I’m using the Philadelphia Almshouse Admission data from 1796-1803. It contains a listing of most, if not all of the admissions to the almshouse from 1796-1893. It covers the John Adams and Thomas Jefferson presidencies which is interesting because Adams was a Federalist, while Jefferson was an anti-Federalist. I’m hoping to show some effects of the differing fiscal policies between the two competing political parties on racial and gender economic inequality. That date includes when people entered the almshouse and when they were discharged, what their “description” was which could include data such as job or economic station in life. I can clean the data to pull just that job information from that category. The data also includes gender, race, and when people were discharged and why.
The questions I have regarding this data, that I believe have answers within the data are:
- What are the seasonal patterns of employment in Philadelphia and just how intense were the ebbs and flows of almshouse admission based on time of year?
- Over time, was there a specific occupation or class of women that were excluded from the workforce? What types of jobs did women admitted to the almshouse hold and lose leading to their arrival?
- What is the relationship between poverty, age, race, and death in the almshouse during this period?
Hopefully some tableau graphs will show connections between some of these categories that could lead to additional research into things like embargoes, commerce laws, and politics later down the line.
Smith, Billy G., “Almshouse Admissions Philadelphia 1796-1803,” -. 42. Philadelphia, PA: McNeil Center for Early American Studies [distributor], 2020. https://repository.upenn.edu
One reply on “Mod. 6 Almshouse Data for Final Project”
This is a really interesting use of that dataset, and not something I would have thought of! I’m excited to see what you do with this. My gut says you will probably not be able to do much with question 2, but I think it’s worth pursuing just in case to see what you can find.
If you find yourself in need of a comparative case, I pulled down Boston Almshouse data for about the same period here. It’s VERY messy, which is why I didn’t link it in the final project datasets list and it doesn’t have as much occupation data as the Philadelphia data, but it covers 1797-1800 or so I think.
Joni is working on a similar thing of comparison between dates of laws and her data. If you have a handful of laws you want to mark in your data, you can do that with annotations; if you have a bunch, it may be worth your time making a separate spreadsheet with columns like:
year | law | type
and joining it to your almshouse data in Tableau. Joins can be kind of fussy, so if you end up pursuing that and get stuck, lmk.