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    1. quickmodel_ai on

      Based on feedback on the original post, here is the same data normalized by GDP.

      This is a data representation of all non profit programs found on publicly available 990s for the tax year 2023 categorized by their description as a percent of state GDP. These are the aggregate program expenses, not all expenses for all non-profits.
      To create the categorizations we generated embeddings for all program descriptions clustered them, then labelled clusters using an LLM.
      Tools used: matplotlib, sentence-transformers, umap, hdbscan.
      Data provided by [Npo Align](https://npoalign.com/?campaign=reddit) and and https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_GDP

    2. ethidium_bromide on

      What is the difference here between “Community Health Services” and “Community Healthcare Services”?

    3. KAugsburger on

      Honestly, I am surprised that the differences are as great as they are. The 990 forms don’t capture the spending of most churches and many smaller non-profits so there are some limitations but. That might explain some of the lower percentage in states that have a lot of people donating to churches.

      The only other pattern I seemed to notice was that generally older states seem to rank higher. I am guessing that is because their non-profits are generally older and more likely to have had time to build up endowments or large donor bases. There are some outliers though to that like New Jersey. It is one of the original 13 states but it ranks near the bottom. There must be some other factor that influence that but I am not familiar enough with the non-profit space to have a good theory on how New Jersey is different.

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