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Update on Overleaf.

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Nathan TeBlunthuis
2023-03-06 23:44:17 +00:00
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@@ -704,7 +704,7 @@ Our example relies on the publicly available Civil Comments dataset \citep{cjada
Each comment was labeled by up to ten manual annotators (although selected comments were labeled by even more annotators). Originally, the dataset represents \emph{toxicity} and \emph{disclosure} as proportions of annotators who labeled a comment as toxic or as disclosing aspects of personal identity including race and ethnicity. Each comment was labeled by up to ten manual annotators (although selected comments were labeled by even more annotators). Originally, the dataset represents \emph{toxicity} and \emph{disclosure} as proportions of annotators who labeled a comment as toxic or as disclosing aspects of personal identity including race and ethnicity.
For our analysis, we converted these proportions into indicators of the majority view to transform both variables to a binary scale. For our analysis, we converted these proportions into indicators of the majority view to transform both variables to a binary scale.
Our MLA method works in this scenario, as shown in \ref{fig:real.data.example.app} Our MLA method works in this scenario, as shown in \ref{fig:real.data.example.app} below.
\begin{figure}[htbp!] \begin{figure}[htbp!]
\centering \centering