6 ms·

> Problem 1 is morally worst and much more common than one would hope. Outright fabricated data in a Nature or NEJM publication (as has happened) is a disaster.

by nextos 1y ago

> Problem 1 is morally worst and much more common than one would hope. Outright fabricated data in a Nature or NEJM publication (as has happened) is a disaster. In my experience, fabricated data is rare. But cherry-picking data and misuse of statistics to prove the desired hypotheses is extremely common in top journals from e.g. the Nature Portfolio journal family. I'd say at least 1/5 of the articles in biology and medicine have serious methodological errors. IMHO, the main reason are perverse incentives and power imbalance. If you are a student or a postdoc and you get pressure from your supervisor to obtain certain result and you refuse to engage in academic misconduct, you will get pushed out of most projects and this might be the end of your academic career. In contrast, there are few, if any, consequences for the senior scientists and principal investigators who perpetuate this culture. There's no oversight, no integrity checks, nothing. Universities tend to ignore even clear cases of data fabrication and fraud, where e.g. images derived from experiments are fake. Ultimately, this creates selective pressure for misconduct, as those willing to bend the rules are rewarded.

nothercastle 1y ago
The advisor gets all the credit for publishing and none of the blame for retracting. That’s why some labs have been hit by multiple retractions (clearly a indicator of fraud culture) but only the low level researchers are punished
- echelon 1y ago
  The problem is that academic publishing isn't tied to any real fitness function. Unlike a startup or company or some other thing where you vote with dollars on utility, many papers can't be quantitatively evaluated on how much they contribute to science. Some papers are obvious and groundbreaking, but a lot of research is at such a frontier that literally no one else can evaluate it. You just nod your head and trust it. That, coupled with the fact that negative results just aren't published, is incredibly inefficient and disheartening.
- KolibriFly 1y ago
  That dynamic is deeply broken
btilly 1y ago
The widespread belief that it is rare, is an invitation to fraudsters. Who have therefore wound up in such positions as president of Stanford. It is hard to catch them because people's a priori belief that there isn't much fraud makes it hard to accept that any particular researcher could be a fraudster. Which greatly reduces the risk of being a fraudster.
- BobbyTables2 1y ago
  It’s also just not fraud. Well meaning students have little alternative than to publish journal papers showing how their algorithm/method had a 0.001% improvement (measured by questionable metrics) because they are trying to get N publications to graduate. While discourse about such methods can be beneficial, it also tends to create too much noise that drowns out more meaningful work.
- nextos 1y ago
  Just to clarify, I think fabricated data in top biology and medicine journals is relatively rare because it's typically high-throughput data, and you must archive it. It's just too much trouble to fake that. However, another equally damaging form of fraud, cherry-picking data and manipulating statistical inference is common. I think the reason is that it's much simpler to get the results you want this way, and you are much less likely to get caught. Previously, fake data was common, e.g. in the form of fabricated Western blots, as it has been proven by large-scale image analyses conducted by sleuths. I imagine similar forms of fraud are still frequent in other disciplines or in domains that generate low-throughput data, such as some clinical trials.
mike_hearn 1y ago
That's all true but I think what you meant to say is that successfully detecting fabricated data is rare. I've been in the weeds on this and after a while it's tempting to believe you can always spot scientific fraud by reading papers, but of course it's not so. A paper is just a bag of words and pictures, it can say anything it wants. As long as a data fabricator doesn't make basic errors you won't detect fraud. Unfortunately, when people do find ways to automatically detect inconsistent numbers in a paper, like SPRITE or GRIM, they find maybe 50% of all checkable papers fail the audit and the authors almost invariably refuse to share their raw data for further checks despite having previously agreed to do so. So it seems likely that fake data is actually not rare at all but very widespread. Caveat: like I say in every comment on scientific fraud on HN, all this varies dramatically by field. Some fields are much more corrupt than others. That 50% number is from psychology. Computer science isn't that bad relative to others. But for example, in climatology it's taken as axiomatic that it's OK to fabricate data and then present it as "observations". Anyone who tries to call them out on this behavior gets attacked, censored or even sued, yet if you did the exact same thing in physics nobody would hesitate to call it fraud. There isn't even a consistent definition in academia of what data fabrication means. So no, sadly we don't really know how prevalent data fabrication is. The only way to detect scientific fraud to the level of robustness we'd accept for any other kind of fraud is regular, randomized lab audits with jail time or ruinous damages for perpetrators, backed by rigorous field-independent written standards for what evidence must be provided, all checked by outside organizations. Think financial audits but for scientists. Obviously not only is academia not doing this, it's culturally nowhere close to considering the possibility of even thinking about starting. Academia has spent so many years engaging in such deep ideological purges that everyone who remains is at minimum sympathetic to ideas like "defund the police". The concept of policing themselves to the level accountancy does will never come up, not even during discussions of reform.
- adornKey 1y ago
  To me it's quite simple: * If there's no clear way to get the raw-data * If it's unclear how the data was gathered -> the results are most likely fabricated One strange psychological effect I've seen is that especially in medicine some people themselves spend a lot of time rigging data to get to their PhD, but in the end they absolutely trust in anything published in the field. "The science nowadays is so good - medical scandals today are completely impossible"

by nextos 1y ago

nothercastle 1y ago

The advisor gets all the credit for publishing and none of the blame for retracting. That’s why some labs have been hit by multiple retractions (clearly a indicator of fraud culture) but only the low level researchers are punished

echelon 1y ago
The problem is that academic publishing isn't tied to any real fitness function. Unlike a startup or company or some other thing where you vote with dollars on utility, many papers can't be quantitatively evaluated on how much they contribute to science. Some papers are obvious and groundbreaking, but a lot of research is at such a frontier that literally no one else can evaluate it. You just nod your head and trust it. That, coupled with the fact that negative results just aren't published, is incredibly inefficient and disheartening.
KolibriFly 1y ago
That dynamic is deeply broken

btilly 1y ago

The widespread belief that it is rare, is an invitation to fraudsters. Who have therefore wound up in such positions as president of Stanford. It is hard to catch them because people's a priori belief that there isn't much fraud makes it hard to accept that any particular researcher could be a fraudster. Which greatly reduces the risk of being a fraudster.

BobbyTables2 1y ago
It’s also just not fraud. Well meaning students have little alternative than to publish journal papers showing how their algorithm/method had a 0.001% improvement (measured by questionable metrics) because they are trying to get N publications to graduate. While discourse about such methods can be beneficial, it also tends to create too much noise that drowns out more meaningful work.
nextos 1y ago
Just to clarify, I think fabricated data in top biology and medicine journals is relatively rare because it's typically high-throughput data, and you must archive it. It's just too much trouble to fake that. However, another equally damaging form of fraud, cherry-picking data and manipulating statistical inference is common. I think the reason is that it's much simpler to get the results you want this way, and you are much less likely to get caught. Previously, fake data was common, e.g. in the form of fabricated Western blots, as it has been proven by large-scale image analyses conducted by sleuths. I imagine similar forms of fraud are still frequent in other disciplines or in domains that generate low-throughput data, such as some clinical trials.

mike_hearn 1y ago

That's all true but I think what you meant to say is that successfully detecting fabricated data is rare. I've been in the weeds on this and after a while it's tempting to believe you can always spot scientific fraud by reading papers, but of course it's not so. A paper is just a bag of words and pictures, it can say anything it wants. As long as a data fabricator doesn't make basic errors you won't detect fraud. Unfortunately, when people do find ways to automatically detect inconsistent numbers in a paper, like SPRITE or GRIM, they find maybe 50% of all checkable papers fail the audit and the authors almost invariably refuse to share their raw data for further checks despite having previously agreed to do so. So it seems likely that fake data is actually not rare at all but very widespread. Caveat: like I say in every comment on scientific fraud on HN, all this varies dramatically by field. Some fields are much more corrupt than others. That 50% number is from psychology. Computer science isn't that bad relative to others. But for example, in climatology it's taken as axiomatic that it's OK to fabricate data and then present it as "observations". Anyone who tries to call them out on this behavior gets attacked, censored or even sued, yet if you did the exact same thing in physics nobody would hesitate to call it fraud. There isn't even a consistent definition in academia of what data fabrication means. So no, sadly we don't really know how prevalent data fabrication is. The only way to detect scientific fraud to the level of robustness we'd accept for any other kind of fraud is regular, randomized lab audits with jail time or ruinous damages for perpetrators, backed by rigorous field-independent written standards for what evidence must be provided, all checked by outside organizations. Think financial audits but for scientists. Obviously not only is academia not doing this, it's culturally nowhere close to considering the possibility of even thinking about starting. Academia has spent so many years engaging in such deep ideological purges that everyone who remains is at minimum sympathetic to ideas like "defund the police". The concept of policing themselves to the level accountancy does will never come up, not even during discussions of reform.

adornKey 1y ago
To me it's quite simple: * If there's no clear way to get the raw-data * If it's unclear how the data was gathered -> the results are most likely fabricated One strange psychological effect I've seen is that especially in medicine some people themselves spend a lot of time rigging data to get to their PhD, but in the end they absolutely trust in anything published in the field. "The science nowadays is so good - medical scandals today are completely impossible"