Carol Harris

In the article “Against Cleaning” Katie Rawson and Trevor Munoz makes that point that what is seen as a substantial part of the process of acquiring knowledge through data i.e. the “cleaning” of the data has implications for how we present the data and what we are able to ascertain from it. This is particularly important when it comes to sensitive data that gives us insight into the psychological and mental states of individuals particularly individuals who are struggling with affirming their identity in a society that is often hostile at times. It is with from this backdrop that I decide to look into the mental health experiences and struggles for Transgender individuals. The data used in this analysis came from the Household Pulse Survey which was conducted by the Census Bureau during COVID. The survey is conducted online from a random sample of households and measures of anxiety, depression and a combination of both are tabulated for the individuals completing the survey. The results are weighted in accordance with the demographic breakdown of the US population. For my analysis I focus on depressive symptoms and I looked at three groups. Individuals who were identified as male or female at birth and transgender. The first graph is the overall with all three groups shown in accordance with the percent of depressive symptoms they experienced during the time period. Males and females have similar rates of depressive symptoms with females being slightly higher than males. The transgender group showed the highest depressive symptoms for the the ten month period in 2023. It is important to point out that the data was collected in one week waves and then the average was tabulated for the month. While the line graph looked identical for the male and female the transgender graph had more peaks and troughs. In other words it is less stable and more erratic during this period. It is also important to point out that when it comes to identity people sometimes occupy several different identities. So while this is a snapshot of sexual identity, other identities such as race and ethnicity may also be a contributing factor. This gets to why this type of data is so hard to separate and pull apart. The way the data is collected I had to basically strip away other identities and focus on a single identity which is not a realistic reflection on how people interact in their daily lives.