I reverse engineered mcdonald's internal api and I'm currently placing an order worth $18,752 every minute at every mcdonald's in the US to figure out which locations have a broken ice cream machine
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I ran the McBroken data through the Spatial Equity Data tool. apps.urban.org/features/equit It found McDonalds are slightly overrepresented in white areas (first image) while locations with broken ice cream machines skew Black and low-income. (second image)
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I believe it's about tracking the relative number of broken ice cream machines per census tract relative to the percentage of various groups in the same census tract.
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Interesting. Wonder if the skew falls to corporate or the franchisees.
Would need to look at it against franchisees owning multiple locations (common enough).
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The spatial equity tool checks against a number of variables. It happened to be race that showed the most skew.
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I don’t know how franchises work. Would low-income locations not be less likely or at least slower to fix/replace their equipment strictly based on finances? Do they get money from corporate to maintain these things or is it based solely on the individual owners? Neat tool!
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According to Dr. Milton Mills, 75% of all African Americans are lactose intolerant. Dairy products are constantly marketed to African American communities, despite the considerable evidence of the health problems that drinking #dairy can cause.
WATCH 
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Mark, I’m loving all of your comments on this thread 👌🏾 thx for them!
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