Teaching Data Storytelling: Michelle Alexander, The New Jim Crow, and the 2016 Election

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Kenton Rambsy

Michelle Alexander’s The New Jim Crow, inspired my student Kyle Aaron to create a visualization” that responds to a central tenet of the book. His Tableau Public visualization demonstrates how the 2016 presidential election might have had a different outcome if felons had the right to vote. In his results, he concludes that Minnesota would have possibly flipped in favor of Donald Trump, but Georgia, Florida, Minnesota, and Wisconsin would have gone to Hillary Clinton, giving her 288 electoral points and making her the president of the United States.

The FLOAT Method facilitated the ordering of Kyle’s thoughts, which in turn informed his research processes. He created this visualization using a dataset that compiled statistics such as the ineligibility percentage, winning margin percentage, eligible non-voter percentages, and likely voter affiliations in each state for 2016. He then created a projection model similar to election analysts to interpret mass incarceration’s impact on this presidential election. He used the data to calculate the probability of each state’s electoral vote if felons had the opportunity to cast ballots.

Kyle’s project underscores the importance of a well-thought-out research question. His original question “How impactful is disenfranchisement among felons in the 2016 US presidential election?” was too broad in scope when trying to analyze mass incarceration’s impact on presidential elections.

He revised his single question into three different inquiries:

1.) Which states had the possibility of changing their electoral vote in the election? 

2.) How would the electoral college count change nationally?

3.) Which political party has more people disenfranchised that could potentially flip the state? By doing offering these focused questions, he focused his analysis and decided upon a methodology that could yield specific answers.

Like Bailey Cannon’s project on voter disenfranchisement in Georgia, Kyle’s project focuses on a particular aspect of voting suppression tactics. Where Bailey looked at one state in particular, Kyle considered how disproportional conviction rates of Black and brown people possibly influence election outcomes. Taken together, their projects represent how deeply entrenched anti-black and institutional racist practices impede upon civil liberties. Moreover, their projects show how academic texts can stimulate visual interpretations.

In our graduate seminar, the FLOAT Method proved to be a useful (and iterative) step-by-step process that provided a blueprint for several types of data stories related to voter suppression tactics. My emphasis on data storytelling encourages my students to blur the lines between academic and social discourses by using quantitative and qualitative information to create visual narratives. Data visualizations offer one avenue by which we can translate academic ideas and circulate our findings in an online environment.