Blog Post 6

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Hello! In my blog post this week, I decided to analyze the amount of Non-White free people per county in 1790.

I thought this was super interesting, frankly. It’s so interesting to me learning about the people who were considered “free” (air quotes are DEFINITELY necessary here) during this time period. I really enjoyed looking at the data and different census maps and learning about which places were more densely populated. You’ll notice in my map that there are more free people along the coast, which makes sense, and that in the south, there are very few free people. This was interesting to me to see, however. I think it is often hard to conceptualize just how few people were considered free during this time period simply because of the time gap between our generations. I enjoyed creating a map and physically seeing this data in action. I feel as though maps like this really help us understand slavery and its impacts on people. I think for many it is easy to disconnect from the topic of slavery since it’s taught as a history lesson. However, data like this really puts it in front of our faces, and helps people truly connect and understand history in a more comprehensive way – which I love!

One thought on “Blog Post 6

  1. I’m so glad to hear that you enjoyed this assignment and that you learned a lot from it! The process of using flourish can be challenging, but the results are totally worth it! Your map looks fantastic and I like how you chose to visualize populations of free nonwhite people in 1790. From what we can estimate, there were indeed populations of “free” people of color and those numbers were probably much higher in 1790 than they were in say, 1850, because of increased laws protecting/sanctioning slavery. I am definitely skeptical of these numbers, especially in places like Charleston County– 950 seems so high for a county in the south. It was a major port city for transporting enslaved people, so perhaps these numbers represent people of color who were captured/incarcerated and waiting to be sold into slavery? I’m not sure, but this data definitely raises some important questions!

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