Chart Data and Compare
Results of the diversity audit are best shown as percentages as to compare to demographic numbers directly.
The three main categories of race, sexuality and gender were each separated into identifiers and marked for each book on the audit spreadsheets. These three categories, under each collection and key figure, were then converted into pie charts that represent the percentage of items in the collection that reflect that identifier. Converting the data into pie charts is a simple process of counting the number of occurrences and placing it into a program that can make a pie chart out of the data. The initial audit used Canva as their pie chart making tool.
*When counting occurrences of marked identifiers, be sure to mark in some way repeats of key figures. In your collection, you might have books by the same author or a series with the same main character. Recording the same author data for a number of books could inflate data in favor of certain identifiers, and would lead to inaccurate data.
Below is an example of the pie chart signifying the race of main characters for all the adult popular fiction collection.
The pie chart is the main category of "race" and each slice is an identifier that falls under the category. For example, 57.6% of all the adult popular fiction main characters identify as "white" for race. This type of graph is the best method to measure percentages and was used in the initial audit for each main category of each key figure in each collection. This LibGuide has a tab titled Initial Audit Pie Charts and Analysis containing a document with each pie chart and an analysis of the data collected from the initial audit.
To compare pie chart data to demographic data, let's compare data from the pie chart above to the Pima County ethnic profile. In the pie chart, 4.1% of main characters in adult popular fiction identify as Latinx. Taking the ethnic profile of Pima County, 37.7% of individuals identify as Latinx. A conclusion can be drawn that the Latinx representation of main characters in adult popular fiction is below the actual county profile. This comparison can be done between any main identifier and piece demographic data provided in this LibGuide under Demographic Research.
Additional identifiers were added as supplemental data shown in written form found under the title signifying the collection of pie charts in the pie chart analysis. The data is shown as percentages as well. For example, in the children's readers, 2.1% of authors identify as having a disability. In our case, we do not have demographic data to compare to additional identifier information. If you can find demographic data profiling any additional identifiers you utilize, use them for data comparison purposes.
The data collected gives Pima Community College Downtown Campus Library a diversity profile of some of their collections housed at a certain point of time. By comparing the data collected to Pima County demographic profiles, the library staff at Pima's Downtown Campus Library can visualize where they can improve and where they are doing well to ensure the collection reflects the diversity of their users.