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When you're wrong, you're wrong. But when you're right, you're extra-wrong. And if you're in between, it's still your fault. You just can't win. Suppose you're right on the facts in a content dispute, or right about Wikipedia policies and guidelines if it's a procedural issue or another editor is misbehaving. If you're so right, it's extra ...
For example, for certain types of questions, answers that people rate as "99% certain" turn out to be wrong 40% of the time. [5] [44] [45] [46] Planning fallacy, the tendency for people to underestimate the time it will take them to complete a given task. [47]
Mea culpa / ˌ m eɪ. ə ˈ k ʊ l. p ə / is a phrase originating from Latin that means my fault or my mistake and is an acknowledgment of having done wrong. [1] The expression is used also as an admission of having made a mistake that should have been avoided and, in a religious context, may be accompanied by symbolically beating the breast when uttering the words.
"I admit I was wrong. I called a Harris win and she didn't win. But I was far from the only forecaster that was wrong. Most other models were wrong." They got the election right: ...
In every fight, one person is right and one person is wrong. Julie : That's the way people sabotage connection during a fight—by fighting to win, as opposed to fighting to understand.
Rationalization can be used to avoid admitting disappointment: "I didn't get the job that I applied for, but I really didn't want it in the first place." Egregious rationalizations intended to deflect blame can also take the form of ad hominem attacks or DARVO. Some rationalizations take the form of a comparison.
I'm Not Wrong. If your boss refuses to admit he or she is wrong after a mistake, they're not only lying but bringing the morale of their entire workplace down with them. ... you're sapping ...
Studies have stated that myside bias is an absence of "active open-mindedness", meaning the active search for why an initial idea may be wrong. [42] Typically, myside bias is operationalized in empirical studies as the quantity of evidence used in support of their side in comparison to the opposite side.