Breakdown of Diverse Content & Own Voices works within Butler’s 2018 Collection

Introduction:
Inspired by We Need Diverse Books and the University of Wisconsin-Madison info-graphic breaking down the percentage of books depicting diverse characters (specifically race and ethnicity) we here at Butler decided to evaluate our 2018 collection to determine whether or not we had a similar breakdown. Questions that we hope to answer by looking back at our 2018 titles included: Does our collection accurately represent what’s being published? Do we need to do some active curation to give our users a better picture of current publishing trends? Although we realize that we receive much fewer books in one year than either of this two institutions do, we felt that is our responsibility to ensure that our collection was an accurate reflection of what is published in a given year. 

WNDB 2018 Graphic

We Need Diverse Books & CCBC Diversity info-graphic

Method & Results:
1. Gather all 2018 titles Butler received and put it into an excel doc. Delete any and all duplicate titles within the excel doc. This was done by putting the doc in alphabetical order by author to make it easier to spot any duplicates.
2. We then looked up each book on Kirkus and Amazon to determine the race/ethnicity of the protagonists of each book. Once this was determined, this would be indicated on the excel doc with the following acronyms:

  • African/African American (A/AA)
  • American Indian/First Nations (AI/FN)
  • Asian Pacific Islander/Asian Pacific American (API/APA)
  • Latinx
  • White

In the case that it was none of the above, we left it blank to represent animals/other.
3. After determining the contents diversity, we then went on to look up the author and illustrator of the title to determine whether or not the title was own voices. If it was own voices, an ‘x’ was put in the excel doc. If the title was not own voices, this would be indicated in the excel doc by writing the race/ethnicity of the author and illustrator next to one of the above acronyms.
4. After all this was done, we found that we had a few anthology titles that included both diverse characters and none diverse characters. Since we could not determine how much of these titles were dedicated to either non diverse or diverse characters we decided to delete these titles from the doc so as not to misrepresent them in our graphic.
5. We then organized the doc in alphabetical order based off our acronyms. From there we counted how many books we had in all of our categories—including those we had left blank that represented books about animals or other inanimate objects. For each category we had the following amount of books:

BCLC 2018 All Books graph6. With these numbers in mind, we decided to focus on the 240 books that had diverse content to see how many were own voices.
7. We counted how many ‘x’ indicators we had in our A/AA, AI/FN, API/APA, and Latinx categories to see how many titles we had that were actually own voices.
We found that altogether there were only 119 titles that were on voices.
Once all the data had been gathered we made a graph breaking down all the books by      content and a graph that broke down the number of own voices titles by race/ethnicity.BCLC 2018 Only Diverse Content.png

  • Notably, we found that although the graph based off content indicated that of the 1420 we had only 0.42% was AI/FN content. The own voices graph, on the other-hand, indicated that of the 240 books we had with diverse characters 2% of own voices content was AI/FN.
  • In fact, the percentages for each category doubled between graphs. However, the overall percentage of non-own voices content made up 50% of the second graph while no individual category went above 19%.
  • Overall, own voices content only made up 8% of the total number of books that we received in 2018.BCLC 2018 Own Voices Overall

Breaking this down further, looking at each A/AA, AI/FN, API/APA, and Latinx individually to see what percentage of the content about them was own voices, we found that although A/AA had the most content its overall percentage of own voices titles was the lowest of all the other categories at 41%. Meanwhile Latinx, which had the second lowest amount of content had the highest percentage of own voice titles at 68%.  BCLC 2018 Own Voices within each race ethnicity

Conclusions:
The percentages of our content graph are overall lower than those found by We Need Diverse Books (WNDB) and the University of Wisconsin-Madison. However, the one area where we had a higher percentage than WNDB and University of Wisconsin-Madison was in our other/animal category. This may in part be due to the fact that we included self-help and how-to books within this category. Without knowing exactly how WNDB and University Wisconsin-Madison determined what went into this category it is hard to say why this discrepancy exists.
On the whole, our results seemed to match the same pattern as WNDB and the University of Wisconsin with White making up the majority of content, followed by Animal/Other, A/AA, API/APA, Latinx, and AI/FN at the bottom. While the gap between diverse and not diverse content is great, the gap between own voices content and non-own voices content is even greater still.

Nature Children Atlantic

The Atlantic, Ashley Fetters

Final Thoughts:
As more diverse titles are published, it is important that they are predominantly written by people from the community they are writing about. It is not enough to have a diverse cast of characters if they do not act or accurately reflect the community they are meant to represent. At the very least, writers and illustrators should make sure that whatever they are producing does not further advance negative stereotypes of their subjects. People are not always aware of the biases they may hold; it is always a good idea to have a sensitivity reader look over and reevaluate your work so as not to further any biases that may be present.
These findings, as well as the findings by WNDB and the University of Wisconsin-Madison, may be helpful to librarians, educators, and parents when curating their own collections. Knowing that publishers mostly publish content depicting white children or animals, librarians, educators, and parents can take the appropriate steps to ensure that their collections are representative of the diverse communities of people which they serve. It is important that everyone feels heard and represented, and making sure that the books we select accurately reflect these voices is critical to expanding children’s world views and validating their self-worth.

 

 

 

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s