> A Harvard University probe into prominent researcher Francesca Gino found that her work contained manipulated data and recommended that she be fired, according to a voluminous court filing that offers a rare behind-the-scenes look at research misconduct investigations.
I thought this was going to be about Dan Ariely, who has been mixed up in a similar controversy, though idk if Ariely's saga has reached a conclusion yet.
Added: aha, Ariely is at Duke rather than Harvard. Can't keep track without a scorecard.
Added 2: Andrew Gelman blog post from Thursday about the Gino finding:
I haven't followed this case but I found the blog posts doing the initial investigation quite interesting. Not only due to all the errors in the data but also because it gives some insight into how Excel works behind the scenes:
I'm confused by her suing and her argument in court though. Is her argument that they didn't catch her in front of the computer so someone else might have fauxed the data or is her argument that no data was altered? Because it seems undeniable that the data was altered to align with the hypothesis.
To be a Harvard academic, you need to do high-profile research. That has three components:
- Academic ability
- Willingness to cheat
- Shameless self-promotion
Competition is extreme. As a result, someone who is not "strong" on all three axes would need to be truly astronomical on one of them to make it through the hiring filter.
This is true for all elite schools. That's why you see groundbreaking result after groundbreaking result from the elites (most of which don't replicate). Things get a lot better for integrity one or two tiers down, but the culture is quickly spreading.
Due to my career path, I've had a lot of visibility into the innards of many schools, including Harvard, and the level of research fraud there is high. The cases where it's discovered are rare, and when it is, the vast majority of the time, it's covered up. I can't speak for Harvard directly here, but I can say that the outcome at e.g. MIT when research fraud is discovered by a high-profile researcher is an NDA to everyone who learns about it, rather than a correction or a firing.
Coincidentally, similar logic applies to most extremely competitive career paths. If you'd like to know why career executives and senators are mostly crooks, it's because they need to be at the top of their game to get there, in a game-theoretic sense.
If you don’t mind sharing, is your career also in psychology like Gino’s? Or do you mean to say that engineering/CS also has these problems with cheating at elite schools?
My personal field is irrelevant, since my work let me see across fields (for reference, most of my direct work as relevant to this discussion was in the social sciences, though -- that's the project which let me interact with large numbers of academics across institutions and fields).
The short answer is that what I saw was the level and means of cheating roughly correlates with the degree to which it is possible.
In a lot of engineering papers, if I publish a new material, mechanical structure, or electronic circuit, most people will be able to:
(1) tell how it works just by inspection
(2) if it's useful, try to use it in an engineered system
Cheating would be caught very quickly, at least for any interesting result, so it's much less common than in fields like social sciences.
Computer science is in between. There is a growing pile of b-llshit, since a lot of the work is squishy. Something like a user study can certainly be doctored, a data analysis can be p-hunted, and results can be overstated. On the other hand, something like the big-O of a new algorithm isn't something you can really cheat on.
There are also fields like [insert minority group] Studies or [insert domain of art / music / literature] Analysis, where it's not so much direct fabrication (since there is no data) as writing papers for an inner circle of mutual adoration. "Research" is mostly around stroking egos of people who make decision around hiring, promotions, publication, and funding. I'm not quite sure how to describe that, since it's not really cheating, but very little new knowledge is generated.
Footnote: What's interesting is MIT used to be super-honest in the nineties with computer science research at both AI Lab and LCS (which have since merged into CSAIL). The Media Lab really pioneered (by the standards of the time) b-llshit computer science research. It was a running joke at the Institute. In the decades which passed, the Media Lab stayed roughly where it was, while CSAIL's integrity fell, and now the Media Lab feels much more honest than CSAIL.
Footnote 2: This post should be viewed as much more anecdotal than the one before. I have a very high level of confidence making cross-cutting statements as in my original post. Doing field-by-field dives is just personal observations, so this post, I'm responding to your question, but please just take it for what it's worth. It's small n by field-cross-school.
Although I agree with your general point (to be a successful Ivy League academic you have to be quite an outlier, therefore there is pressure to cheat), it isn't specifically true that you need to be "strong" on willingness to cheat and shameless self-promotion.
There may be disciplines where this is more true, but it is definitely not required in the humanities, for example (perhaps because research is not empirical, so "cheating" isn't a hack that gets you ahead).
I actually know some successful academics who are very humble, and have zero willingness to cheat. The reason they have been successful is because they are extremely talented, well-liked, and also somewhat lucky.
Academia was very honest for most of history. From WWII through roughly 1980-2000, there was almost exponential growth in the number of academic jobs available. At the time of WWII, about 5% of people had college degrees. Today, about 2/3 of people enter college.
That near-exponential growth meant there while each professor had a few grad students, and there were enough faculty openings for the students who were both talented and wanted to go into the academy since new schools were opening up.
The extreme competition came in when this growth stopped -- college enrolment can't go above 100% of the population. For every professor, there are still many graduate students, but a position at a research institution only opens up when that professor retires. The whole dynamic changed.
Culture doesn't change overnight either, so things remained pretty honest for a few years. The present level of wholesale academic fraud is a relatively new phenomenon.
Professors in their early 40s. The job market is indeed very tight, so I can see why there would be pressure to hit every conceivable metric. But some people are unfailingly honest, and some disciplines don't lend themselves to fudging.
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[ 4.2 ms ] story [ 15.1 ms ] threadhttps://www.npr.org/2023/07/27/1190568472/dan-ariely-frances...
I thought this was going to be about Dan Ariely, who has been mixed up in a similar controversy, though idk if Ariely's saga has reached a conclusion yet.
Added: aha, Ariely is at Duke rather than Harvard. Can't keep track without a scorecard.
Added 2: Andrew Gelman blog post from Thursday about the Gino finding:
https://statmodeling.stat.columbia.edu/
[1]: https://datacolada.org/109
https://datacolada.org/109
https://datacolada.org/110
https://datacolada.org/111
https://datacolada.org/112
https://datacolada.org/114
I'm confused by her suing and her argument in court though. Is her argument that they didn't catch her in front of the computer so someone else might have fauxed the data or is her argument that no data was altered? Because it seems undeniable that the data was altered to align with the hypothesis.
To be a Harvard academic, you need to do high-profile research. That has three components:
- Academic ability
- Willingness to cheat
- Shameless self-promotion
Competition is extreme. As a result, someone who is not "strong" on all three axes would need to be truly astronomical on one of them to make it through the hiring filter.
This is true for all elite schools. That's why you see groundbreaking result after groundbreaking result from the elites (most of which don't replicate). Things get a lot better for integrity one or two tiers down, but the culture is quickly spreading.
Due to my career path, I've had a lot of visibility into the innards of many schools, including Harvard, and the level of research fraud there is high. The cases where it's discovered are rare, and when it is, the vast majority of the time, it's covered up. I can't speak for Harvard directly here, but I can say that the outcome at e.g. MIT when research fraud is discovered by a high-profile researcher is an NDA to everyone who learns about it, rather than a correction or a firing.
Coincidentally, similar logic applies to most extremely competitive career paths. If you'd like to know why career executives and senators are mostly crooks, it's because they need to be at the top of their game to get there, in a game-theoretic sense.
The short answer is that what I saw was the level and means of cheating roughly correlates with the degree to which it is possible.
In a lot of engineering papers, if I publish a new material, mechanical structure, or electronic circuit, most people will be able to:
(1) tell how it works just by inspection
(2) if it's useful, try to use it in an engineered system
Cheating would be caught very quickly, at least for any interesting result, so it's much less common than in fields like social sciences.
Computer science is in between. There is a growing pile of b-llshit, since a lot of the work is squishy. Something like a user study can certainly be doctored, a data analysis can be p-hunted, and results can be overstated. On the other hand, something like the big-O of a new algorithm isn't something you can really cheat on.
There are also fields like [insert minority group] Studies or [insert domain of art / music / literature] Analysis, where it's not so much direct fabrication (since there is no data) as writing papers for an inner circle of mutual adoration. "Research" is mostly around stroking egos of people who make decision around hiring, promotions, publication, and funding. I'm not quite sure how to describe that, since it's not really cheating, but very little new knowledge is generated.
Footnote: What's interesting is MIT used to be super-honest in the nineties with computer science research at both AI Lab and LCS (which have since merged into CSAIL). The Media Lab really pioneered (by the standards of the time) b-llshit computer science research. It was a running joke at the Institute. In the decades which passed, the Media Lab stayed roughly where it was, while CSAIL's integrity fell, and now the Media Lab feels much more honest than CSAIL.
Footnote 2: This post should be viewed as much more anecdotal than the one before. I have a very high level of confidence making cross-cutting statements as in my original post. Doing field-by-field dives is just personal observations, so this post, I'm responding to your question, but please just take it for what it's worth. It's small n by field-cross-school.
There may be disciplines where this is more true, but it is definitely not required in the humanities, for example (perhaps because research is not empirical, so "cheating" isn't a hack that gets you ahead).
I actually know some successful academics who are very humble, and have zero willingness to cheat. The reason they have been successful is because they are extremely talented, well-liked, and also somewhat lucky.
Academia was very honest for most of history. From WWII through roughly 1980-2000, there was almost exponential growth in the number of academic jobs available. At the time of WWII, about 5% of people had college degrees. Today, about 2/3 of people enter college.
That near-exponential growth meant there while each professor had a few grad students, and there were enough faculty openings for the students who were both talented and wanted to go into the academy since new schools were opening up.
The extreme competition came in when this growth stopped -- college enrolment can't go above 100% of the population. For every professor, there are still many graduate students, but a position at a research institution only opens up when that professor retires. The whole dynamic changed.
Culture doesn't change overnight either, so things remained pretty honest for a few years. The present level of wholesale academic fraud is a relatively new phenomenon.
Professors in their early 40s. The job market is indeed very tight, so I can see why there would be pressure to hit every conceivable metric. But some people are unfailingly honest, and some disciplines don't lend themselves to fudging.