GAW was forced to ban several of long-time contributors over the past few days after some extremely unacceptable behaviour both on the site and in modmail. What happened? These users were warned, asking them to tone it down, get re-focused a bit (maybe go camping?), etc., but instead the behaviour only got worse, and, finally, becoming very concerning. Rather than sit out their vacations and re-focus, the users decided opted for the nuclear option.
We HATE banning good users! Especially permanently! Everyone should be having fun here. But.
We will ban insane behaviour like this, all day, every day, equally, any user, it doesn't matter. This kind of crazy, insane behaviour (doxing, threats, posts on other WINs, etc.) towards GAW's mods, our users, posts, comments, or abuse in modmail, will not be tolerated.
These users are now PM'ing various users here, and these conversations are now filtering up to the mod team. Feel free to reply if you want, etc., but, if you choose to engage, you'll quickly see this same immature behaviour from them as they will quickly demonstrate why they were banned.
GAW will continue to have one of the best online communities around. The entire mod team remains committed to keeping GAW focused on Q, focused on solid, quality discussion, and keeping us ready for The Storm. Thank you!
EDIT: Here are some answers to some questions we're getting asked.
Why can't the mod team do anything about this contact? Apologies, we aren't able to control how the .WINs work, and we're sorry many of you were forced to deal with this unfortunate situation.
How does GAW run? Other than the 100% volunteer mod team, basically, several years ago, we were lucky enough to get invited to run on the same digital infrastructure that The_Donald.WIN (now Patriots.WIN, of course) ran on. Why? Because Q was part of the movement, but they wanted us annoying (LEL 😎) "Q believers" to have their own space so that regular patriots could have the option to participate or not. The mods have no access to the codebase. We found ways to add our own feel here (pepes, colours, etc.), but we don't have the ability to shadowban, or otherwise hassle anyone, anywhere. We can only control user access, sticky posts, and remove harmful comments.
This graph shows the more complete data for the Dunning-Kruger Effect. This one includes the opposite end where competent people generally underestimate their abilities.
Basically "The more you know, the more you realize you dont know". Or as Bertrand Russell put it:
Youre right, this could absolutely be used to describe the mental process happening during a normies awakening process.
And your comment just made me realize that the opposite end of the D-K Effect graph can also describe people who started the awakening process long ago. We're the ones who sometimes second guess (and even doubt) our own knowledge.
I don't understand where the first graph graph came from. The peak of mount stupid doesn't come from Dunning-Kruger at all (the first peak is not in their data set), and your graph is one of four they included in their paper (self-assessment of grammar). While it's true that at the very upper end there's between 10% and 25% underestimation of skill, it's interesting there's almost no underestimation in logic and reasoning:
https://graphpaperdiaries.files.wordpress.com/2017/08/logicgraph.png
But there's a significant overestimation at the low end.
Edit: By first graph, I'm referring to the one in the post you responded to.
Did a quick search... half the graphs and explanations online have been very simplified.
For some reason they only include the ignorant side that overestimate, and completely ignore the other end of the scale.
Yeah. That's definitely true. My guess is that it's because Dunning and Kruger didn't highlight that as a conclusion. There was definitely less evidence for it, since the margin of error at the upper end may have been small enough to be statistically insignificant, given the sample size. Not sure.
Some people argue that this phenomenon is actually just a result of regression towards the mean (tenuous argument imo, since estimates aren't random samples).