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Posted by timr 1/25/2026

A flawed paper in management science has been cited more than 6k times(statmodeling.stat.columbia.edu)
715 points | 373 commentspage 3
psychoslave 1/25/2026|
Social fame is fundamentally unscalable, as it operates in limited room on the scene and even less in the few spot lights.

Benefits we can get from collective works, including scientific endeavors, are indefinitely large, as in far more important than what can be held in the head of any individual.

Incitives are just irrelevant as far as global social good is concerned.

glitchc 1/25/2026||
This is simply a case of appeal to authority. No reviewer or editor would reject a paper from either HBS or LBS, let alone a joint paper between the two. Doing so would be akin to career suicide.

And therein lies the uncomfortable truth: Collaborative opportunities take priority over veracity in publications every time.

cloud-oak 1/25/2026|
That's why double-blind review shohld be the norm. It's wild to me that single-blind is still the norm in kost disciplines.
recursivecaveat 1/25/2026||
I don't understand why it has been acceptable to not upload a tarball of your data with the paper in the internet age. Maybe the Asset4 database is only available with license and they can't publish too much. However, the key concern with the method is a pairwise matching of companies which is an invention of the paper authors and should be totally clear to publish. The number of stories I've heard from people forensically investigating PDF plots to uncover key data from a paper is absurd.

Of course doing so is not free and it takes time. A paper represents at least months of work in data collection, analysis, writing, and editing though. A tarball seems like a relatively small amount of effort to provide an huge increase in confidence for the result.

bradley13 1/25/2026|
This. I did my dissertation in the early '90s, so very early days of the internet. All of my data and code was online.

IMHO this should be expected for any, literally any publication. If you have secrets, or proprietary information, fine - but then, you don't get to publish.

dgxyz 1/25/2026||
Not even surprised. My daughter tried to reproduce a well-cited paper a couple of years back as part of her research project. It was not possible. They pushed for a retraction but university don't want to do it because it would cause political issues as one of the peer-reviewers is tenured at another closely associated university. She almost immediately fucked off and went to work in the private sector.
jruohonen 1/25/2026||
> They pushed for a retraction ...

That's not right; retractions should only be for research misconduct cases. It is a problem with the article's recommendations too. Even if a correction is published that the results may not hold, the article should stay where it is.

But I agree with the point about replications, which are much needed. That was also the best part in the article, i.e. "stop citing single studies as definitive".

dgxyz 1/25/2026||
I will add it's a little more complicated than I wanted to let on here as I don't identify it in the process. But it definitely was misconduct on this one.

I read the paper as well. My background is mathematics and statistics and the data was quite frankly synthesised.

jruohonen 1/25/2026||
Okay, but to return to replications, publishers could incentivize replications by linking replication studies directly on a paper's website location. In fact, you could even have a collection of DOIs for these purposes, including for datasets. With this point in mind, what I find depressing is that the journal declined a follow-up comment.

But the article is generally weird or even harmful too. Going to social media with these things and all; we have enough of that "pretty" stuff already.

dgxyz 1/25/2026||
Agree completely on all points.

However there are two problems with it. Firstly it's a step towards gamification and having tried that model in a fintech on reputation scoring, it was a bit of a disaster. Secondarily, very few studies are replicated in the first place unless there is a demand for linked research to replicate it before building on it.

There are also entire fields which are mostly populated by bullshit generators. And they actively avoid replication studies. Certain branches of psychology are rather interesting in that space.

jruohonen 1/25/2026||
> Certain branches of psychology are rather interesting in that space.

Maybe, I cannot say, but what I can say is that CS is in the midst of a huge replication crisis because LLM research cannot be replicated by definition. So I'd perhaps tone down the claims about other fields.

dgxyz 1/25/2026||
Another good example that for sure. You won't find me having any positive comments about LLMs.
dekhn 1/25/2026|||
A single failure to reproduce a well-cited paper does not constitute grounds for a retraction unless the failure somehow demonstrates the paper is provably incorrect.
kelipso 1/25/2026||
It’s much much more likely that she did something wrong trying to replicate it than the paper was wrong. Did she try to contact the authors, discuss with her advisor?

Pushing for retraction just like that and going off to private sector is…idk it’s a decision.

dgxyz 1/25/2026||
It went on for a few months. The source data for the paper was synthesised and it was like trying to get blood out of a stone trying to get hold of it, clearly because they knew they were in trouble. Lots of research money was wasted trying to reproduce it.

She was just done with it then and a pharma company said "hey you fed up with this shit and like money?" and she was and does.

edit: as per the other comment, my background is mathematics and statistics after engineering. I went into software but still have connections back to academia which I left many years ago because it was a political mess more than anything. Oh and I also like money.

tokai 1/25/2026||
Google Scholar citation numbers are unreliable and and cannot be used in bibliometric evaluation. They are auto generated and are not limited to the journal literature. This critique is completely unserious. At the same time bad papers also tend to get more citations on average than middling papers, because they are cited in critiques. This effect should be even larger in a dataset that includes more than the citations from journal papers. This blog post will in time also add to the Google Scholar citation count.

Citation studies are problematic and can and their use should be criticized. But this here is just warm air build on a fundamental misunderstanding of how to measure and interpret citation data.

cloche 1/25/2026||
> Because published articles frequently omit key details

This is a frustrating aspect of studies. You have to contact the authors for full datasets. I can see why it would not be possible to publish them in the past due to limited space in printed publications. In today's world though every paper should be required to have their full datasets published to a website for others to have access to in order to verify and replicate.

nickpsecurity 1/25/2026||
I think what these papers prove is my newer theory that organized science isn't scientific at all. It's mostly unverified claims by people rewarded for throwing papers out that look scientific, have novelty, and achieve policy goals of specific groups. There's also little review with dissent banned in many places. We've been calling it scientism since it's like a self-reinforcing religion.

We need to throw all of this out by default. From public policy to courtrooms, we need to treat it like any other eyewitness claim. We shouldn't beleive anything unless it has strong arguments or data backing it. For science, we need the scientific method applied with skeptical review and/or replication. Our tools, like statistical methods and programs, must be vetted.

Like with logic, we shouldn't allow them to go beyond what's proven in this way. So, only the vetted claims are allowed as building blocks (premises) in newly-vetted work. The premises must be used how they were used before. If not, they are re-checked for the new circumstances. Then, the conclusions are stated with their preconditions and limitations to only he applied that way.

I imagine many non-scientists and taxpayers assumed what I described is how all these "scientific facts" and "consensus" vlaims were done. The opposite was true in most cases. So, we need to not onoy redo it but apply scientific method to the institutions themselves assessing their reliability. If they don't get reliable, they loose their funding and quickly.

(Note: There are groups in many fields doing real research and experimental science. We should highlight them as exemplars. Maybe let them take the lead in consulting for how to fix these problems.)

esseph 1/25/2026|
I have a Growing Concern with our legal systems.

> We need to throw all of this out by default. From public policy to courtrooms, we need to treat it like any other eyewitness claim.

If you can't trust eyewitness claims, if you can't trust video or photographic or audio evidence, then how does one Find Truth? Nobody really seems to have a solid answer to this.

nickpsecurity 1/25/2026||
It's specific segments of people saying we can't trust eyewitness claims. They actually work well enough that we run on them from childhood to adulthood. Accepting that truth is the first step.

Next, we need to understand why that is, which should be trusted, and which can't be. Also, what methods to use in what contexts. We need to develop education for people about how humanity actually works. We can improve steadily over time.

On my end, I've been collecting resources that might be helpful. That includes Christ-centered theology with real-world application, philosophies of knowledge with guides on each one, differences between real vs organized science, biological impact on these, dealing with media bias (eg AllSides), worldview analyses, critical thinking (logic), statistical analyses (esp error spotting), writing correct code, and so on.

One day, I might try to put it together into a series that equips people to navigate all of this stuff. For right now, I'm using it as a refresher to improve my own abilities ahead of entering the Data Science field.

esseph 1/25/2026||
> It's specific segments of people saying we can't trust eyewitness claims.

Scientists that have studied this over long periods of times and diverse population groups?

I've done this firsthand - remembered an event a particular way only to see video (in the old days, before easy video editing) and find out it... didn't quite happen as I remembered.

That's because human beings aren't video recorders. We're encoding emotions into sensor data, and get blinded by things like Weapon Focus and Selective Attention.

nickpsecurity 1/26/2026||
Ok, let me give you examples.

Much of what many learned about life came from their parents. That included lots of foundational knowledge that was either true or worked well enough.

You learned a ton in school from textbooks that you didn't personally verify.

You learned lots from media, online experts, etc. Much of which you couldn't verify.

In each case, they are making eyewitness claims that are a mix of first-hand and hearsay. Many books or journals report others' claims. So, even most education involves tons of hearsay claims.

So, how do scientists raised, educated, and informed by eyewitness claims write reports saying eyewitness testimony isn't reliable? How do scientists educated by tons of hearsay not believe eyewitness testimony is trustworthy?

Or did they personally do the scientific method on every claim, technique, machine, circuit, etc they ever considered using? And make all of it from first principles and raw materials? Did they never believe another person's claims?

Also, "scientists that have studied this over long periods of times and diverse population groups" is itself an eyewitness claim and hearsay if you want us to take your word for it. If we look up the studies, we're believing their eyewitness claims on faith while we've validated your claim that theirs exist.

It's clear most people have no idea how much they act on faith in others' word, even those scientists who claim to refute the value of it.

poemxo 1/25/2026||
> They intended to type “not significant” but omitted the word “not.”

This one is pretty egregious.

B1FIDO 1/25/2026|
Once, back around 2011 or 2012, I was using Google Translate for a speech I was to deliver in church. It was shorter than one page printed out.

I only needed the Spanish translation. Now I am proficient in spoken and written Spanish, and I can perfectly understand what is said, and yet I still ran the English through Google Translate and printed it out without really checking through it.

I got to the podium and there was a line where I said "electricity is in the air" (a metaphor, obviously) and the Spanish translation said "electricidad no está en el aire" and I was able to correct that on-the-fly, but I was pissed at Translate, and I badmouthed it for months. And sure, it was my fault for not proofing and vetting the entire output, but come on!

aidenn0 1/27/2026||
Similar timeframe, I used it for translating some German into English. I'm a native English speaker who has spent some time in Germany (but had not spoken any German in over a decade at this point) and quickly noticed some things were off. After reviewing the original text I realized that every single separable verb[1] that was not in infinitive form was mistranslated. This is an astoundingly bad systematic error for a machine translation program to have.

1: https://en.wikipedia.org/wiki/Separable_verb

lbcadden3 1/25/2026||
>There’s a horrible sort of comfort in thinking that whatever you’ve published is already written and can’t be changed. Sometimes this is viewed as a forward-looking stance, but science that can’t be fixed isn’t past science; it’s dead science.

Actually it’s not science at all.

bronlund 1/25/2026|
This likely represents only a fragment of a larger pattern. Research contradicting prevailing political narratives faces significant professional obstacles, and as this article shows, so does critiques of research that don't.
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