The team at ICPSR is doing some clever promotions of data for Love Data Week, including Adopt a Dataset! I adopted the Quantitative Data Coded from the Federal Writers’ Project Slave Narratives, United States, 1936-1938. I’ve read so much about this project and it seemed appropriate for February and Black History Month. You can read the actual interview transcripts on the Library of Congress website: Born in Slavery: Slave Narratives from the Federal Writers’ Project, 1936 to 1938. In the late 1970s, Paul Escott read and coded 2,358 of the slave narratives to create this dataset.
The narratives provide insight both into the process of the interview as well as the experiences of the formerly enslaved people. One of the most controversial questions was about attitudes toward the master, with some writers pointing to “favorable” attitudes toward masters as an indicator of slavery being a “less harsh” institution. But that ignores the fact that there were 771 who did not answer the question (or gave no indication of an answer in the narrative). In addition, around 1200 of the interviewers were white as opposed 400 who were black. In the 1930s American South, it would have been difficult for a person of color to speak ill of a white person in front of another white person. In addition, the coder’s interpretation of favorability needs to be taken into account.
ICPSR has made the dataset easy to use in R. The only trick is that the variables are mostly factors that need to be converted to numeric. ICPSR helpfully provides the R library and functions that can help with the conversion. Just remember to read the documentation closely before jumping in! Below are some my explorations including creating a subset of NC and another of NC women.
You should adopt a dataset and explore some data! You don’t need to know statistical software because the codebooks can provide some basic overviews of the dataset. In addition, many of their datasets have online analyses available.
Tomorrow you can join their tweetchat starting at 12:30 pm. Go and give some love to your data!