11 hours ago
Dogs can distinguish between human fear and sadness?
https://www.scivillage.com/thread-21062.html
SABINE HOSSENFELDER
https://youtu.be/0XcEsuFs5Y8
VIDEO INTRO: The dumber you are, the more certain you are that you aren't. That's the Dunning-Kruger effect, and it's been used to explain everything from bad politicians to the state of social media. Now psychologists have gone back to the biggest dataset we have and come out with the opposite conclusion. But there's a reason both sides can look at the same dots and see the opposite thing. Let's take a look.
VIDEO EXCERPT: But wait, how can it be that there are two different best fits to the same data cloud? It's because each of these curves is best in a different way. Loosely speaking, for the standard Dunning-Kruger, you minimize the deviation in the horizontal direction. For the new paper. in the vertical direction. You could instead take the mean of both, which would give you this line. And that tells you that the people who score least underrated themselves, whereas the people who score highest overrated themselves.
Still, how can it be that there are so many different ways to look at this data? Well, as a physicist, I'd say just look at the data. It basically doesn't have any correlation whatsoever. Why the hell are you fitting any straight line to this? This is why I give this paper as well as all previous papers on the topic a 10 out of 10 on the bullshit meter. These are all crappy data analyses. If you draw enough lines through the data, one will eventually confirm that everybody else is an idiot.
PAPER: https://psycnet.apa.org/fulltext/2028-00629-001.html
https://youtu.be/0XcEsuFs5Y8
https://www.scivillage.com/thread-21062.html
SABINE HOSSENFELDER
https://youtu.be/0XcEsuFs5Y8
VIDEO INTRO: The dumber you are, the more certain you are that you aren't. That's the Dunning-Kruger effect, and it's been used to explain everything from bad politicians to the state of social media. Now psychologists have gone back to the biggest dataset we have and come out with the opposite conclusion. But there's a reason both sides can look at the same dots and see the opposite thing. Let's take a look.
VIDEO EXCERPT: But wait, how can it be that there are two different best fits to the same data cloud? It's because each of these curves is best in a different way. Loosely speaking, for the standard Dunning-Kruger, you minimize the deviation in the horizontal direction. For the new paper. in the vertical direction. You could instead take the mean of both, which would give you this line. And that tells you that the people who score least underrated themselves, whereas the people who score highest overrated themselves.
Still, how can it be that there are so many different ways to look at this data? Well, as a physicist, I'd say just look at the data. It basically doesn't have any correlation whatsoever. Why the hell are you fitting any straight line to this? This is why I give this paper as well as all previous papers on the topic a 10 out of 10 on the bullshit meter. These are all crappy data analyses. If you draw enough lines through the data, one will eventually confirm that everybody else is an idiot.
PAPER: https://psycnet.apa.org/fulltext/2028-00629-001.html
https://youtu.be/0XcEsuFs5Y8