[Aurornis]

> you need to think critically (and skeptically) to avoid assigning value to things that don't have it, but you must find value.

This isn’t critical thinking.

This is toxic positivity.

It’s okay to admit that some studies don’t have value to add. If you don’t accept this, you’re going to be tricked by a lot of people trying to get your attention with bad data.

Being able (and willing!) to filter out bad sources, even when they say something you want to hear, is a critically important skill. If you force yourself and others to find something positive about everything then you’re a dream come true to purveyors of low quality or even deliberate misinfo.

[mmooss]

lol

> some studies

It's almost every study on HN, not some studies, which you'd understand if you read my comment.

[jval43]

Yes because most studies that end on up HN are there because they were reported on somewhere as news.

This usually happens in usually these cases:

1. when a paper is extremely good and it's results are groundbreaking, or

2. when a study itself claims it has groundbreaking results, or

3. when it's a regular study that's gotten some great marketing/promotion e.g. by their university.

The case of 1. is extremely rare, and even when everyone believed the results and they were peer reviewed by a reputable paper like Science, some of them turned out to be academic fraud that was later retracted.

Most studies that pop up on HN are of types 2. and 3. That's just because otherwise they would not get news attention.

But most studies in general are in category 4: the ones an academic or professional would read going about their daily business / research. These range from terrible, to OK, to really great, but 99% never make the news.

As a (former) academic, I've read lots of papers and like in real life it's usually the people (papers) that get attention who scream the loudest. There are some gems too of course, and it's right to not ignore anything.

But in my personal experience and over time, I've been very right to be very sceptical once a result turns up in the news because of the 3 ways it can get there.

This is amplified even more so with papers that base their results / outcome purely on statistics, such as most experimental studies done. These derive their results from the statistics (sample size, experiment design, etc) so their power and the probability of their result being correct (what the authors say) it directly coupled.