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I ask students and new authors of #ICLR2020 to not take reviews to heart. If you believe in your work, you have to keep fighting for it. Try to read objectively and decide which comments are constructive. Don't let reviewers determine your self worth. You deserve to be here!
In current #PeerReview system #ICLR2020 negative reviewers write long statements making every attempt to destroy it. Often wrong and claiming to be experts. Positive reviewers write a few sentences like "good contribution, relevant.." Often they don't claim to be experts
Self-evaluation of expertise in #PeerReview #ICLR2020 is bizarre. Clueless people claim to be experts (often of privileged class). Humble people don't want to do that. I have seen as AC, professors who rank themselves in the middle and undergrads rank themselves as experts.
Even most non-controversial tweet brings out #Trolls Goes with being a #woman with opinions on #twitter This dude blocked me from replying because I wrote that traditionally men have been told they are fragile if they express their emotions. Toxic masculinity is linked to this.pic.twitter.com/CiSlP30gDL
There is lack of civility in #AI communities. Prominent "leaders" behave terribly. (I had someone call current times as "revenge of #neuralnets and destroy all other researchers). I have made enemies when I have called out their racist and sexist posts.
One more #troll with no logical abilities attacking me personally for talking about #PeerReview Wasn't just one review: thanks to collaborators, I am on several papers. Saw a general trend. What does this have to do with my number of followers? Thanks @sdathath for your response.pic.twitter.com/CjWM5ONPag
Sounds like an example of the Dunning-Kruger effect https://en.wikipedia.org/wiki/Dunning–Kruger_effect …
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