Category Archives: Academic Blog

A Note on Categories, Census and Otherwise

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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? 

Our Data: In and Beyond the Gender Binary

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A particularly challenging part of our project has been dealing with gender identity within our data. We have a limited amount of information about authors and protagonists, especially since our research has been affected by the spread of COVID-19, and have relied on the pronouns used in primary and secondary materials to assign gender to protagonists and authors. This has lead to issues with the labels we choose to describe our findings.

For example, our data does not show any trans or non-binary authors. This does not mean that our data does not include trans and/or non-binary authors because (1) an author’s gender identity might not be known to the public (2) an author might be misgendered by the media (3) some trans people use binary pronouns, even if they do not entirely identify with a binary gender (4) some people, gender fluid or otherwise, might use different pronouns at different times or in different situations. It’s hard to even list all the possibilities of the way this data might mislabel reality, but that is one of the realities of doing this type of work.

Gender identity has only recently become a part of public dialogue. The lack of non-binary gender identities among the authors of the older works is not surprising; however, this is not to say that no winner or honoree has had a non-binary and/or trans identity. In fact, we doubt this is the case. Further, some trans identities could be invisible in our data as a result of how we report it. If a trans woman won the Newbery next year, would labeling her as a trans woman be preferable to labeling her “just” a woman?

In more recent years, the lack of gender diversity is more worrying. When it comes to protagonists, whose genders are assigned by the author, we can more securely point to a lack of non-binary and/or trans representation rather than a lack of accurate gender information in the data itself. Although gender is not the main subject of our inquiry, we hope our exploration of this subject matter might influence others who can further examine our data for their own purposes. 

These uncertainties lead us to another important decision: what do we choose to report about an author or protagonists’ gender identity, and how do we choose to report this? Right now, we have protagonists and authors listed as either male or female. We have assigned these genders using the pronouns in the books or author biographies we have looked at.

We have struggled with how to use this label… the terms male/female are pretty explicitly connected to biological sex, but they present a much more elegant way to describe gender identity because they can function as adjectives as well as nouns. Outside of academia, these terms are probably more easily digestible and require less explanation. But the issue is… when it comes to authors, we are assigning genders based on incomplete data then using labels which don’t actually describe gender but biological sex.

I have suggested that we simply report which pronouns we have found in primary and secondary materials for both authors and protagonists, as this approach does not require us to make an assumption about gender. It remains to be seen what decision we make as a group, but we will definitely comment on it during our blogs so stay tuned!