One of the things that was attractive about studying the Newbery Awards was the fact that these awards have been given for almost 100 years. This gives us a grand view of changes over time. However, when studying trends, changes in categories affect results.
For example, an early question became, how do we label people from groups which have been assimilated into whiteness over the past 100 years? This was of particular concern when it came to groups such as Jews and Italians who faced discrimination for much of the 20th century. For this, we decided that we would eventually label these groups as white but give them a signifier beyond that in our data. That way, we could reflect the current ideas on these groups and represent the differences between them and a white, Anglo-Saxon protestant. These labels will likely appear in a future iteration of the project.
But when it came to broad categories, we wanted a system that would allow us to compare our results to the larger demographics of a given time period. For this we based categories on US Census categories. But to pretend that this created a “neutral” way of viewing results is extremely flawed, as we had simply adopted the same prejudices which formed the categories for the US Census. Not to mention the bias in the way the census is/was collected. Census takers could not even choose their own race until the 1960 census. Before that, census workers chose for participants.
These categories have changed over time but have been relatively stable since the 1970s. We are in a census recording period right now, and many people do not feel that the census can accurately record their identity. Government agencies have always been slow to reflect social change, and this causes issues trying to get people to participate in public initiatives. Other community members, especially those who are undocumented, are skeptical of the project of the census in general because of privacy concerns.
In a further iteration of this project, we hope to add different ways of sorting the data to move away from these Census categories. We would keep the Census categories on Tableau public to show how the data changes when more adaptive, community-centered categories affect the way the data is displayed.
The main thing we found was not a surprise—that is the overwhelming whiteness of these honorees and book award winners. It has been challenging to display this overwhelming trend in a way that does not erase smaller trends or issues that are not whiteness centered. This will be an ongoing process, and we hope for feedback from the communities affected by what we describe in our project. Improving and changing categories should be an iterative process rather than a static one, and we are here to learn the possibilities that are available to us.
In the meantime, we hope this discussion of the issues with the census categories sparks interest in what’s going on with the census in a general way. It’s a very important way that the federal government allocates funds so it’s important people participate, but when they aren’t accurately represented by the categories, how can they have faith in the process?
