Episode 151: Witold Więcek discusses statistics and academic research
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Why do media headlines often overstate scientific findings?
Yeah.
Hello and welcome to Elucidations, an unexpected philosophy podcast. I'm Matt Tykeman. And with me today is Vitold Vienzek, Consulting Director for Development Innovation Lab at the University of Chicago. And he's here to discuss statistics and academic research. Vitold Vienchek? Welcome. Hi,
thanks for coming.
So this is a topic that's near and dear to my heart, I have to say. Um one thing that's been kind of bothering me for I wanna say like the last twenty, twenty five years in our popular media is that there seems to be sort of an arms raise in overconfident language. People will say something like, this study shows X, Y, Z, and it'll be like one experiment. And be like, you can't conclude that the thing is the case after one experiment. And like, you know, this shows word typically is reserved for cases where like the thing you're saying is showed is actually true. It kind of has this pre- uh uh what philosophers would call a factive presupposition. Um and I feel like we see this all over the place. Instead of saying something like, Oh, there was a study and uh the results are suggestive of XYZ.
People will be like, Well we now know XYZ. We're like, I don't know, are we really in a position to like conclude that with like really strong certainty yet? So anyway, I wonder if is this something that you've also noticed uh in our media culture that like there is a hesitancy to say that there's anything we don't know and uh uh pressure to act omniscient?
So I think there is a few layers to this question. First one being that generic point going beyond any media depiction of scientific facts is that the language interacts with statistical knowledge, which I guess we'll be talking about here mostly, in a quite imperfect way. The obverse of what you describe is is which is my particular pet peeve is headlines where uh no evidence makes an appearance. So and also in colloquial language where we'll say, but currently there is no evidence for X, which Typically people will uh take to mean that there is actually negative evidence. And uh the the way we discuss science is so good at conflating all kinds of uh conflicting uh claims and then What you describe is the degree of certainty, which is also very hard to express in just regular conversation.
But I I think apart from everyday language it's interesting to think about this from the perspective of practice of science and uh scientists. Or since we will be touching on uh economics in this conversation a lot, do a supply side analysis. Because if I'm thinking about demand side for those media headlines, you would a priori think, well, to say study shows or study suggests is the same number of bits of information. So why would we have a preference for one or the other, right? So if we start from the supply side of scientific facts, i it seems like there is obviously a very competitive market out there to break through the noise. And It probably highlights the general trend in academia of there being more scientific facts and also more scientists competing against more noise.
Um
like if If there was a case where we could be really confident in the result, that would get more clicks. Um and so there's pressure to act like we actually have gotten a result that that's robust.
Yeah, there is more value nowadays to creating an atomized scientific fact. because there are outlets out there that are specializing in in uh creating that product, right? But it doesn't To say that doesn't really answer why why culturally we do have media outlets that specialize in packaging atomized scientific facts into things that people will click on. And I don't have a great take on this, but it's It's interesting that you could make almost conservative or reactionary critique of this entire process where as science is becoming something commodified and popular Because of the assumption that a regular person is meant to be interested in science. So it's maybe a bit of a chicken and egg problem, but as w we assume that people care about scientific facts.
Maybe or maybe we
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Chapters
8 chapters
1
Why do media headlines often overstate scientific findings?
0:15–6:53
2
How does p‑hacking undermine the reliability of statistical significance?
6:53–12:20
3
What role should external statistical consultants play in research projects?
12:20–18:11
4
Why is the “garden of forking paths” a problem for hypothesis testing?
18:11–24:44
5
How can pre‑registration reduce researcher degrees of freedom?
24:44–30:20
6
What are the ethical implications of data fabrication and cherry‑picking?
30:20–35:10
7
How can forensic statistical tools like Benford’s Law detect fraud?
35:10–40:14
8
What institutional changes can improve statistical integrity in academia?
40:14–45:56
Speakers
1 identifiedMore from Elucidations
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