Added the figure.

paper/sl.tex

 \documentclass[sigconf,anonymous]{acmart}
 % \documentclass[sigconf]{acmart}
 
+
+\usepackage{tikz}
+\usepackage{tikz-cd}
+\usetikzlibrary{arrows,automata, positioning}
+
 % Packages
 \usepackage{type1cm}     % type1 computer modern font
 \usepackage{graphicx}     % advanced figures
@@ -118,6 +123,30 @@ deciding whether of defendant should be given bail or kept in jail, we are not a
 
 \section{Framework}
 
+
+\begin{figure}
+    \begin{tikzpicture}[->,>=stealth',node distance=1.5cm, semithick]
+
+  \tikzstyle{every state}=[fill=none,draw=black,text=black]
+
+  \node[state] (R)                    {$R$};
+  \node[state] (X) [right of=R] {$X$};
+  \node[state] (T) [below of=X] {$T$};
+  \node[state] (Z) [rectangle, right of=X] {$Z$};
+  \node[state] (Y) [below of=Z] {$Y$};
+
+  \path (R) edge (T)
+        (X) edge (T)
+	     edge (Y)
+        (Z) edge (T)
+	     edge (Y)
+        (T) edge (Y);
+\end{tikzpicture}
+\caption{ $R$ leniency of the decision maker, $T$ is a binary decision,  $Y$ is the outcome only observed for some decisions. Background features  $X$ for a subject affect the decision and the outcome. Additional background features  $Z$ are visible only to the decision maker in use. }
+\end{figure}
+
+
+
 In this section, we define the key terms used in this paper, present the modular framework for selective labels problems and state our problem.
 
 \begin{itemize}