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"I was seeing inmate abuse, but I was labelling it as 'Oh, he's psychologically compromised,' " Mallinckrodt told me.
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prior knowledge on documents: if document i is labeled di then the polarity estimate dest,i should be close to this label; prior knowledge on words: if word i is labeled wi then the polarity estimate ci should be close to this label.
For labeled data, Y ij = 1 if x i is labeled with c j, and Y ij = 0 otherwise.
Instead I was labeled "petite".
I was labeled rude.
"I was labeled a troublemaker".
For this I was labeled "shrill".
During my third I was labeled bipolar.
I was labeled a financial delinquent.
I was labelled as being "unreliable", not "corporate" enough.
"I was labelled an out-of-control, racist white cop with a history," he recalls.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com