same with patents). Names are attached out of respect, and obedience. Not my place as grad student if dept head wants his/her name on my paper to say "why". So, the 'big shots' of academia get bigger because clout-buys-clout, just like money-begets-money. Those who actually do the creative work, well, we get a PhD degree. Not a bad trade, maybe.
That may be standard practice but that is just another example of academic corruption and historical fraud. No one should be on a paper who did not significantly contribute to it. Providing the resources is not a reason to be an author. Should the funding agencies be cited as authors too? Funding and resources should be cited as a thank-you notice.
The point of the senior author role is that they set the initial plan for the research (by writing the grant), and should be checking the work that the others have done. The vast majority of PIs *are* involved in planning experiments, discussing results, advising the postdocs and students on analysis etc.
@@samsonsoturian6013 not at all. That is a fundamental misunderstanding of the scientific research process. Almost all science is collaborative, and PhD and Postdoc positions are fundamentally education and training to become an independent researcher. The PI / senior author is there to lead the research - this is a key contribution, directing the work of the group and giving key intellectual input to the research activities. There are many research group leaders who do lab work/classical research activities, but If PIs had to be in the lab doing all the work, there would be no time to support students and postdocs, write grant applications, and engage in collaborations. Modern science would fall apart. These days many journals require a contribution statement, which explicitly says what each author contributed to.
i heard that actually, global warming is more serious than previous papers say because they adjusted something related to the clouds? a physics woman talked about it on youtube
@@ujubin For clarity, there were two models of the atmosphere, predicting weather. One was based on historic trends, sediment deposition and ice samples, and one based on modern weather measurements for weather forcasts- the weather forecast people had to update their models to get accurate results because they weren't getting the same patterns over the last 20 years. The people using the modern measurments ran the historic data and got a 'this can't be right' high number for global temprature average, eventually it was figured out that the effects of some clouds was different - we've been getting more of them than historic trends indicated due to things like unintentional cloud seeding with aircraft, as well as miscalculating how reflective those clouds were, and the 'oh shit' global warming numbers were accepted as being accurate after a lot of people looked at the data. A lot of the climate scientists I've been following have been sounding more and more like survivalists. Not like 'humanity is doomed' bad, but 'we're gonna have a bunch of wars over water supply' bad. We still have the tools to stop climate change, its just gonna be a lot messier using them.
Except the data comes from many different sources. The evidence is overwhelming, and as much as you don't want it to be true, it doesn't seem to change the more they look into it.
On your image manipulation section you bring up Elizabeth Bic's work in the context of fraud. I haven't watched your previous videos and you have the impression that she was someone who had committed image manipulation. Only later so you make clear that she's exposing fraudulent use of images by others. You need to be more careful and not assume everyone watching your videos has seen previous videos and make it clearer who is committing the fraud and who is exposing it.
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It's crazy how my view has changed over the entirety of my education; in my undergrad, I automatically assumed that anyone who was "smart enough" to publish a paper was deemed to be a pillar of the industry, only to enter grad school and find out that scumbags exist in every field :)
The two people I know who got published in undergrad did jack shit to get on the paper. It was "thanks for cleaning the dishes and attending meetings, here's a pub".
Frauds can also be detected if the following points are all true to some extent:
a) fails to keep MS/phd students in their lab,
b) has lots of collaboration, getting idea from collaborators, making students do everything with 0% help, securing corresponding author position doing simply nothing.
c) hiring too many post docs.
d) reaching out to great professors and doing their side works with the help of high-paid post-doc. As a result, being able to get Co-PI position in next grant.
e) Being Co-PI in many grants and have no PI of any grants.
This is a good list, though your point (e) can be wrong depending on the person's specialization. For example, someone who's a technical specialist, e.g., a statistician or specialist in certain data gathering methods, is quite frequently a co-PI but quite rarely a PI.
@@crimfan I agree with you. The points I mentioned are all linked together. So, the points are all "AND"s
This should be the pinned comment.
Even without fraud that's definitely a shitty workplace
@@samsonsoturian6013 Sure is. I was a co-PI with someone who was a PI like that. Terrible. There was massive turnover that definitely affected the work. Bleh. What a shitshow.
Based on my observations: A lot of people don’t care about scientific fraud
A lot of people don't care about fraud
They won't even check. Essentially, if a news blurb comes out: "Dark chocolate now proven to make you wealthier", you can *GUARANTEE* that dark choco sales will increase. Guaranteed.
A lot of people WANT fraud to go unnoticed. It's like the Olympics, we want to entertain power fantasies about what is possible, also fraud is the only way to change demographic trends in academia
They're happy to have their pre-existing views supported, yep.
They have literally been trained and coerced, with the threat of social ostracism, to listen to The Experts and trust The Science, no matter what. Acknowledging that scientists may be not only wrong, but *willfully* corrupt and serving a non-scientific agenda - is basically sacrilege of The Science, the modern church that has little to do with the scientific method.
"Right to jail."
After hearing about Harvard’s disgraced ex-dean, I am not surprised scammers fill the top-rung of the healthcare industrial complex.
👍Stanford too
the violin doesn't work with speech
@2:22 "the manpower or the infrastructure" If you can popularize lawsuits against scientific fraud it will become a self driving mechanism.
That will NEVER happen. The wealthy cannot possibly allow it; it would destroy them at the very core.
Be careful of what you wish for because lawsuits can and are used by bullies who want to cause problems. Most scientists don't have deep enough pockets to ward that off.
Or just criminalize it as fraud. Technically no new laws are needed, as anyone can reasonably expect financial gain from getting published
@@crimfanYeah, it's easy to imagine corporations abusing it to suppress studies they don't like
@@_human_1946 then include something similar to SLAPP but with more teeth.
We are seeing how people that lack integrity and honesty can easily game the system. And that's just not in publishing scientific papers. It's epidemic throughout our society. Great video!
I think it's time to treat scientific papers like we treat open source code: Something that EVERYONE can audit and analyze, without any paywalls or any other impediment. Also, I think that each university should host its own server for provisioning data about the publications and have them authenticated through a decentralized blockchain method.
For my data analysis, I've preselected 1 TB real and simulated data. There's no way my university is going to keep this data longer than I stay working on this data, after that it will be removed, because the cost of storing such big data for decades without any further use is just ridiculously expensive.
@@arabusovseriously? 1 terabyte is like what $40?
Universities do increasingly have long term storage for research data. You can always reach out to the researchers and ask if they'd share their data with you or if its being hosted somewhere. Of course lots of data can't actually be shared even when it is stored, for reasons related to privacy laws, ethics policies or commerical agreements.
@@BenjaminGatti it must be done by means of universities, they need to dedicate people and hardware for just this task. It's expensive
Important genome data like from the UK biobank is kept under lock and key so people don't get any unapproved ideas about things like race
My wife is a scientist. I think more than four as primary author is suspicious.
what do you mean primary author? if you only mean author I don't think so... because sometimesnyou need collaboration on fields for a research, example biologists and physicians, then, if it is the work of students, you need to include the supervisors and PI. if you need a technology only available in another lab, you'll have to include whoever conducted the experiment in the other lab... I understand that a max of 8-10 authors if sufficient for most of research
this type of mindset is what excluded me from 2 papers in which I had significantly contributed on. They thought there were too many authors listed so they excluded the undergrad students
@@kheming01 He means "equally contributing authors", those considered to have done the critical parts of the backbone of the paper.
It depends a lot on the area. In some areas like particle physics, you'll see A LOT of authors. In other areas, like math or philosophy, multiple authors is rare. That said, I do agree with your wife that author lists have gotten pretty out of hand in some areas... social psychology, I'm talking about you.
@Draconisrex1 Yeah, 4 is def a large amount as a PI, especially if it's experimental research and if it's human subjects.
Governmental conflicts of interest definitely deserve more attention. When most people talk about conflicts of interest, they often only talk about corporate conflicts of interest. Governmental grants are often seen as a public expense and represent the interest of taxpayers, in other words, you and me. But in reality, the ruling class often holds the ultimate decision of who gets the fund, which can go against the public interest in a lot of ways.
While it is not strictly academic, are you interested in fraud in healthcare reviews from governmental institutions (e.g. the notorious Cass Review and others)? Speaking of corporate conflicts of interest, I think another neglected area is weight loss research, which almost always makes their results more appealing than they actually are.
great summary. would be interesting to see how journals react to recent developments and fraud cases.
The survey you did could have benefited from lower response options. 70% of respondents choosing a single option is absurdly high. It is possible that many of your viewers consider more than 5 papers a year to be too many, but there wasn't an option for that so they choose the nearest one: 10+. However, this does not contradict your conclusions in any way. I just felt it important to comment on it, given that the video is about scientific accuracy. Keep fighting the good fight.
The ones with this amount of papers published per year could be working in large physics collaborations, like those at CERN: ATLAS, CMS and even the progressively smaller ones such as LHCb, Alice and so forth. For example, last year, the ATLAS collaboration published 111 papers, each one having an author list of about 3000 people. Up to now, in 2024, there have been 69 ATLAS papers published. Of course, these large physics experiments are a bit funny that way because they couldn't even happen if they wouldn't be run this way. But I don't doubt that there are a lot of fraudsters claiming to publish hundreds of papers per year in small teams or on their own. That's a completely different story.
Yes indeed that is quite true.
And why should that bad habit be acceptable?
@@Anton-tf9iw did you miss the part where I said that this is the only way to run this type of physics experiment? In high-energy physics experiments aren't tabletop stuff. They are giant apparatuses that are some of the most complex devices ever created. You think people would contribute to building them without any recognition? Out of those 3000 ATLAS authors, a few dozens are actual physics theoreticians, a few hundred do physics data analysis, which could be any other type of data analysis in most cases, and then, the vast majority, are doing engineering research, development, manufacturing, logistics etc. And all of this is done by people working in research institutes, where publications are essential for career advancement. So nobody would contribute if their contributions were not recognized. And without all those contributions, nothing would be accomplished. So you criticizing the way things are done only show you don't understand how things are done.
@@Anton-tf9iw Whether you think it's acceptable or not, it doesn't mean the papers are fake. Those are two different issues.
@@jeffersondaviszombie2734 Engineers, developers, machinists, and warehouse operators do not need career advancements in physics. They may have other ways to advance their careers or they could also be happy to continue to work in their positions as professionals. I think it is ludicrous to include them as authors in physics publications even if they all work in an institution.
Isn't "Peer Review" supposed to catch most of these things? Isn't that the whole idea of peer-reviewed studies?
Peer review is a scam more or less. It is an invention to publishers to raise the perceived status of their journals but it all depends on the "peers" who are unpaid, busy with their own work and are motivated not to piss off peers that might block their own papers.
To see how bad peer review can get look for the greivence studies affair. Admittedly not science but illustrative of the problems with peer review.
Before peer review there was adversarial review where competing scientific minds would tear at each other's theories, but that functioned in a very different system where scientists were fighting for glory rather than grants for their institutions.
So, I'm not a scientist or a scientist. Heck, I spent the first 44 years of my life without a bachelor's degree. It was while I was wrapping up my undergrad that a psychology professor covered a thing or two about spotting not only bad study design, but also fraudulent study design. What alarmed me was the sheer quantities of examples she could cite.
Naive me just assumed that peer review worked, but if that professor and the TH-cams-these-days are correct, it's absolutely broken. It must be done cheaply, if at all.
I do think you're raising the right point. Peer review is supposed to be a knowledgeable, human safeguard. We have to be missing incentives to do it and do it well, no?
@chrisumbel3132 Peer review does somewhat work, but it has some significant issues. It is completely unpaid, which limits the time that people can justify spending on it for a start. For the issues in this video, peer review is often blinded, so they couldn't look up to see if the author is publishing a suspicious amount, or consistently finding surprising results. Any individual can also only expect to find so much- if the data is faked but the interpretation of that faked data is consistent then the peer reviewer may not be in a good position to raise much of an issue
Peer review is just getting somebody else to look over some work, tell the editor if it's worth publishing and maybe make some suggestions to the authors. Detecting fraud is outside what it's meant to do and very few peer reviewers would be on the lookout for it. Even if they were on the lookout for it detecting likely data manipulation is generally going to be much more time consuming than can resonably be expected for what is basically volunteered time that actively takes away from their actual jobs. On top of all that you have to remember that a lot of fraud isn't going to be detectable based on the paper itself, if they're making up data you may need to actually look into their research process to discover this.
The music is a tad loud at the start of the video, just fyi
In the process of submitting a manuscript and yes, you simply have to declare that you have no conflict of interest. Basically you pinky promise.
Pete, you should do a statistical analysis on all types of scientific fraud to establish a general understanding on the extent and magnitude of this problem.
That is a massive undertaking for one person
@@DrJTPhysio shoot I'll help if he shows me what to do lol
That would be something that would require a pretty massive research grant to do and would be field-specific as he said, but I think the basic signals are there: Unbelievable sustained publication rate is, in my view, the sine qua non. Unfortunately, universities and granting agencies really do like their rock stars, not us more ordinary working faculty who are the ones who make the university run and publish at a more reasonable rate. Some years we have a lot of articles (my best year had 7 articles) and other years are more down years (uh... 0, or 1).
@@DrJTPhysio - start with a pilot study. Sample of N papers selected at random from all published original studies within X field (or from c search term), with primary authors university faculty, between Jan. Xxxx and dec. Xxxx
Or
N number of primary research papers selected from total pubs new pharmaceutical agents in 1989 versus 2024 that demonstrate conflict of interest as defined by yada yada
@@ColdHawk there's a bit more to it, but I get where you're going. I'm working on a study that implements a similar research design. Doing this alone would be pure pain.
Not a red but orange flag is someone getting too many successful grant applications from fields other than their own, for example, AI to address some topic in the humanities.
The wealthy always win. Always. 💪😎✌️ No exceptions. Facts don't matter. Science is for geeks. MONEY rules all.
That's just fraud/embezzlement
Graphic distortions e.g. truncated axis on a graph but uninterrupted plot. Not fraudulent as much as deceptive
The way I catch them is by watching Pete judo's channel
Those are some great points to look out for and quite nice how easy it is to check for red flags.
Data availability. One paper i wanted to look at the data myself. It was apparently a PDF. However the data was protected by a password. I was able to copy the results by hand but this was a nasty trick
It's funny when they say "Upon reasonable request," as if there is such a thing as a request to see data (personally identifying information notwithstanding) that isn't reasonable.
The number really depends a lot on authorship level, field, and subfield. For example, Erik Demaine, who is in my field, and overlapping with some subfields of mine, publishes around 20 papers a year, and is well respected. Since it is CS theory (AKA, math stuff), there is no data to be faked, and I haven't ready any flawed proofs of his. But certainly, the more papers that is published by someone, the more I'm suspicious. For social sciences and physical sciences, I would be very suspicious of even matching Erik's publication rate.
The solution is to make it irrelevant to have large numbers of papers. Use a logarithmic metric, with a maximum at --say-- log(12 papers/year) and decreasing for larger number pf papers per year down to zero if you publish --say-- 24 papers or more per year. Actually I think the numbers should be closer to half of those above.
Thank you Pete.
The question depends not only on field but on what “publication” is.
There’s a “tradition” of putting as authors people who have contributed to the paper, so if you built some machine that say 30 grad students are using, and they each publish 2 papers, it wouldn’t be rare to have 60 publications without you having to do pretty much anything.
I hate how academics trade and game publications, but I wouldn’t jump to conclusions based solely on the number of publications.
I think the number one way to catch bad science ought be replication.
Requiring independent replication of results will be a much more reliable way of finding bad science and bad scientist than counting publications, auditing for conflicts of interest or investigating images. Theories built on bad data will not stand up under replication regardless or whether the data were fraudulently made up, the result of unintentional methodical problems or bad luck.
I publish dozen or more papers a year, though only a few are first/sole author. In planetary science we often work in broad flat teams of individual 'independent' scientists associated with space missions (without the more feudal lab head/minion hierarchy associated with a lab). The mission data are contractually obliged to be publicly available.
About people with an impossible number of publications: what is pretty common is for an influential academic (typically a prof) to be systematically named as a co-author by his faithful graduate students (and other junior academics); the influential academic boosts his h-index, while the lowly graduate students and junior academics increase their odds of being published, being awarded grants, progressing in their career, etc. wink wink nod nod, it's practically a right of passage at this point.
Yup. Rich gotta rich. It has *nothing* to do with logic, data, science, legitimate analyses, etc.
Indeed. This is a problem with incentive structure of academia.
The first thing that should be done is to pay reviewers for their time and have a grading system for reviewers. Reviewers are incentivied to spend as little time as possible on reviewing a paper. Reviewing time should be mandated on an institutional level and paid for by the cost to publish fee by the for-profit publishing industry. Yes, this may lead to higher cost of publishing and slower publishing, but also fewer fraud cases and less retraction rate of papers.
Regarding the scientists publishing a ridiculously high number of papers. Is that really a sign of fraud or does it just mean that the scientist is running a huge lab and all the junior researchers are putting his name on their work?
That would be a possible sign of overreaching. What could be his contribution? Some of these "authors" never read the paper.
Even with a big group, 200 papers is way out of reasonable. There is no way that person has seriously contributed to those papers. I’d be surprised if they had even read them all.
@@AndrewJacksonSE True - But signing your name on to a paper you haven’t even read is a very different issue from research fraud.
@@danielschein6845 indeed, but seems to be conflated in a lot of comments on this type of video. Also, it inflates the risk of errors or fraud by the main author or contributor not getting spotted.
Except that is also fraud since it isn't their work
Great video like always, thanks!
I wonder, though, if you could also look into the darker fallacies of science? The ones that are done more on an unconscious level. The obvious examples are (and I think you already touched upon those in past videos):
- Statistical correction for multiple testing. In biology, p>0.05 is widely accepted as "significant", after Bonferroni (etc.) correction for multiple testing. All that means that, on average, 1 in 20 studies will yield a "significant" result. Well, in certain fields, hundreds of papers are published every year - so we end up with all the false positives, while the negative results are much less likely to see the eye of the reader.
- Statistics in general (I won't go into cohorts here, that's a topic all by itself). Statistics is based on a random distribution, whatever that distribution might be. Especially biologists, who are not experts in statistics, working with statisticians, who are not experts in biology, can easily produce way to optimistic p-values, without being aware. In my experience, reviewers only rarely catch that, because they are either biologists or statisticians.
- Reproducibility. This is particularly apparent in GWAS studies, only a tiny fraction can ever be reproduced by anyone else, and even if, never exactly. Yet, the claims of GWAS ("you have a 14% higher chance of getting this or that disease if...") are often widely reported by the media, hence the incentive to do these studies. Even if the statistics used is sound, this comes down to case vs. control selection, sampling bias, etc., which invalidates the underlying assumptions. I think there is a need to also publish negative results wrt reproducibility, as well as positive ones. Because the proof is ultimately in the pudding.
All in all, yes, there are the obvious bad apples in the scientific community, the ones who willfully falsify results. I think these are in the minority though, and that most false results are published out of (tolerated) ignorance.
Very good discussion.
I think point 5 can be a problem in some areas of research, where privacy requirements pull against data sharing. For example, getting permission to release data from actual patients or minors can be quite onerous.
That said, bad faith researchers can and do make use of these requirements as a shield. One of the worst examples I've encountered in my professional existence---won't name names but I'm talking B grade horrid, not A grade like the ones that have been getting outed to substantial publicity, such as that real peach Francesca Gino---loved to hide behind the IRB. In my time working with that team, I didn't see any data made up, but I did see quite a lot of really shady data practices.
You should name them or at least the practices
@@user-vb3ly7ib4r I'm not naming names on TH-cam, but I filed complaints to the relevant authorities, including the grant agency.
As to the practices, basically the PI would state that data would not be released due to FERPA (educational data privacy law) but then was perfectly happy to do things that pretty clearly violated FERPA, such as give out datasets to people on the team who had no business having things like participant names. Simply put, she didn't want to have anyone else seeing the data. I wasn't convinced she understood the difference between research and data analysis done for course improvement, quite honestly. She's one of those people who's charismatic and clever, not actually smart.
@@crimfan send the deets to Judo my man
Great topic, thanks
The french Didier Raoult fills all the boxes.
200 papers a year?!!! That's beyond suspicious
Excellent video.
I effectively spent a year on my MS thesis. Under other circumstances, I could maybe have broken it into 3 or 4 papers, max.
Regarding the "10 Papers a year" thing. The reason why I am stating this, is because I assume to be an author you need to at least have "read" and "understood" it. Both of these need time. if you are publishing a paper a day, when are you actually doing the data generation part?
Ultimately, it's up to scientists to conduct replication studies to check each other. The system isn't incentivizing replication remotely enough.
There is a problem in scientific culture. Many treat science merely as a career or a game, where getting ahead is much more important than the often directly competing concern to do good work that will stand the test of time. Publishing is just a box to check. At the fringes of this are the frauds but in the middle is occupied by people who forget the actual purpose of doing science.
Beware of generalizations ..... "data available upon request" or "data available at http...." in many cases is a move in the good direction you state (and which I support) and the only means of telling your potential readers that you're willing to share your data.
It's a good generalization because the data is not available
Single authorship on all or most papers someone publishes is another red flag.
Another eye should be kept on journal editors, as they can help their buddies publish their research before someone else via simply rejecting a paper that tested that hypothesis first. Also, journal editors who gatekeep new directions in the field as a favour to their buddies is a form of scientific misconduct.
As someone else pointed out, a search of how many harassment complaints are against a researcher is an indication that they have also gotten engaged in scientific misconduct.
this is a great video, everyone needs to watch this!! thank you for consistently sharing valuable information through your videos.
Do you "first author"? I find it very surprising you didn't specify this. Last authors, for example, are typically lab/science area heads who will appear on every paper authored by their team.
Do you consider results that are very socially popular as falling in the "conflicts of interest" category? Maybe affecting the works of the likes of Roland Fryer and others who research such touchy topics?
If a pseudo-scientist hits on results which the general public WANT to see as being valid and true, you can bet that the P-hacking will commence, baby! 💪😎✌️ There's HUUUGE money in telling billions of people what they already hoped was "true". 😂
If the results support existing political rhetoric then it's fraud. I find this when reading history all the time, no further study necessary: Fraud.
"right to jail" hahahahaha, great video
you should cover what the scientific community is proposing doing about this (fake data, but also p-hacking, replicability, publication bias etc), i think its a known problem to many scientists
also the history of how and reasons why we got such ridiculous seeming systems like not having to publish the data along side your paper
How do you get the scientific community and journals change their baseline practices? Is there a committee/professional organization that defines these?
Keep up the good work.
7:40 I think this is unfair. Sometimes the dataset is just very large to host online. Sometimes the data is confidential. As for the codes, the ideal is indeed to release them. From experience though, well-documented working code that reproduce all the results with graphs is sometimes almost as much work as writing the manuscript itself. But most of the time when I wrote to an authors for their codes, they were kind enough to share them with me.
What is the point of academic journals if they don’t already do all of this??!! All this time, effort and resources that could be used to do ACTUAL RESEARCH but has to be wasted on this - not to mention all the funding that they take from honest academics!! For just the autism article ALONE The Lancet and everyone involved should go “straight to jail!” 😡
can you please make a video on how to spot ai generated text in papers? My professors are saying "it's so obvious by the way ut is formated" but i can't really see it. Can you please share your thoughts on how to spot it?
No idea how you can not publish the data set but somehow your findings are 'peer reviewed'
Maybe they can sign an honesty pledge at the top of the submission process. I have heard it makes people be more honest 😂
I....publish at the rate of 200 per year, but I take days off, sometimes weeks.
I would think one significant paper per year as lead author, or several related ones as lead author, is the maximum.
Good video idea!
How are people Who watch your TH-cam video justified or educated enough to determine how many publications per year are too many?
If one person publishes 10 papers in one year and then Publishers only one paper for the next two years how can and essentially uneducated populous, decide that this person has committed fraud?
Initially your channel was wonderful and brought about many feelings of the system.
Since that time it appears that you have become extremely enamored by yourself and are putting out information that is Clickbait and dubious at best..
I don't agree with you on the Data Availability Statement (below a suggestion). Data in biochemistry etc is typically very simple, there it can be standard practice. However, often the raw data impossible to handle, if you're not an expert in the field - typically there are maybe 100-1000 true experts in each specific subfield.
Therefore, first, randomly upload data for the community won't really benefit anyone. The chance ppl will wrongly treat the data out of missing expertise is just really high. Second, making everything available we will just feed AI to know better, how to make raw data, which then will be used by asshole scientists to create fake raw data and deposit it.
Therefore, another suggestion:
First, here over in Germany, the German Research Foundation requires universities to store ALL data. If you don't do that, you won't get funding.
Second, nowadays every journal provides paper statistics. Just add one for "Requests / Data shared / Not shared". Thats even better because honest scientist (who the majority) love it if somebody shows interest AND uses their data and has to cite them!
In this way data is available, support is provided by the authors, the community communicate, and we will easily spot assholes.
I recommend a future video dive into Avi Loeb, because he publishes waaay too much to not be suspicious
I woud not say that "data available upon request" qualifies automatically as a lie. My university demands by contract that our data and code is uploaded onto a university server (its their property not mine). If I would not respond to other scientists asking for the data, they could ask the university which hands it out to ensure reproducibility of the results. I hope more universities start implementing such standards. Of course this does not help if the data itself is subject to misconduct.
Given most peer to peer emails get sent to spam folders, this is the same as not providing the data
@@samsonsoturian6013 I get constantly e-mails from other scientists. I never experienced this issue. Notice also that you can contact the university or department directly if I do not respond. I mean what is the claim here, that emails dont work?
Historian here: We don't have an incentive to publish surprising results. For instance, one submission I sent was rejected unread because I refused to say that a particular battle was part of a wider conflict between "white men" against "indigenous peoples" because it was simply not so (the battle was between US cavalrymen and unidentified Indians in Mexican service).
What's the difference?
@fromabove422 vhut? These Indians weren't involved in any other conflicts we're aware of and they didn't like me saying that.
@@samsonsoturian6013I guess context matters
@@fromabove422the context is these were unidentified Indians in Mexican service stealing cattle from Federals
These are all reasonable ideas to catch basic frauds. We should remember though that this is an adversarial system and fraudsters will get better at beating basic automated checks, so we'll really need to go deeper over time and maybe even change the way science is done if we really want to root out fraud.
You must do a video on Fauci, if you haven't already.
*_comment for the algorithm gods_*
~ Thanks! Winston Salem, NC
Oh wow, glad to see someone else in this town have critical thinking skills! It becomes more rare each year here!
@@robertharper3754 It's a sad fact of reality here in W-S, with many unfortunate down-&-upstream effects. Thanks for the neighborly show of solidarity; your reply gave me a much-needed boost of optimism in these otherwise dark & unpleasant times!! Perhaps W-S isn't an entirely blasted toxic wasteland, after all!🤷♂️ 😁💞✌️
We're all way too careful. Don't be afraid to hurt feelings of 0.1% if the upside is removing the filth of bad research. We just need to require more evidence from suspicious actors. >10 papers a year? You must supply all of the raw data, with very specific requirements for details. I think the requirement should be "An external non-field related person should be able to deduce the details of the experiment: how the participants were contacted, what they were given at what time. If this was a mechanical/chemical experiment, there has to be equipment specs, settings details." So that replication is no longer a guesswork, and there aren't "obvious" things that field-related scientist like to omit. For instance I know every detail Maxdiff study. I may just say RLH was X and expect the reader to understand. Such expectations should no longer be allowed. Specify the formula, and how you obtained it. Was it individual scores, aggregate scores, etc
Data should be made available to readers definitely because how else will we verify results? 200 papers a year by 22 academics is crazy. Must be AI generated.
Butterfly net. Works every time.
Good topics to do a deep dive and do more exposure to how there are very questionable so called experts.
Can you elaborate more on the level of data manipulation effecting university ratings ?
I'm aware of Wakefield's conflict of interest and the problems with his work but I am perpetually amused by all the bleating labeling him AntiVax when he was actually trying to hawk a competing vaccine all along.
I have a p-value of 1 guys, using Francesca Gino's data, how excellent !
I would also add that if the study is from Harvard, then it's doctored.
Do they refer to themselves as a scientist? Bonus points if additional modifiers such as 'behavioral' 'political' 'social' etc.
If movies have taught me anything, it’s that you should automatically distrust male scientists with long hair.
DP!
Feynmann could consistently publish surprising results...
I think the rise of AI tools is going to make faking a paper much, much easier. Your list is a very good start, but, ultimately -- in about five years! -- I think most work, especially by limited groups, will need to be independently validated to be trustworthy. (And that will require serious funding.) That sounds like a huge waste, but I wonder if it will cost more than the hidden costs that we're already suffering from junk science leading researchers astray. (And let's not talk about the huge societal costs of faulty public programs based on bogus research!)
I just finished reading another Carl Elliott book, his latest: The Occasional Human Sacrifice. Fraud isn't the half of it.
Look into studies with many deaths.
Brooo don't leave us hanging on that ominous note. People be hiring hitmen off the dark web to off academic researchers or what
You mean where people may or may not have died due an experiment? Probably doesn't happen much, even frauds feel bad when people get hurt
On it
Whoever works for the CDC..
What is your opinion of EVs? Fraud or over-hyped?
His opinion is irrelevant
Like Dr Nefaurios or Like Climate Change Scientiest?
The problem is that with the recent climate, if you dispute anything - whether it be conflict of interest, rate of publication, or any of the five ways you described, you'd be labelled anti-science, conspiracy-theorist, right-wing (as if science were exclusive to one political affiliation), etc. And if you speak with a scientist about it, the first thing they do is ask for your credentials as if it's the degree that enables someone to use critical thought and discern bad science.
(1:42)
..."they" aren't writing shit😂 ....there are plenty of sites out there that have freelance writers, editors, artists, proofreaders and the whole publication market for hire...potentials put their experience and rates up for grabs and do the writing or whatever is needed without question....follow the scientist's names to these sites and I promise you'll end up with a Bingo! or three....
...as per the end question, the answer varies from a real net to a sting operation and subpoena....
P-Hacking.
Great Summery :)
Bro wtf they're trying to kill your video, it's buffering every few seconds on 480p for no reason
3:00 Note that Wakefield's critics also were paid for by people that owned vac patents. UC Davis was give labs and tons of money. The biggest criticism was that he used a small sample size. That is what they do to! Thats what everyone starts with and then goes to larges size.
Sample size was not the biggest criticism.
Viewing your presentations creates in me a desire more and more fraud to be committed so that you have ever more content to present..but then there is already more fraud than you can cover.
Issue #1, publication rate. I suspect you're forgetting that junior scientists (grad students) publish a paper, it takes a year or more, but our supervisor(s) automatically get attached to the paper. Automatic. So, if a prof has 10 students, he/she easily has 10 per year papers, without doing any hands-on personal work themselves, with e.g., other colleagues. (Same with patents). Names are attached out of respect, and obedience. Not my place as grad student if dept head wants his/her name on my paper to say "why".
So, the 'big shots' of academia get bigger because clout-buys-clout, just like money-begets-money. Those who actually do the creative work, well, we get a PhD degree. Not a bad trade, maybe.
That may be standard practice but that is just another example of academic corruption and historical fraud. No one should be on a paper who did not significantly contribute to it. Providing the resources is not a reason to be an author. Should the funding agencies be cited as authors too? Funding and resources should be cited as a thank-you notice.
The point of the senior author role is that they set the initial plan for the research (by writing the grant), and should be checking the work that the others have done. The vast majority of PIs *are* involved in planning experiments, discussing results, advising the postdocs and students on analysis etc.
But that is also a form of fraud since prof's name is attached to work they didn't do
>names are attached out of respect and obedience
Ah, so fraudulent misrepresentation of the authorship roles. Got it.
@@samsonsoturian6013 not at all. That is a fundamental misunderstanding of the scientific research process. Almost all science is collaborative, and PhD and Postdoc positions are fundamentally education and training to become an independent researcher. The PI / senior author is there to lead the research - this is a key contribution, directing the work of the group and giving key intellectual input to the research activities. There are many research group leaders who do lab work/classical research activities, but If PIs had to be in the lab doing all the work, there would be no time to support students and postdocs, write grant applications, and engage in collaborations. Modern science would fall apart.
These days many journals require a contribution statement, which explicitly says what each author contributed to.
Really annoying background music (too loud) places this vid firmly in the TLDR category. (Too Long, Didn't Watch, so TLDW)
I’m sure this applies to Global Warming.
i heard that actually, global warming is more serious than previous papers say because they adjusted something related to the clouds? a physics woman talked about it on youtube
@@ujubin For clarity, there were two models of the atmosphere, predicting weather. One was based on historic trends, sediment deposition and ice samples, and one based on modern weather measurements for weather forcasts- the weather forecast people had to update their models to get accurate results because they weren't getting the same patterns over the last 20 years.
The people using the modern measurments ran the historic data and got a 'this can't be right' high number for global temprature average, eventually it was figured out that the effects of some clouds was different - we've been getting more of them than historic trends indicated due to things like unintentional cloud seeding with aircraft, as well as miscalculating how reflective those clouds were, and the 'oh shit' global warming numbers were accepted as being accurate after a lot of people looked at the data.
A lot of the climate scientists I've been following have been sounding more and more like survivalists. Not like 'humanity is doomed' bad, but 'we're gonna have a bunch of wars over water supply' bad. We still have the tools to stop climate change, its just gonna be a lot messier using them.
Except the data comes from many different sources. The evidence is overwhelming, and as much as you don't want it to be true, it doesn't seem to change the more they look into it.
There's certainly a lot of bad science, but all broad judgments is just political bullshit
@@kablamo9999that means nothing
On your image manipulation section you bring up Elizabeth Bic's work in the context of fraud. I haven't watched your previous videos and you have the impression that she was someone who had committed image manipulation. Only later so you make clear that she's exposing fraudulent use of images by others.
You need to be more careful and not assume everyone watching your videos has seen previous videos and make it clearer who is committing the fraud and who is exposing it.
Covid?
How do you know if a scientists is a liar?
They are published.