dirtmayorHarvard Scholar Who Studies Honesty Is Accused of Fabricating Findings
Oh, the irony!
Donchu think?
A little TOO ironic.
And yeah I really do think...
It's like raaaaaa eeeeeee aaaaaain
niktemadurNow there's a The Onion headline if I've ever seen one.
illogical_virtuesI thought it was one at first
I thought r/nottheonion had made the jump to the fediverse
Nah, that was empirical research ðŸ¤
It's a fascinating article title right? The story is pretty wild when you read the details of it too. most of the evidence of what happened is public and linked in the story so I encourage y'all to read them.
In short, I don't think this is isolated to this one researcher. In fact on one of her papers there are TWO INDEPENDANT CASES of statistical fraud by two different people.
Another interesting thing to note is that overall when it comes to the ability to reproduce a study, many of these peer reviewed studies do not hold up to scrutiny. One of the articles covering this story mentioned that less than 50% of the studies were able to be reproduced.
Here's another article that puts the number higher than two-thirds:
https://www.npr.org/sections/health-shots/2018/08/27/642218377/in-psychology-and-other-social-sciences-many-studies-fail-the-reproducibility-te
JoThe high rate of failure to replicate is not, in and of itself, evidence of fraud. It's primarily a problem with low power to detect plausible effects (ie small sample sizes). That's not to say there isn't much deliberate fraud or p-hacking going on, there's far too much. But the so-called replication crisis was entirely predictable without needing to assume any wrongdoing. It happened primarily because most researchers don't fully understand the statistics they are using.
There was a good paper published on this recently: Understanding the Replication Crisis as a Base Rate Fallacy
And this is a nice simple explanation of the base rate fallacy for anyone who finds the paper a bit daunting: The p value and the base rate fallacy
tl;dr p<0.05 does not mean what most researchers think it means
Understanding the Replication Crisis as a Base Rate Fallacy | The British Journal for the Philosophy of Science: Vol 72, No 4
The replication (replicability, reproducibility) crisis in social psychology and clinical medicine arises from the fact that many apparently well-confirmed experimental results are subsequently overturned by studies that aim to replicate the original study. The culprit is widely held to be poor science: questionable research practices, failure to publish negative results, bad incentives, and even fraud. In this article I argue that the high rate of failed replications is consistent with high-quality science. We would expect this outcome if the field of science in question produces a high proportion of false hypotheses prior to testing. If most of the hypotheses under test are false, then there will be many false hypotheses that are apparently supported by the outcomes of well conducted experiments and null hypothesis significance tests with a type-I error rate (α) of 5%. Failure to recognize this is to commit the fallacy of ignoring the base rate. I argue that this is a plausible diagnosis of the replication crisis and examine what lessons we thereby learn for the future conduct of science.
ChetzemokaThe Harvard scholar is being accused of deliberately fabricating study results by changing data in a spreadsheet on at least one of the studies.
I think the other commenter mentioned lack of replicability because that's often one of the first indications that the original research results were fraudulent. Inability to reproduce will cause people to go digging through the original data, which is how this stuff gets found in many cases.
The blog posts mentioned in the NYT article [1, 2, 3] are also worth a read, if you want to understand the evidence for tampering.
[109] Data Falsificada (Part 1): "Clusterfake" - Data Colada
This is the introduction to a four-part series of posts detailing evidence of fraud in four academic papers co-authored by Harvard Business School Professor Francesca Gino. In 2021, we and a team of anonymous researchers examined a number of studies co-authored by Gino, because we had concerns that they contained fraudulent data. We discovered evidence...