> is a great example of why people don't or shouldn't take the social sciences seriously.
Oh the irony in your last statement. Somebody who hasn't done social science research professionally (this is an assumption, let me know if I'm wrong), has difficulty judging what social science research can (and can't) do ...
One does not need to have done social science research to be able to recognize obvious general philosophy of science level problems with the methods used in much social science.
I’d we take your claim seriously then we have to disallow all critiques of the replicatability crisis in the social sciences that don’t come from social scientists, but that would present an obvious new problem: conflict of interest. It’s also just an absurd requirement.
You are correct - I should have been more precise: I hypothesis parent has not done science research professionally (again happy to be proven wrong).
Don't get me wrong, I'm not defending social science research per se (yes, there are questionable methods). I'm critiquing parent who has high confidence in pointing out issues with the DK paper, yet misses the real issues. Which, in the context of discussing whether the DK effect is more than just regression to the mean, is quite ironic (which I have worded quite strongly, agreed).
Parent's arguments lead to absurd conclusions like "two Cornell professors not being very logical people" or "a HN poster being better at peer review than experts in the field". If you want to see a state-of-the-art critique of whether the DK effect is explained by metacognition vs. regression to the mean see [1].
Why is this relevant? From the article:
> I have no illusions that everything I read online should be correct, or about people’s susceptibility to a strong rhetoric cleverly bashing conventional science, even in great communities such as HN. But frankly, for the last few years, the world seems to be accelerating the rate at which it’s going crazy, and it feels to me a lot of that is related to people’s distrust in science (and statistics in particular).
I completely agree with the author here. Science is rarely black and white, and, arguably, there are more shades of grey in the social sciences. Just as an example, because you mentioned the replicability crisis. I still see many commenters here on HN believing that from the failure to replicate a result it follows the result is wrong. It doesn't. But that's a whole other discussion.
None of your points actually address the sample size and study design issues that wouldn’t be unacceptable even in social sciences today. Generalizing results from a fistful of privileged undergrads is a well-known issue even in the community.
Oh the irony in your last statement. Somebody who hasn't done social science research professionally (this is an assumption, let me know if I'm wrong), has difficulty judging what social science research can (and can't) do ...