9 ms·

More Fakery

152 points by rossdavidh 5y ago

bannedbybros 5y ago
j7ake 5y ago
As long as there is some quantitative criteria on which jobs and promotions depend, there will be people gaming the system. One solution is to couple this quantitative criteria with independent committees that assess people beyond the metrics, but that requires a lot of human effort and not scalable. Assessing people in ways that don’t scale seem to be the way to avoid this gaming trap in academia.
- cycomanic 5y ago
  I'd argue that it's not just that the metrics don't scale but the problem is that we are trying to find quantitative metrics for something that can't be easily quantified. The worst outcome is not even the forgeries and fakes as in this article, but more that even the vast majority of ethical academics are being pushed into a direction that is detrimental to longterm scientific progress, in particular short term outcomes instead of longterm progress.
  - lutorm 5y ago
    even the vast majority of ethical academics are being pushed into a direction that is detrimental to longterm scientific progress, in particular short term outcomes instead of longterm progress I agree. The egregious fraud is just the high-sigma wing. It's a symptom, but the real problem is how it affects the majority.
- rossdavidh 5y ago
  Interesting point; it is much like the problems of trying to assess programmer productivity.
  - _tom_ 5y ago
    I was thinking it's much like Google trying to deal with SEO. Most people optimize for high google ranking, not quality content. Google periodically changes the evaluation, in theory to reward good content and penalize bad, but people still try to game the system, rather than improving content.
- _tom_ 5y ago
  And non-quantitive evaluations are prone to favoritism and prejudice. AKA people gaming the system. I doubt there's an easy answer. Trying to better align the short term objectives with longer term ones could help, but that just makes it harder to game, doesn't eliminate it.
  - j7ake 5y ago
    It’s why one needs both. You need both undeniable productivity by quantitative metrics, as well as glowing reviews from independent panels that are not influenced by favoritism (almost like an audit).
some_random 5y ago
It's crazy to me that academic fraud isn't a more pressing concern to society in general and academia in particular. The scientific process as currently implemented is broken across every single discipline. Even subjects like CS that should in theory be trivially reproducible, are rarely so. The reproduction crisis is still going on, but only nerds like us care.
- rossdavidh 5y ago
  I think there's two problems impeding our ability to focus better on this: 1) for many people, the idea that science has widespread fraud is just hard to accept; in this respect it is similar to the difficulties that many religious communities have in accepting that their clergy could have a corruption problem 2) the solutions require thinking about problems like p-hacking, incentives, selection effects, and other non-trivial concepts that are tough for the average person to wrap their heads around.
  - SubiculumCode 5y ago
    Also: I have not seen evidence of widespread fraud. Evidence of fraud,yes. Evidence of widespread fraud no.
    - mistermann 5y ago
      Don't forget though: events proceed evidence, and evidence doesn't always follow events. Also: perception is ~effectively reality.
    - derbOac 5y ago
      That's a fair point, although fraud per se is only a small part of all the problems. There's other forms of corruption than fraud, and a lot of it falls into this zone of plausible deniability rather than outright fraud. Also, I think the problems tend to find most weight with higher concentration of power, so what matters isn't as much "how widespread is corruption?" but rather "how is corruption distributed among power structures in academics and what is rewarded?"
    - 5y ago
photochemsyn 5y ago
My own rather short academic career involved doing lab work with three different PI-led groups. One PI was actually excellent, and I really had no idea how good I had it. I caught the other two engaging in deliberately fraudulent practices. For example, data they'd collect from experiments would be thrown out selectively so that they could publish better curve-fits. Another trick was fabricating data with highly obscure methods that other groups would be unlikely to replicate. They'd also apply pressure to graduate students to falsify data in order to get results that agreed with their previously published work. The main difference between the excellent PI and the two fraudsters was that the former insisted on everyone in her lab keeping highly accurate and detailed daily lab notebooks, while the other two had incredibly poor lab notebook discipline (and often didn't even keep records!). She actually caught one of her grad students fudging data via this method, before it went to publication. Another requirement was that samples had to be blindly randomized before we analyzed them, so that nobody could manipulate the analytical process to get their desired result. If you're thinking about going into academia, that's the kind of thing to look out for when visiting prospective PIs. Shoddy record keeping is a huge red flag. Inability to replicate results, and in particular no desire to replicate results, is another warning sign. And yes, a fair number of PIs have made careers out of publishing fraudulent results and never get caught, and they infest the academic system.
- georgecmu 5y ago
  I would say that this applies even more so outside of academia. At early stages of development, a research group's or company's product is by necessity a report or a presentation rather than a physical plant's or process's real, quantifiable performance. No malicious intent is required; it's just all too easy to fool yourself or cherry-pick data to support desired conclusions when the recordkeeping is poor. In my hard-tech experiment-heavy start-up there's no way we could have made any actual technical progress without setting up a solid data preservation and analysis framework first. For every experimental run, all the original sensor data are collected and immediately uploaded along with any photos, videos, and operator comments to a uniquely-tagged confluence page. Results and data from any further data or product analysis are linked to this original page. As an anecdotal example, we recently caught swapped dataset labels in results from analysis performed on our physical samples by a third-party lab. We were able to do this easily just because we could refer back to every other piece of information regarding these samples, including the conditions in which they were generated months prior to this analysis. As soon all the data were on display at once, the discrepancies were obvious.
qchris 5y ago
My favorite article on this topic is "Escaping science's paradox" by Stuart Buck[1]. I'm, in particular, interested by the idea (at least within the United States) of "red teaming" science. This would involve having an independent agency funding attempts to replicate (and to find/publish flaws in) NSF- or NIH-funded projects, and publishing those. Ideally, the history of replication for authors' papers could then be part of the criteria for receiving funding for more novel research in the future. Obviously, there's a few fields where this might not work (you can't just create a second Large Hadron Collider for validation), but in areas from sociology to organic chemistry to environmental science, I think there's a lot of promise in that method for helping to re-align incentives around producing solid, replicable research. [1] https://www.worksinprogress.co/issue/escaping-sciences-paradox/ https://www.worksinprogress.co/issue/escaping-sciences-parad...
- mherdeg 5y ago
  I took a science journalism class in college where our instructor had us read a paper and then write the news story that explained what was interesting about the result. "You all got it wrong," he said, "the news is not that Amy Wagers could not make things work with mouse stem cells the way this prior paper said this one time. The news is that Wagers-ize is becoming a verb which means 'to disprove an amazing result after attempting to replicate it'. The lab has Wageres-ed another pluripotent stem cell result. The news is about how often this happens and what it means for this kind of science." This class was in 2006 and this later profile in 2008 seemed to bear things out the way he said: https://news.harvard.edu/gazette/story/2008/07/amy-wagers-focusing-on-stem-cell-biology/ https://news.harvard.edu/gazette/story/2008/07/amy-wagers-fo...
- 0x0203 5y ago
  One thing I'd like to see is a requirement that for all government funded research, a certain percentage of that funding, say 30%, must go toward replicating other publicly funded research that has had less than 2 independent and non-affiliated labs replicate. Any original research couldn't be published until at least two independent and non-affiliated labs replicate based on the submitted paper and report on the results that can then be included with the original research. I'd like to see this across all of academia, but I imagine there are enough challenges with enforcing this in a productive manner already that doing it across all research becomes both impractical and difficult to prevent abuse. But at least with public funds, it would be nice to put in some checks to reduce the amount of fraudulent or sloppy research that tax payers pay for.
javajosh 5y ago
Could it be there's just too much science being done for much of it to be any use? And that this oversupply causes these schemes, as a side-effect? If so, selling authorship is merely a symptom of the worthlessness of most modern science. For much of human history, science was something you did in your spare time - or, if you were exceptional, you might have a patron. Then nation states discovered the value of technology and science, and wanted more, and so have created science factories. But, perhaps unsurprisingly, the rate of science production cannot really be improved in this way, and yet the economics of science demand that is does. This disconnect between reality and expectation is the root of this problem, and many others.
- SubiculumCode 5y ago
  This is in fact incredibly wrong. At least in my field, there is so much more data than there are qualified experts to analyze it. For one reason, academia pays so much less than the private sphere that post docs are leaving.
- twofornone 5y ago
  Maybe it's a deeper problem related to western liberal notions that anyone can do anything if they just "set their mind to it". We have a glut of "professionals" across industries and institutions who don't really have any business being there, but the machine requires that they appear to be useful, and so mechanisms emerge to satisfy this constraint. A consequence in science is a long list of poor quality junk publications, and few people are willing to acknowledge the nakedness of the emperor for fear of losing their positions, but because doing so may betray their own redundancy.
- seiferteric 5y ago
  Something I was wondering is if faking results is so common, then surely these things they are researching must never be used in any application right? If they were, it would quickly be found that it does not actually work...
  - HarryHirsch 5y ago
    This is exactly how it works in practice. Anyone who works at the bench learns quickly to spot the frauds and fakes and avoids them. That's the "replication" everyone talks about, no special agency to waste funds on boring stuff needed.
slowhand09 5y ago
Worked on a NASA program once, about measuring Earth Science data. We built a database application to gather suggested requirements from members of the earth science community. One such member from our own team helped develop specs for our system. After we built it, she wanted to measure its utility and usability. She watched as users navigated and entered data into the system. She also asked myself and members of my team who developed the developed the software to use it and be measured. I and one other developer (2 of 3 members) explained why we implemented each feature as we were utilizing the system. The "scientist" measuring us all promptly published as a conclusion in her paper "The usability of the system was better for inexperienced users than it was for experienced users. The experienced users took nearly 50% longer to navigate and enter similar requirements". She basically made up an "interesting" conclusion by omitting characterization of our testing session, where we explained how we implemented her requirements.
Enginerrrd 5y ago
I always thought it would be a good idea to start a journal that has a lab submit their methods and intent of study for peer review and approval / denial PRIOR to performing the work. Then, if approved, and as long as they adhere to the approved methods, they get published regardless of outcome. That would really encourage the publishing of negative results and eliminate a lot of the incentive to fudge the numbers on the data. It would probably overly reward pre-existing clout, but frankly that's a problem ANYWAY.
- Guybrush_T 5y ago
  This is done with clinical trials (or at least it's recommended). Many researchers register their study at https://clinicaltrials.gov/ https://clinicaltrials.gov/ before data collection starts. I'm not sure if something similar exists for lab based research.
- psychomugs 5y ago
  This is called preregistering. https://credlab.wharton.upenn.edu/ https://credlab.wharton.upenn.edu/
francislavoie 5y ago
Reminds me of Bobby Broccoli's video series on Jan Hendrik Schön who almost got the Nobel Prize in Physics fraudulently. Extremely good watch: https://www.youtube.com/playlist?list=PLAB-wWbHL7Vsfl4PoQpNsGp61xaDDiZmh https://www.youtube.com/playlist?list=PLAB-wWbHL7Vsfl4PoQpNs...
EamonnMR 5y ago
Does the new In The Pipeline blog have an RSS feed? I haven't been able to find it.
- jheitmann 5y ago
  This feed has been working for me: https://blogs.sciencemag.org/pipeline/feed https://blogs.sciencemag.org/pipeline/feed
  - EamonnMR 5y ago
    Thanks a bunch, that works!
epolanski 5y ago
Data fabrication is sadly the norm nowadays. I was a chemistry researcher working on renewables, and during my master's thesis 9 months were spent validating fake results (from a publication of a scientist who worked in our group moreover).
- javajosh 5y ago
  This cannot be allowed. If institutions allow scientists to publish fake papers, then science itself will fail. I hope you raised hell about this and got the researcher fired.
  - epolanski 5y ago
    Institutions don't care, it's still a publication, and would not have ways to know that anyway.
pmarreck 5y ago
Lies from China? No way! https://www.straitstimes.com/asia/in-china-honesty-is-not-the-best-policy https://www.straitstimes.com/asia/in-china-honesty-is-not-th...
moltar 5y ago
You get what you optimize for. It’s basically like SEO. You want links (citations)? No problem!
nsonha 5y ago
I think there are valid reasons why people don't trust science. It's not that we think scientists are malice, it's just they can be lazy and incompetent like people in other careers. In addition, incentives are clear in industry, they are either not clear or completely broken in academia, so the quality of their work is too much dependent on their integrity.

152 points by rossdavidh 5y ago

As long as there is some quantitative criteria on which jobs and promotions depend, there will be people gaming the system. One solution is to couple this quantitative criteria with independent committees that assess people beyond the metrics, but that requires a lot of human effort and not scalable. Assessing people in ways that don’t scale seem to be the way to avoid this gaming trap in academia.

cycomanic 5y ago
I'd argue that it's not just that the metrics don't scale but the problem is that we are trying to find quantitative metrics for something that can't be easily quantified. The worst outcome is not even the forgeries and fakes as in this article, but more that even the vast majority of ethical academics are being pushed into a direction that is detrimental to longterm scientific progress, in particular short term outcomes instead of longterm progress.
- lutorm 5y ago
  even the vast majority of ethical academics are being pushed into a direction that is detrimental to longterm scientific progress, in particular short term outcomes instead of longterm progress I agree. The egregious fraud is just the high-sigma wing. It's a symptom, but the real problem is how it affects the majority.
rossdavidh 5y ago
Interesting point; it is much like the problems of trying to assess programmer productivity.
- _tom_ 5y ago
  I was thinking it's much like Google trying to deal with SEO. Most people optimize for high google ranking, not quality content. Google periodically changes the evaluation, in theory to reward good content and penalize bad, but people still try to game the system, rather than improving content.
_tom_ 5y ago
And non-quantitive evaluations are prone to favoritism and prejudice. AKA people gaming the system. I doubt there's an easy answer. Trying to better align the short term objectives with longer term ones could help, but that just makes it harder to game, doesn't eliminate it.
- j7ake 5y ago
  It’s why one needs both. You need both undeniable productivity by quantitative metrics, as well as glowing reviews from independent panels that are not influenced by favoritism (almost like an audit).

some_random 5y ago

It's crazy to me that academic fraud isn't a more pressing concern to society in general and academia in particular. The scientific process as currently implemented is broken across every single discipline. Even subjects like CS that should in theory be trivially reproducible, are rarely so. The reproduction crisis is still going on, but only nerds like us care.

rossdavidh 5y ago
I think there's two problems impeding our ability to focus better on this: 1) for many people, the idea that science has widespread fraud is just hard to accept; in this respect it is similar to the difficulties that many religious communities have in accepting that their clergy could have a corruption problem 2) the solutions require thinking about problems like p-hacking, incentives, selection effects, and other non-trivial concepts that are tough for the average person to wrap their heads around.
- SubiculumCode 5y ago
  Also: I have not seen evidence of widespread fraud. Evidence of fraud,yes. Evidence of widespread fraud no.
  - mistermann 5y ago
    Don't forget though: events proceed evidence, and evidence doesn't always follow events. Also: perception is ~effectively reality.
  - derbOac 5y ago
    That's a fair point, although fraud per se is only a small part of all the problems. There's other forms of corruption than fraud, and a lot of it falls into this zone of plausible deniability rather than outright fraud. Also, I think the problems tend to find most weight with higher concentration of power, so what matters isn't as much "how widespread is corruption?" but rather "how is corruption distributed among power structures in academics and what is rewarded?"
  - 5y ago

photochemsyn 5y ago

My own rather short academic career involved doing lab work with three different PI-led groups. One PI was actually excellent, and I really had no idea how good I had it. I caught the other two engaging in deliberately fraudulent practices. For example, data they'd collect from experiments would be thrown out selectively so that they could publish better curve-fits. Another trick was fabricating data with highly obscure methods that other groups would be unlikely to replicate. They'd also apply pressure to graduate students to falsify data in order to get results that agreed with their previously published work. The main difference between the excellent PI and the two fraudsters was that the former insisted on everyone in her lab keeping highly accurate and detailed daily lab notebooks, while the other two had incredibly poor lab notebook discipline (and often didn't even keep records!). She actually caught one of her grad students fudging data via this method, before it went to publication. Another requirement was that samples had to be blindly randomized before we analyzed them, so that nobody could manipulate the analytical process to get their desired result. If you're thinking about going into academia, that's the kind of thing to look out for when visiting prospective PIs. Shoddy record keeping is a huge red flag. Inability to replicate results, and in particular no desire to replicate results, is another warning sign. And yes, a fair number of PIs have made careers out of publishing fraudulent results and never get caught, and they infest the academic system.

georgecmu 5y ago
I would say that this applies even more so outside of academia. At early stages of development, a research group's or company's product is by necessity a report or a presentation rather than a physical plant's or process's real, quantifiable performance. No malicious intent is required; it's just all too easy to fool yourself or cherry-pick data to support desired conclusions when the recordkeeping is poor. In my hard-tech experiment-heavy start-up there's no way we could have made any actual technical progress without setting up a solid data preservation and analysis framework first. For every experimental run, all the original sensor data are collected and immediately uploaded along with any photos, videos, and operator comments to a uniquely-tagged confluence page. Results and data from any further data or product analysis are linked to this original page. As an anecdotal example, we recently caught swapped dataset labels in results from analysis performed on our physical samples by a third-party lab. We were able to do this easily just because we could refer back to every other piece of information regarding these samples, including the conditions in which they were generated months prior to this analysis. As soon all the data were on display at once, the discrepancies were obvious.

qchris 5y ago

My favorite article on this topic is "Escaping science's paradox" by Stuart Buck[1]. I'm, in particular, interested by the idea (at least within the United States) of "red teaming" science. This would involve having an independent agency funding attempts to replicate (and to find/publish flaws in) NSF- or NIH-funded projects, and publishing those. Ideally, the history of replication for authors' papers could then be part of the criteria for receiving funding for more novel research in the future. Obviously, there's a few fields where this might not work (you can't just create a second Large Hadron Collider for validation), but in areas from sociology to organic chemistry to environmental science, I think there's a lot of promise in that method for helping to re-align incentives around producing solid, replicable research. [1] https://www.worksinprogress.co/issue/escaping-sciences-paradox/ https://www.worksinprogress.co/issue/escaping-sciences-parad...

mherdeg 5y ago
I took a science journalism class in college where our instructor had us read a paper and then write the news story that explained what was interesting about the result. "You all got it wrong," he said, "the news is not that Amy Wagers could not make things work with mouse stem cells the way this prior paper said this one time. The news is that Wagers-ize is becoming a verb which means 'to disprove an amazing result after attempting to replicate it'. The lab has Wageres-ed another pluripotent stem cell result. The news is about how often this happens and what it means for this kind of science." This class was in 2006 and this later profile in 2008 seemed to bear things out the way he said: https://news.harvard.edu/gazette/story/2008/07/amy-wagers-focusing-on-stem-cell-biology/ https://news.harvard.edu/gazette/story/2008/07/amy-wagers-fo...
0x0203 5y ago
One thing I'd like to see is a requirement that for all government funded research, a certain percentage of that funding, say 30%, must go toward replicating other publicly funded research that has had less than 2 independent and non-affiliated labs replicate. Any original research couldn't be published until at least two independent and non-affiliated labs replicate based on the submitted paper and report on the results that can then be included with the original research. I'd like to see this across all of academia, but I imagine there are enough challenges with enforcing this in a productive manner already that doing it across all research becomes both impractical and difficult to prevent abuse. But at least with public funds, it would be nice to put in some checks to reduce the amount of fraudulent or sloppy research that tax payers pay for.

javajosh 5y ago

Could it be there's just too much science being done for much of it to be any use? And that this oversupply causes these schemes, as a side-effect? If so, selling authorship is merely a symptom of the worthlessness of most modern science. For much of human history, science was something you did in your spare time - or, if you were exceptional, you might have a patron. Then nation states discovered the value of technology and science, and wanted more, and so have created science factories. But, perhaps unsurprisingly, the rate of science production cannot really be improved in this way, and yet the economics of science demand that is does. This disconnect between reality and expectation is the root of this problem, and many others.

SubiculumCode 5y ago
This is in fact incredibly wrong. At least in my field, there is so much more data than there are qualified experts to analyze it. For one reason, academia pays so much less than the private sphere that post docs are leaving.
twofornone 5y ago
Maybe it's a deeper problem related to western liberal notions that anyone can do anything if they just "set their mind to it". We have a glut of "professionals" across industries and institutions who don't really have any business being there, but the machine requires that they appear to be useful, and so mechanisms emerge to satisfy this constraint. A consequence in science is a long list of poor quality junk publications, and few people are willing to acknowledge the nakedness of the emperor for fear of losing their positions, but because doing so may betray their own redundancy.
seiferteric 5y ago
Something I was wondering is if faking results is so common, then surely these things they are researching must never be used in any application right? If they were, it would quickly be found that it does not actually work...
- HarryHirsch 5y ago
  This is exactly how it works in practice. Anyone who works at the bench learns quickly to spot the frauds and fakes and avoids them. That's the "replication" everyone talks about, no special agency to waste funds on boring stuff needed.

slowhand09 5y ago

Worked on a NASA program once, about measuring Earth Science data. We built a database application to gather suggested requirements from members of the earth science community. One such member from our own team helped develop specs for our system. After we built it, she wanted to measure its utility and usability. She watched as users navigated and entered data into the system. She also asked myself and members of my team who developed the developed the software to use it and be measured. I and one other developer (2 of 3 members) explained why we implemented each feature as we were utilizing the system. The "scientist" measuring us all promptly published as a conclusion in her paper "The usability of the system was better for inexperienced users than it was for experienced users. The experienced users took nearly 50% longer to navigate and enter similar requirements". She basically made up an "interesting" conclusion by omitting characterization of our testing session, where we explained how we implemented her requirements.

Enginerrrd 5y ago

I always thought it would be a good idea to start a journal that has a lab submit their methods and intent of study for peer review and approval / denial PRIOR to performing the work. Then, if approved, and as long as they adhere to the approved methods, they get published regardless of outcome. That would really encourage the publishing of negative results and eliminate a lot of the incentive to fudge the numbers on the data. It would probably overly reward pre-existing clout, but frankly that's a problem ANYWAY.

Guybrush_T 5y ago
This is done with clinical trials (or at least it's recommended). Many researchers register their study at https://clinicaltrials.gov/ https://clinicaltrials.gov/ before data collection starts. I'm not sure if something similar exists for lab based research.
psychomugs 5y ago
This is called preregistering. https://credlab.wharton.upenn.edu/ https://credlab.wharton.upenn.edu/

francislavoie 5y ago

Reminds me of Bobby Broccoli's video series on Jan Hendrik Schön who almost got the Nobel Prize in Physics fraudulently. Extremely good watch: https://www.youtube.com/playlist?list=PLAB-wWbHL7Vsfl4PoQpNsGp61xaDDiZmh https://www.youtube.com/playlist?list=PLAB-wWbHL7Vsfl4PoQpNs...

EamonnMR 5y ago

Does the new In The Pipeline blog have an RSS feed? I haven't been able to find it.

jheitmann 5y ago
This feed has been working for me: https://blogs.sciencemag.org/pipeline/feed https://blogs.sciencemag.org/pipeline/feed
- EamonnMR 5y ago
  Thanks a bunch, that works!

epolanski 5y ago

Data fabrication is sadly the norm nowadays. I was a chemistry researcher working on renewables, and during my master's thesis 9 months were spent validating fake results (from a publication of a scientist who worked in our group moreover).

javajosh 5y ago
This cannot be allowed. If institutions allow scientists to publish fake papers, then science itself will fail. I hope you raised hell about this and got the researcher fired.
- epolanski 5y ago
  Institutions don't care, it's still a publication, and would not have ways to know that anyway.

pmarreck 5y ago

Lies from China? No way! https://www.straitstimes.com/asia/in-china-honesty-is-not-the-best-policy https://www.straitstimes.com/asia/in-china-honesty-is-not-th...

moltar 5y ago

You get what you optimize for. It’s basically like SEO. You want links (citations)? No problem!

nsonha 5y ago

I think there are valid reasons why people don't trust science. It's not that we think scientists are malice, it's just they can be lazy and incompetent like people in other careers. In addition, incentives are clear in industry, they are either not clear or completely broken in academia, so the quality of their work is too much dependent on their integrity.